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Graham Linck EJ, Goligher EC, Semler MW, Churpek MM. Toward Precision in Critical Care Research: Methods for Observational and Interventional Studies. Crit Care Med 2024; 52:1439-1450. [PMID: 39145702 PMCID: PMC11328956 DOI: 10.1097/ccm.0000000000006371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment's effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside.
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Affiliation(s)
- Emma J Graham Linck
- Department of Biostatistics and Medical Informatics, UW-Madison, Madison, WI
| | - Ewan C Goligher
- Interdepartmental Division of Critical Care Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Department of Physiology, University of Toronto, Toronto, ON, Canada
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
| | - Matthew W Semler
- Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | - Matthew M Churpek
- Department of Biostatistics and Medical Informatics, UW-Madison, Madison, WI
- Division of Pulmonary and Critical Care, Department of Medicine, University of Wisconsin-Madison, Madison, WI
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Howell CR, Zhang L, Clay OJ, Dutton G, Horton T, Mugavero MJ, Cherrington AL. Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis. JMIR Public Health Surveill 2024; 10:e53371. [PMID: 39113389 PMCID: PMC11322797 DOI: 10.2196/53371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 05/24/2024] [Accepted: 06/05/2024] [Indexed: 08/16/2024] Open
Abstract
Background Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor. Objective This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status. Methods Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs). Results Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79). Conclusions Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.
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Affiliation(s)
- Carrie R Howell
- Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Li Zhang
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Olivio J Clay
- Alzheimer’s Disease Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
- Deep South Resource Center for Minority Aging Research, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Gareth Dutton
- Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Trudi Horton
- Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Michael J Mugavero
- Division of Infectious Diseases, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Andrea L Cherrington
- Division of Preventive Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
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Gordon AC, Alipanah-Lechner N, Bos LD, Dianti J, Diaz JV, Finfer S, Fujii T, Giamarellos-Bourboulis EJ, Goligher EC, Gong MN, Karakike E, Liu VX, Lumlertgul N, Marshall JC, Menon DK, Meyer NJ, Munroe ES, Myatra SN, Ostermann M, Prescott HC, Randolph AG, Schenck EJ, Seymour CW, Shankar-Hari M, Singer M, Smit MR, Tanaka A, Taccone FS, Thompson BT, Torres LK, van der Poll T, Vincent JL, Calfee CS. From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU. Am J Respir Crit Care Med 2024; 210:155-166. [PMID: 38687499 PMCID: PMC11273306 DOI: 10.1164/rccm.202311-2086so] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 04/29/2024] [Indexed: 05/02/2024] Open
Abstract
Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.
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Affiliation(s)
| | - Narges Alipanah-Lechner
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
| | | | - Jose Dianti
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
- Departamento de Cuidados Intensivos, Centro de Educación Médica e Investigaciones Clínicas, Buenos Aires, Argentina
| | | | - Simon Finfer
- School of Public Health, Imperial College London, London, United Kingdom
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Tomoko Fujii
- Jikei University School of Medicine, Jikei University Hospital, Tokyo, Japan
| | | | - Ewan C. Goligher
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Michelle Ng Gong
- Division of Critical Care Medicine and
- Division of Pulmonary Medicine, Department of Medicine and Department of Epidemiology and Population Health, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York
| | - Eleni Karakike
- Second Department of Critical Care Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Vincent X. Liu
- Division of Research, Kaiser Permanente, Oakland, California
| | - Nuttha Lumlertgul
- Excellence Center for Critical Care Nephrology, Division of Nephrology, Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - John C. Marshall
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - David K. Menon
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Nuala J. Meyer
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Elizabeth S. Munroe
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Sheila N. Myatra
- Department of Anaesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Marlies Ostermann
- King’s College London, Guy’s & St Thomas’ Hospital, London, United Kingdom
| | - Hallie C. Prescott
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
- Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan
| | - Adrienne G. Randolph
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children’s Hospital, Boston, Massachusetts
- Department of Anaesthesia and
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
| | - Edward J. Schenck
- Division of Pulmonary and Critical Care Medicine, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Christopher W. Seymour
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Manu Shankar-Hari
- Centre for Inflammation Research, Institute of Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
| | - Mervyn Singer
- Bloomsbury Institute of Intensive Care Medicine, Division of Medicine, University College London, London, United Kingdom
| | | | - Aiko Tanaka
- Department of Intensive Care, University of Fukui Hospital, Yoshida, Fukui, Japan
- Department of Anesthesiology and Intensive Care Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Fabio S. Taccone
- Department des Soins Intensifs, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Brussels, Belgium; and
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Lisa K. Torres
- Division of Pulmonary and Critical Care Medicine, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Tom van der Poll
- Center of Experimental and Molecular Medicine, and
- Division of Infectious Diseases, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Jean-Louis Vincent
- Department des Soins Intensifs, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles (ULB), Brussels, Belgium; and
| | - Carolyn S. Calfee
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
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Kiernan E, Zelnick LR, Khader A, Coston TD, Bailey ZA, Speckmaier S, Lo J, Sathe N, Kestenbaum BR, Himmelfarb J, Johnson N, Shapiro N, Douglas IS, Hough C, Bhatraju P. Molecular Phenotyping of Patients with Sepsis and Kidney Injury and Differential Response to Fluid Resuscitation. RESEARCH SQUARE 2024:rs.3.rs-4523416. [PMID: 39011119 PMCID: PMC11247924 DOI: 10.21203/rs.3.rs-4523416/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Purpose Previous work has identified two AKI sub-phenotypes (SP1 and SP2) characterized by differences in inflammation and endothelial dysfunction. Here we identify these sub-phenotypes using biospecimens collected in the emergency department and test for differential response to restrictive versus liberal fluid strategy in sepsis-induced hypotension in the CLOVERS trial. Methods We applied a previously validated 3-biomarker model using plasma angiopietin-1 and 2, and soluble tumor necrosis factor receptor-1 to classify sub-phenotypes in patients with kidney dysfunction (AKI or end-stage kidney disease [ESKD]). We also compared a de novo latent class analysis (LCA) to the 3-biomarker based sub-phenotypes. Kaplan-Meier estimates were used to test for differences in outcomes and sub-phenotype by treatment interaction. Results Among 1289 patients, 846 had kidney dysfunction on enrollment and the 3-variable prediction model identified 605 as SP1 and 241 as SP2. The optimal LCA model identified two sub-phenotypes with high correlation with the 3-biomarker model (Cohen's Kappa 0.8). The risk of 28 and 90-day mortality was greater in SP2 relative to SP1 independent of AKI stage and SOFA scores. Patients with SP2, characterized by more severe endothelial injury and inflammation, had a reduction in 28-day mortality with a restrictive fluid strategy versus a liberal fluid strategy (26% vs 41%), while patients with SP1 had no difference in 28-day mortality (10% vs 11%) (p-value-for-interaction = 0.03). Conclusion Sub-phenotypes can be identified in the emergency department that respond differently to fluid strategy in sepsis. Identification of these sub-phenotypes could inform a precision-guided therapeutic approach for patients with sepsis-induced hypotension and kidney injury.
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Tamura H, Yasuda H, Oishi T, Shinzato Y, Amagasa S, Kashiura M, Moriya T. Association between sub-phenotypes identified using latent class analysis and neurological outcomes in patients with out-of-hospital cardiac arrest in Japan. BMC Cardiovasc Disord 2024; 24:303. [PMID: 38877462 PMCID: PMC11177357 DOI: 10.1186/s12872-024-03975-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 06/10/2024] [Indexed: 06/16/2024] Open
Abstract
BACKGROUND In patients who experience out-of-hospital cardiac arrest (OHCA), it is important to assess the association of sub-phenotypes identified by latent class analysis (LCA) using pre-hospital prognostic factors and factors measurable immediately after hospital arrival with neurological outcomes at 30 days, which would aid in making treatment decisions. METHODS This study retrospectively analyzed data obtained from the Japanese OHCA registry between June 2014 and December 2019. The registry included a complete set of data on adult patients with OHCA, which was used in the LCA. The association between the sub-phenotypes and 30-day survival with favorable neurological outcomes was investigated. Furthermore, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by multivariate logistic regression analysis using in-hospital data as covariates. RESULTS A total of, 22,261 adult patients who experienced OHCA were classified into three sub-phenotypes. The factor with the highest discriminative power upon patient's arrival was Glasgow Coma Scale followed by partial pressure of oxygen. Thirty-day survival with favorable neurological outcome as the primary outcome was evident in 66.0% participants in Group 1, 5.2% in Group 2, and 0.5% in Group 3. The 30-day survival rates were 80.6%, 11.8%, and 1.3% in groups 1, 2, and 3, respectively. Logistic regression analysis revealed that the ORs (95% CI) for 30-day survival with favorable neurological outcomes were 137.1 (99.4-192.2) for Group 1 and 4.59 (3.46-6.23) for Group 2 in comparison to Group 3. For 30-day survival, the ORs (95%CI) were 161.7 (124.2-212.1) for Group 1 and 5.78 (4.78-7.04) for Group 2, compared to Group 3. CONCLUSIONS This study identified three sub-phenotypes based on the prognostic factors available immediately after hospital arrival that could predict neurological outcomes and be useful in determining the treatment strategy of patients experiencing OHCA upon their arrival at the hospital.
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Affiliation(s)
- Hiroyuki Tamura
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan
| | - Hideto Yasuda
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan.
| | - Takatoshi Oishi
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan
| | - Yutaro Shinzato
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan
| | - Shunsuke Amagasa
- Division of Emergency and Transport Services, National Center for Child Health and Development, Tokyo, Japan
| | - Masahiro Kashiura
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan
| | - Takashi Moriya
- Department of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847 Amanuma-Cho, Omiya-Ku, Saitama-Shi, Saitama, 330-8503, Japan
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Leis AM, Hurvitz EA, Whitney DG. Comorbidity Clusters Among Adults With Cerebral Palsy: A Latent Class Analysis. Am J Prev Med 2024; 66:971-979. [PMID: 38278372 DOI: 10.1016/j.amepre.2024.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 01/28/2024]
Abstract
INTRODUCTION Adults with cerebral palsy are at risk for early multimorbidity onset, but little is known about the composition of multimorbidity profiles or how these profiles present across adulthood. The objective of this study was to identify multimorbidity profiles and association with mortality among adults with cerebral palsy. METHODS This retrospective cohort study used a random 20% fee-for-service Medicare database from January 1, 2008 to December 31, 2019 from adults aged ≥18 years with cerebral palsy. Latent class analyses using 4-class models were conducted within each age cohort (young adults aged 18-39 years, middle adulthood aged 40-64 years, and older adults aged ≥65 years) to determine patterns of 30 comorbidities defined using the International Classification of Diseases, Ninth Revision codes, identified from January 1, 2008 to December 31, 2010, and their association with mortality through December 31, 2019 (up to 11 years of follow-up); statistical analysis was performed in 2023. RESULTS Three classes were relatively consistent in the composition of comorbidities across young (n=7,020), middle (n=13,554), and older (n=4,193) cohorts: (1) low morbidity (low proportion of all comorbidities) representing 50.1% (young), 41.4% (middle), and 30.9% (older) of the cohorts; (2) neurologic multimorbidity (e.g., epilepsy, intellectual disabilities) representing 26.0% (young), 26.6% (middle), and 14.7% (older) of the cohorts; and complex multimorbidity (e.g., cardiorespiratory, nutritional, musculoskeletal, neurologic) representing 26.0% (young), 26.6% (middle), and 14.7% (older) of the cohorts. The fourth class varied by young (mental health disorders), middle (hypertension), and older (hypertension and osteoarthritis) age cohorts. Compared with the low morbidity class, other classes had an increased mortality rate for each age cohort (hazard ratio range=1.34-5.58, all p<0.001). CONCLUSIONS Findings provide insight into varied multimorbidity profiles and associations with mortality across the life course for adults with cerebral palsy.
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Affiliation(s)
- Aleda M Leis
- Epidemiology Department, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Edward A Hurvitz
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, Michigan
| | - Daniel G Whitney
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, Michigan; Institute for Healthcare Policy & Innovation, University of Michigan, Ann Arbor, Michigan.
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Zurawel AA, Coates BM. Time to split: biomarker trajectories in pediatric acute respiratory distress syndrome hint at underlying disease. J Clin Invest 2024; 134:e180662. [PMID: 38747286 PMCID: PMC11093594 DOI: 10.1172/jci180662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2024] Open
Abstract
Pediatric acute respiratory distress syndrome (ARDS) is severe, noncardiac hypoxemic respiratory failure that carries a substantial risk of death. Given the complexity of this clinically defined syndrome and the repeated failure of therapeutic trials, there has been an effort to identify subphenotypes of ARDS that may share targetable mechanisms of disease. In this issue of the JCI, Yehya and colleagues measured 19 plasma biomarkers in 279 children over the first seven days of ARDS. Increases in select tissue injury makers and inflammatory cytokines in peripheral blood were associated with multiple organ dysfunction syndrome and death, but not persistent ARDS. These findings argue that splitting patients by clinical and molecular phenotype may be more informative than lumping them under the umbrella diagnosis of ARDS. However, future studies are needed to determine whether these plasma factors represent targetable pathways in lung injury or are a consequence of systemic organ dysfunction.
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Affiliation(s)
- Ashley A. Zurawel
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois, USA
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Bria M. Coates
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois, USA
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Evrard B, Sinha P, Delucchi K, Hendrickson CM, Kangelaris KN, Liu KD, Willmore A, Wu N, Neyton L, Schmiege E, Gomez A, Kerchberger VE, Zalucky A, Matthay MA, Ware LB, Calfee CS. Causes and attributable fraction of death from ARDS in inflammatory phenotypes of sepsis. Crit Care 2024; 28:164. [PMID: 38745253 PMCID: PMC11092165 DOI: 10.1186/s13054-024-04943-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 05/06/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Hypoinflammatory and hyperinflammatory phenotypes have been identified in both Acute Respiratory Distress Syndrome (ARDS) and sepsis. Attributable mortality of ARDS in each phenotype of sepsis is yet to be determined. We aimed to estimate the population attributable fraction of death from ARDS (PAFARDS) in hypoinflammatory and hyperinflammatory sepsis, and to determine the primary cause of death within each phenotype. METHODS We studied 1737 patients with sepsis from two prospective cohorts. Patients were previously assigned to the hyperinflammatory or hypoinflammatory phenotype using latent class analysis. The PAFARDS in patients with sepsis was estimated separately in the hypo and hyperinflammatory phenotypes. Organ dysfunction, severe comorbidities, and withdrawal of life support were abstracted from the medical record in a subset of patients from the EARLI cohort who died (n = 130/179). Primary cause of death was defined as the organ system that most directly contributed to death or withdrawal of life support. RESULTS The PAFARDS was 19% (95%CI 10,28%) in hypoinflammatory sepsis and, 14% (95%CI 6,20%) in hyperinflammatory sepsis. Cause of death differed between the two phenotypes (p < 0.001). Respiratory failure was the most common cause of death in hypoinflammatory sepsis, whereas circulatory shock was the most common cause in hyperinflammatory sepsis. Death with severe underlying comorbidities was more frequent in hypoinflammatory sepsis (81% vs. 67%, p = 0.004). CONCLUSIONS The PAFARDS is modest in both phenotypes whereas primary cause of death among patients with sepsis differed substantially by phenotype. This study identifies challenges in powering future clinical trials to detect changes in mortality outcomes among patients with sepsis and ARDS.
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Affiliation(s)
- Bruno Evrard
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
- Inserm CIC 1435, Dupuytren Teaching Hospital, 87000, Limoges, France.
| | - Pratik Sinha
- Division of Clinical and Translational Research, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Anesthesia, Division of Critical Care, Washington University, Saint Louis, MO, USA
| | - Kevin Delucchi
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Carolyn M Hendrickson
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kathleen D Liu
- Division of Nephrology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
| | - Andrew Willmore
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Nelson Wu
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Lucile Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Emma Schmiege
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Antonio Gomez
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | - V Eric Kerchberger
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ann Zalucky
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Lorraine B Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
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Choudhary T, Upadhyaya P, Davis CM, Yang P, Tallowin S, Lisboa FA, Schobel SA, Coopersmith CM, Elster EA, Buchman TG, Dente CJ, Kamaleswaran R. Derivation and Validation of Generalized Sepsis-induced Acute Respiratory Failure Phenotypes Among Critically Ill Patients: A Retrospective Study. RESEARCH SQUARE 2024:rs.3.rs-4307475. [PMID: 38746442 PMCID: PMC11092838 DOI: 10.21203/rs.3.rs-4307475/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate their generalizability across multi-ICU specialties, considering multi-organ dynamics. Methods We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥24 hours. Data from two different high-volume academic hospital systems were used as a derivation set with N=3,225 medical ICU (MICU) patients and a validation set with N=848 MICU patients. For the multi-ICU validation, we utilized retrospective data from two surgical ICUs at the same hospitals (N=1,577). Clinical data from 24 hours preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts. Results Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F=123]), C (mild hypoxia [median P/F=240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing an external MICU from second hospital and SICUs from both centers. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p<0.01) and consistent across both centers. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy. Conclusion The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Eric A Elster
- Uniformed Services University of the Health Sciences
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10
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Valda Toro PL, Willmore A, Wu NE, Delucchi KL, Jauregui A, Sinha P, Liu KD, Hendrickson CM, Sarma A, Neyton LPA, Leligdowicz A, Langelier CR, Zhuo H, Jones C, Kangelaris KN, Gomez AD, Matthay MA, Calfee CS. Rapidly improving ARDS differs clinically and biologically from persistent ARDS. Crit Care 2024; 28:132. [PMID: 38649920 PMCID: PMC11034037 DOI: 10.1186/s13054-024-04883-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/20/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Rapidly improving acute respiratory distress syndrome (RIARDS) is an increasingly appreciated subgroup of ARDS in which hypoxemia improves within 24 h after initiation of mechanical ventilation. Detailed clinical and biological features of RIARDS have not been clearly defined, and it is unknown whether RIARDS is associated with the hypoinflammatory or hyperinflammatory phenotype of ARDS. The purpose of this study was to define the clinical and biological features of RIARDS and its association with inflammatory subphenotypes. METHODS We analyzed data from 215 patients who met Berlin criteria for ARDS (endotracheally intubated) and were enrolled in a prospective observational cohort conducted at two sites, one tertiary care center and one urban safety net hospital. RIARDS was defined according to previous studies as improvement of hypoxemia defined as (i) PaO2:FiO2 > 300 or (ii) SpO2: FiO2 > 315 on the day following diagnosis of ARDS (day 2) or (iii) unassisted breathing by day 2 and for the next 48 h (defined as absence of endotracheal intubation on day 2 through day 4). Plasma biomarkers were measured on samples collected on the day of study enrollment, and ARDS phenotypes were allocated as previously described. RESULTS RIARDS accounted for 21% of all ARDS participants. Patients with RIARDS had better clinical outcomes compared to those with persistent ARDS, with lower hospital mortality (13% vs. 57%; p value < 0.001) and more ICU-free days (median 24 vs. 0; p value < 0.001). Plasma levels of interleukin-6, interleukin-8, and plasminogen activator inhibitor-1 were significantly lower among patients with RIARDS. The hypoinflammatory phenotype of ARDS was more common among patients with RIARDS (78% vs. 51% in persistent ARDS; p value = 0.001). CONCLUSIONS This study identifies a high prevalence of RIARDS in a multicenter observational cohort and confirms the more benign clinical course of these patients. We report the novel finding that RIARDS is characterized by lower concentrations of plasma biomarkers of inflammation compared to persistent ARDS, and that hypoinflammatory ARDS is more prevalent among patients with RIARDS. Identification and exclusion of RIARDS could potentially improve prognostic and predictive enrichment in clinical trials.
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Affiliation(s)
- Patricia L Valda Toro
- Department of Medicine, Division of Pulmonary and Critical Care, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Internal Medicine, University of California San Francisco, San Francisco, USA.
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Nelson E Wu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Kevin L Delucchi
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Alejandra Jauregui
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Pratik Sinha
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Kathleen D Liu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Carolyn M Hendrickson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Lucile P A Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Charles R Langelier
- Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Hanjing Zhuo
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Chayse Jones
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Antonio D Gomez
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
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11
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Yehya N, Booth TJ, Ardhanari GD, Thompson JM, Lam LM, Till JE, Mai MV, Keim G, McKeone DJ, Halstead ES, Lahni P, Varisco BM, Zhou W, Carpenter EL, Christie JD, Mangalmurti NS. Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome. J Clin Invest 2024; 134:e177896. [PMID: 38573766 PMCID: PMC11093602 DOI: 10.1172/jci177896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/27/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUNDThe molecular signature of pediatric acute respiratory distress syndrome (ARDS) is poorly described, and the degree to which hyperinflammation or specific tissue injury contributes to outcomes is unknown. Therefore, we profiled inflammation and tissue injury dynamics over the first 7 days of ARDS, and associated specific biomarkers with mortality, persistent ARDS, and persistent multiple organ dysfunction syndrome (MODS).METHODSIn a single-center prospective cohort of intubated pediatric patients with ARDS, we collected plasma on days 0, 3, and 7. Nineteen biomarkers reflecting inflammation, tissue injury, and damage-associated molecular patterns (DAMPs) were measured. We assessed the relationship between biomarkers and trajectories with mortality, persistent ARDS, or persistent MODS using multivariable mixed effect models.RESULTSIn 279 patients (64 [23%] nonsurvivors), hyperinflammatory cytokines, tissue injury markers, and DAMPs were higher in nonsurvivors. Survivors and nonsurvivors showed different biomarker trajectories. IL-1α, soluble tumor necrosis factor receptor 1, angiopoietin 2 (ANG2), and surfactant protein D increased in nonsurvivors, while DAMPs remained persistently elevated. ANG2 and procollagen type III N-terminal peptide were associated with persistent ARDS, whereas multiple cytokines, tissue injury markers, and DAMPs were associated with persistent MODS. Corticosteroid use did not impact the association of biomarker levels or trajectory with mortality.CONCLUSIONSPediatric ARDS survivors and nonsurvivors had distinct biomarker trajectories, with cytokines, endothelial and alveolar epithelial injury, and DAMPs elevated in nonsurvivors. Mortality markers overlapped with markers associated with persistent MODS, rather than persistent ARDS.FUNDINGNIH (K23HL-136688, R01-HL148054).
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Affiliation(s)
- Nadir Yehya
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia and
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Thomas J. Booth
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia and
| | - Gnana D. Ardhanari
- Division of Pediatric Cardiac Critical Care Medicine, Children’s Heart Institute, Memorial Hermann Hospital, University of Texas Health McGovern Medical School, Houston, Texas, USA
| | - Jill M. Thompson
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia and
| | - L.K. Metthew Lam
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Department of Medicine and
| | - Jacob E. Till
- Division of Hematology-Oncology, Department of Medicine, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mark V. Mai
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Children’s Healthcare of Atlanta and Emory University, Atlanta, Georgia, USA
| | - Garrett Keim
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia and
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Daniel J. McKeone
- Division of Pediatric Hematology and Oncology, Department of Pediatrics and
| | - E. Scott Halstead
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Patrick Lahni
- Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Brian M. Varisco
- Section of Critical Care, Department of Pediatrics, University of Arkansas for Medical Sciences and Arkansas Children’s Research Institute, Little Rock, Arkansas, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Erica L. Carpenter
- Division of Hematology-Oncology, Department of Medicine, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jason D. Christie
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Department of Medicine and
- Center for Translational Lung Biology and
- Center for Clinical Epidemiology and Biostatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nilam S. Mangalmurti
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Department of Medicine and
- Center for Translational Lung Biology and
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12
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Patel BM, Reilly JP, Bhalla AK, Smith LS, Khemani RG, Jones TK, Meyer NJ, Harhay MO, Yehya N. Association between Age and Mortality in Pediatric and Adult Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med 2024; 209:871-878. [PMID: 38306669 PMCID: PMC10995578 DOI: 10.1164/rccm.202310-1926oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 02/02/2024] [Indexed: 02/04/2024] Open
Abstract
Rationale: The epidemiology, management, and outcomes of acute respiratory distress syndrome (ARDS) differ between children and adults, with lower mortality rates in children despite comparable severity of hypoxemia. However, the relationship between age and mortality is unclear.Objective: We aimed to define the association between age and mortality in ARDS, hypothesizing that it would be nonlinear.Methods: We performed a retrospective cohort study using data from two pediatric ARDS observational cohorts (n = 1,236), multiple adult ARDS trials (n = 5,547), and an adult observational ARDS cohort (n = 1,079). We aligned all datasets to meet Berlin criteria. We performed unadjusted and adjusted logistic regression using fractional polynomials to assess the potentially nonlinear relationship between age and 90-day mortality, adjusting for sex, PaO2/FiO2, immunosuppressed status, year of study, and observational versus randomized controlled trial, treating each individual study as a fixed effect.Measurements and Main Results: There were 7,862 subjects with median ages of 4 years in the pediatric cohorts, 52 years in the adult trials, and 61 years in the adult observational cohort. Most subjects (43%) had moderate ARDS by Berlin criteria. Ninety-day mortality was 19% in the pediatric cohorts, 33% in the adult trials, and 67% in the adult observational cohort. We found a nonlinear relationship between age and mortality, with mortality risk increasing at an accelerating rate between 11 and 65 years of age, after which mortality risk increased more slowly.Conclusions: There was a nonlinear relationship between age and mortality in pediatric and adult ARDS.
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Affiliation(s)
- Bhavesh M Patel
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - John P Reilly
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine
- Center for Translational Lung Biology, and
| | - Anoopindar K Bhalla
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Children's Hospital Los Angeles, Los Angeles, California; and
| | - Lincoln S Smith
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Washington, Seattle, Washington
| | - Robinder G Khemani
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Children's Hospital Los Angeles, Los Angeles, California; and
| | - Tiffanie K Jones
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine
- Center for Translational Lung Biology, and
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nuala J Meyer
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine
- Center for Translational Lung Biology, and
| | - Michael O Harhay
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Nadir Yehya
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
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13
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Levy E, Reilly JP. Pharmacologic Treatments in Acute Respiratory Failure. Crit Care Clin 2024; 40:275-289. [PMID: 38432696 DOI: 10.1016/j.ccc.2023.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Acute respiratory failure relies on supportive care using non-invasive and invasive oxygen and ventilatory support. Pharmacologic therapies for the most severe form of respiratory failure, acute respiratory distress syndrome (ARDS), are limited. This review focuses on the most promising therapies for ARDS, targeting different mechanisms that contribute to dysregulated inflammation and resultant hypoxemia. Significant heterogeneity exists within the ARDS population. Treatment requires prompt recognition of ARDS and an understanding of which patients may benefit most from specific pharmacologic interventions. The key to finding effective pharmacotherapies for ARDS may rely on deeper understanding of pathophysiology and bedside identification of ARDS subphenotypes.
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Affiliation(s)
- Elizabeth Levy
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, 3400 Spruce Street, Philadelphia, PA 19146, USA
| | - John P Reilly
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, 3400 Spruce Street, Philadelphia, PA 19146, USA.
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14
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Sinha P, Neyton L, Sarma A, Wu N, Jones C, Zhuo H, Liu KD, Sanchez Guerrero E, Ghale R, Love C, Mick E, Delucchi KL, Langelier CR, Thompson BT, Matthay MA, Calfee CS. Molecular Phenotypes of Acute Respiratory Distress Syndrome in the ROSE Trial Have Differential Outcomes and Gene Expression Patterns That Differ at Baseline and Longitudinally over Time. Am J Respir Crit Care Med 2024; 209:816-828. [PMID: 38345571 PMCID: PMC10995566 DOI: 10.1164/rccm.202308-1490oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 02/12/2024] [Indexed: 03/03/2024] Open
Abstract
Rationale: Two molecular phenotypes have been identified in acute respiratory distress syndrome (ARDS). In the ROSE (Reevaluation of Systemic Early Neuromuscular Blockade) trial of cisatracurium in moderate to severe ARDS, we addressed three unanswered questions: 1) Do the same phenotypes emerge in a more severe ARDS cohort with earlier recruitment; 2) Do phenotypes respond differently to neuromuscular blockade? and 3) What biological pathways most differentiate inflammatory phenotypes?Methods: We performed latent class analysis in ROSE using preenrollment clinical and protein biomarkers. In a subset of patients (n = 134), we sequenced whole-blood RNA using enrollment and Day 2 samples and performed differential gene expression and pathway analyses. Informed by the differential gene expression analysis, we measured additional plasma proteins and evaluated their abundance relative to gene expression amounts.Measurements and Main Results: In ROSE, we identified the hypoinflammatory (60.4%) and hyperinflammatory (39.6%) phenotypes with similar biological and clinical characteristics as prior studies, including higher mortality at Day 90 for the hyperinflammatory phenotype (30.3% vs. 61.6%; P < 0.0001). We observed no treatment interaction between the phenotypes and randomized groups for mortality. The hyperinflammatory phenotype was enriched for genes associated with innate immune response, tissue remodeling, and zinc metabolism at Day 0 and collagen synthesis and neutrophil degranulation at Day 2. Longitudinal changes in gene expression patterns differed dependent on survivorship. For most highly expressed genes, we observed correlations with their corresponding plasma proteins' abundance. However, for the class-defining plasma proteins in the latent class analysis, no correlation was observed with their corresponding genes' expression.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have different clinical, protein, and dynamic transcriptional characteristics. These findings support the clinical and biological potential of molecular phenotypes to advance precision care in ARDS.
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Affiliation(s)
- Pratik Sinha
- Division of Clinical and Translational Research, Division of Critical Care, Department of Anesthesia, Washington University School of Medicine, St. Louis, Missouri
| | - Lucile Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Nelson Wu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Chayse Jones
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Hanjing Zhuo
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Kathleen D. Liu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Division of Nephrology, and
| | | | - Rajani Ghale
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Division of Infectious Diseases, Department of Medicine
| | | | - Eran Mick
- Division of Infectious Diseases, Department of Medicine
- Chan Zuckerberg Biohub, San Francisco, California; and
| | | | - Charles R. Langelier
- Division of Infectious Diseases, Department of Medicine
- Chan Zuckerberg Biohub, San Francisco, California; and
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Michael A. Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Department of Anesthesia, University of California, San Francisco, San Francisco, California
| | - Carolyn S. Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Department of Anesthesia, University of California, San Francisco, San Francisco, California
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15
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Neyton LPA, Sinha P, Sarma A, Mick E, Kalantar K, Chen S, Wu N, Delucchi K, Zhuo H, Bos LDJ, Jauregui A, Gomez A, Hendrickson CM, Kangelaris KN, Leligdowicz A, Liu KD, Matthay MA, Langelier CR, Calfee CS. Host and Microbe Blood Metagenomics Reveals Key Pathways Characterizing Critical Illness Phenotypes. Am J Respir Crit Care Med 2024; 209:805-815. [PMID: 38190719 PMCID: PMC10995577 DOI: 10.1164/rccm.202308-1328oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/08/2024] [Indexed: 01/10/2024] Open
Abstract
Rationale: Two molecular phenotypes of sepsis and acute respiratory distress syndrome, termed hyperinflammatory and hypoinflammatory, have been consistently identified by latent class analysis in numerous cohorts, with widely divergent clinical outcomes and differential responses to some treatments; however, the key biological differences between these phenotypes remain poorly understood.Objectives: We used host and microbe metagenomic sequencing data from blood to deepen our understanding of biological differences between latent class analysis-derived phenotypes and to assess concordance between the latent class analysis-derived phenotypes and phenotypes reported by other investigative groups (e.g., Sepsis Response Signature [SRS1-2], molecular diagnosis and risk stratification of sepsis [MARS1-4], reactive and uninflamed).Methods: We analyzed data from 113 patients with hypoinflammatory sepsis and 76 patients with hyperinflammatory sepsis enrolled in a two-hospital prospective cohort study. Molecular phenotypes had been previously assigned using latent class analysis.Measurements and Main Results: The hyperinflammatory and hypoinflammatory phenotypes of sepsis had distinct gene expression signatures, with 5,755 genes (31%) differentially expressed. The hyperinflammatory phenotype was associated with elevated expression of innate immune response genes, whereas the hypoinflammatory phenotype was associated with elevated expression of adaptive immune response genes and, notably, T cell response genes. Plasma metagenomic analysis identified differences in prevalence of bacteremia, bacterial DNA abundance, and composition between the phenotypes, with an increased presence and abundance of Enterobacteriaceae in the hyperinflammatory phenotype. Significant overlap was observed between these phenotypes and previously identified transcriptional subtypes of acute respiratory distress syndrome (reactive and uninflamed) and sepsis (SRS1-2). Analysis of data from the VANISH trial indicated that corticosteroids might have a detrimental effect in patients with the hypoinflammatory phenotype.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have distinct transcriptional and metagenomic features that could be leveraged for precision treatment strategies.
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Affiliation(s)
| | - Pratik Sinha
- Department of Anesthesiology, Washington University in St. Louis, St. Louis, Missouri
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | - Eran Mick
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Division of Infectious Diseases
- Chan Zuckerberg Biohub, San Francisco, California
| | | | | | - Nelson Wu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
| | | | | | - Lieuwe D J Bos
- Department of Intensive Care and Laboratory of Experimental Intensive Care and Anesthesiology, Academic Medical Center, Amsterdam, the Netherlands
| | | | - Antonio Gomez
- Department of Medicine
- Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, California; and
| | - Carolyn M Hendrickson
- Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, California; and
| | | | | | | | - Michael A Matthay
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California
| | - Charles R Langelier
- Division of Infectious Diseases
- Chan Zuckerberg Biohub, San Francisco, California
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine
- Department of Anesthesiology, and
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California
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16
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Yang P, Sjoding MW. Acute Respiratory Distress Syndrome: Definition, Diagnosis, and Routine Management. Crit Care Clin 2024; 40:309-327. [PMID: 38432698 DOI: 10.1016/j.ccc.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury characterized by severe hypoxemic respiratory failure, bilateral opacities on chest imaging, and low lung compliance. ARDS is a heterogeneous syndrome that is the common end point of a wide variety of predisposing conditions, with complex pathophysiology and underlying mechanisms. Routine management of ARDS is centered on lung-protective ventilation strategies such as low tidal volume ventilation and targeting low airway pressures to avoid exacerbation of lung injury, as well as a conservative fluid management strategy.
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Affiliation(s)
- Philip Yang
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University, 6335 Hospital Parkway, Physicians Plaza Suite 310, Johns Creek, GA 30097, USA.
| | - Michael W Sjoding
- Division of Pulmonary and Critical Care Medicine, University of Michigan, 2800 Plymouth Road, NCRC, Building 16, G027W, Ann Arbor, MI 48109, USA
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17
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Dolinay T, Hsu L, Maller A, Walsh BC, Szűcs A, Jerng JS, Jun D. Ventilator Weaning in Prolonged Mechanical Ventilation-A Narrative Review. J Clin Med 2024; 13:1909. [PMID: 38610674 PMCID: PMC11012923 DOI: 10.3390/jcm13071909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/11/2024] [Accepted: 03/22/2024] [Indexed: 04/14/2024] Open
Abstract
Patients requiring mechanical ventilation (MV) beyond 21 days, usually referred to as prolonged MV, represent a unique group with significant medical needs and a generally poor prognosis. Research suggests that approximately 10% of all MV patients will need prolonged ventilatory care, and that number will continue to rise. Although we have extensive knowledge of MV in the acute care setting, less is known about care in the post-ICU setting. More than 50% of patients who were deemed unweanable in the ICU will be liberated from MV in the post-acute setting. Prolonged MV also presents a challenge in care for medically complex, elderly, socioeconomically disadvantaged and marginalized individuals, usually at the end of their life. Patients and their families often rely on ventilator weaning facilities and skilled nursing homes for the continuation of care, but home ventilation is becoming more common. The focus of this review is to discuss recent advances in the weaning strategies in prolonged MV, present their outcomes and provide insight into the complexity of care.
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Affiliation(s)
- Tamás Dolinay
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; (L.H.); (A.M.); (B.C.W.); (D.J.)
- Barlow Respiratory Hospital, Los Angeles, CA 90026, USA
| | - Lillian Hsu
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; (L.H.); (A.M.); (B.C.W.); (D.J.)
- Barlow Respiratory Hospital, Los Angeles, CA 90026, USA
| | - Abigail Maller
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; (L.H.); (A.M.); (B.C.W.); (D.J.)
- Barlow Respiratory Hospital, Los Angeles, CA 90026, USA
| | - Brandon Corbett Walsh
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; (L.H.); (A.M.); (B.C.W.); (D.J.)
- Barlow Respiratory Hospital, Los Angeles, CA 90026, USA
- Department of Medicine, Division of Palliative Care Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Attila Szűcs
- Department of Anesthesiology, András Jósa County Hospital, 4400 Nyíregyháza, Hungary;
| | - Jih-Shuin Jerng
- Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, National Taiwan University Hospital, Taipei 100, Taiwan;
| | - Dale Jun
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; (L.H.); (A.M.); (B.C.W.); (D.J.)
- Barlow Respiratory Hospital, Los Angeles, CA 90026, USA
- Pulmonary, Critical Care and Sleep Section, West Los Angeles VA Medical Center, Los Angeles, CA 90073, USA
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18
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Alipanah-Lechner N, Hurst-Hopf J, Delucchi K, Swigart L, Willmore A, LaCombe B, Dewar R, Lane HC, Lallemand P, Liu KD, Esserman L, Matthay MA, Calfee CS. Novel subtypes of severe COVID-19 respiratory failure based on biological heterogeneity: a secondary analysis of a randomized controlled trial. Crit Care 2024; 28:56. [PMID: 38383504 PMCID: PMC10882728 DOI: 10.1186/s13054-024-04819-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 01/25/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Despite evidence associating inflammatory biomarkers with worse outcomes in hospitalized adults with COVID-19, trials of immunomodulatory therapies have met with mixed results, likely due in part to biological heterogeneity of participants. Latent class analysis (LCA) of clinical and protein biomarker data has identified two subtypes of non-COVID acute respiratory distress syndrome (ARDS) with different clinical outcomes and treatment responses. We studied biological heterogeneity and clinical outcomes in a multi-institutional platform randomized controlled trial of adults with severe COVID-19 hypoxemic respiratory failure (I-SPY COVID). METHODS Clinical and plasma protein biomarker data were analyzed from 400 trial participants enrolled from September 2020 until October 2021 with severe COVID-19 requiring ≥ 6 L/min supplemental oxygen. Seventeen hypothesis-directed protein biomarkers were measured at enrollment using multiplex Luminex panels or single analyte enzyme linked immunoassay methods (ELISA). Biomarkers and clinical variables were used to test for latent subtypes and longitudinal biomarker changes by subtype were explored. A validated parsimonious model using interleukin-8, bicarbonate, and protein C was used for comparison with non-COVID hyper- and hypo-inflammatory ARDS subtypes. RESULTS Average participant age was 60 ± 14 years; 67% were male, and 28-day mortality was 25%. At trial enrollment, 85% of participants required high flow oxygen or non-invasive ventilation, and 97% were receiving dexamethasone. Several biomarkers of inflammation (IL-6, IL-8, IL-10, sTNFR-1, TREM-1), epithelial injury (sRAGE), and endothelial injury (Ang-1, thrombomodulin) were associated with 28- and 60-day mortality. Two latent subtypes were identified. Subtype 2 (27% of participants) was characterized by persistent derangements in biomarkers of inflammation, endothelial and epithelial injury, and disordered coagulation and had twice the mortality rate compared with Subtype 1. Only one person was classified as hyper-inflammatory using the previously validated non-COVID ARDS model. CONCLUSIONS We discovered evidence of two novel biological subtypes of severe COVID-19 with significantly different clinical outcomes. These subtypes differed from previously established hyper- and hypo-inflammatory non-COVID subtypes of ARDS. Biological heterogeneity may explain inconsistent findings from trials of hospitalized patients with COVID-19 and guide treatment approaches.
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Affiliation(s)
- Narges Alipanah-Lechner
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA.
| | - James Hurst-Hopf
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA
| | - Kevin Delucchi
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Lamorna Swigart
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA
| | - Benjamin LaCombe
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA
| | - Robin Dewar
- Virus Isolation and Serology Laboratory, Applied and Developmental Directorate, Frederick National Laboratory, Frederick, MD, USA
| | - H Clifford Lane
- Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Perrine Lallemand
- Virus Isolation and Serology Laboratory, Applied and Developmental Directorate, Frederick National Laboratory, Frederick, MD, USA
| | - Kathleen D Liu
- Cardiovascular Research Institute, University of California, San Francisco, CA, USA
- Division of Nephrology, University of California, San Francisco, CA, USA
| | - Laura Esserman
- Department of Surgery, University of California, San Francisco, CA, USA
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA
- Department of Anesthesia, University of California, San Francisco, CA, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California, Room M-1083, 505 Parnassus Ave., San Francisco, CA, 94143, USA
- Department of Anesthesia, University of California, San Francisco, CA, USA
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19
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Torres LK, Siempos II. Identifying a hyperinflammatory subphenotype of ARDS associated with worse outcomes: may ferritin help? Thorax 2024; 79:200-201. [PMID: 38286617 PMCID: PMC10980828 DOI: 10.1136/thorax-2023-221131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/07/2024] [Indexed: 01/31/2024]
Affiliation(s)
- Lisa K Torres
- NewYork-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York, USA
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Ilias I Siempos
- First Department of Critical Care Medicine and Pulmonary Services, Evangelismos Hospital, National and Kapodistrian University of Athens Medical School, Athens, Greece
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20
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Wildi K, Colombo SM, McGuire D, Ainola C, Heinsar S, Sato N, Sato K, Liu K, Bouquet M, Wilson E, Passmore M, Hyslop K, Livingstone S, Di Feliciantonio M, Strugnell W, Palmieri C, Suen J, Li Bassi G, Fraser J. An appraisal of lung computer tomography in very early anti-inflammatory treatment of two different ovine ARDS phenotypes. Sci Rep 2024; 14:2162. [PMID: 38272980 PMCID: PMC10810785 DOI: 10.1038/s41598-024-52698-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 01/22/2024] [Indexed: 01/27/2024] Open
Abstract
Mortality and morbidity of Acute Respiratory Distress Syndrome (ARDS) are largely unaltered. A possible new approach to treatment of ARDS is offered by the discovery of inflammatory subphenotypes. In an ovine model of ARDS phenotypes, matching key features of the human subphenotypes, we provide an imaging characterization using computer tomography (CT). Nine animals were randomized into (a) OA (oleic acid, hypoinflammatory; n = 5) and (b) OA-LPS (oleic acid and lipopolysaccharides, hyperinflammatory; n = 4). 48 h after ARDS induction and anti-inflammatory treatment, CT scans were performed at high (H) and then low (L) airway pressure. After CT, the animals were euthanized and lung tissue was collected. OA-LPS showed a higher air fraction and OA a higher tissue fraction, resulting in more normally aerated lungs in OA-LPS in contrast to more non-aerated lung in OA. The change in lung and air volume between H and L was more accentuated in OA-LPS, indicating a higher recruitment potential. Strain was higher in OA, indicating a higher level of lung damage, while the amount of lung edema and histological lung injury were largely comparable. Anti-inflammatory treatment might be beneficial in terms of overall ventilated lung portion and recruitment potential, especially in the OA-LPS group.
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Affiliation(s)
- Karin Wildi
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia.
- The University of Queensland, Brisbane, Australia.
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland.
| | - Sebastiano Maria Colombo
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
- Department of Anaesthesia and Intensive Care Medicine, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Daniel McGuire
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
- The Prince Charles Hospital, Chermside, QLD, Australia
| | - Carmen Ainola
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Silver Heinsar
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
- Department of Intensive Care, North Estonia Medical Centre, Tallinn, Estonia
| | - Noriko Sato
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
| | - Kei Sato
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Keibun Liu
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
| | - Mahé Bouquet
- The University of Queensland, Brisbane, Australia
| | - Emily Wilson
- The University of Queensland, Brisbane, Australia
| | - Margaret Passmore
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Kieran Hyslop
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Samantha Livingstone
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Marianna Di Feliciantonio
- Department of Anaesthesia and Intensive Care Medicine, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Wendy Strugnell
- The University of Queensland, Brisbane, Australia
- The Prince Charles Hospital, Chermside, QLD, Australia
| | - Chiara Palmieri
- School of Veterinary Science, The University of Queensland, Gatton, Australia
| | - Jacky Suen
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
| | - Gianluigi Li Bassi
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia.
- The University of Queensland, Brisbane, Australia.
- St Andrews War Memorial Hospital, Intensive Care Unit, Spring Hill, QLD, Australia.
- The Wesley Hospital, Intensive Care Unit, Auchenflower, QLD, Australia.
| | - John Fraser
- Critical Care Research Group, The Prince Charles Hospital, Rode Road, Chermside, Brisbane, QLD, 4032, Australia
- The University of Queensland, Brisbane, Australia
- St Andrews War Memorial Hospital, Intensive Care Unit, Spring Hill, QLD, Australia
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21
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Yehya N, Zinter MS, Thompson JM, Lim MJ, Hanudel MR, Alkhouli MF, Wong H, Alder MN, McKeone DJ, Halstead ES, Sinha P, Sapru A. Identification of molecular subphenotypes in two cohorts of paediatric ARDS. Thorax 2024; 79:128-134. [PMID: 37813544 PMCID: PMC10850835 DOI: 10.1136/thorax-2023-220130] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023]
Abstract
BACKGROUND Two subphenotypes of acute respiratory distress syndrome (ARDS), hypoinflammatory and hyperinflammatory, have been reported in adults and in a single paediatric cohort. The relevance of these subphenotypes in paediatrics requires further investigation. We aimed to identify subphenotypes in two large observational cohorts of paediatric ARDS and assess their congruence with prior descriptions. METHODS We performed latent class analysis (LCA) separately on two cohorts using biomarkers as inputs. Subphenotypes were compared on clinical characteristics and outcomes. Finally, we assessed overlap with adult cohorts using parsimonious classifiers. FINDINGS In two cohorts from the Children's Hospital of Philadelphia (n=333) and from a multicentre study based at the University of California San Francisco (n=293), LCA identified two subphenotypes defined by differential elevation of biomarkers reflecting inflammation and endotheliopathy. In both cohorts, hyperinflammatory subjects had greater illness severity, more sepsis and higher mortality (41% and 28% in hyperinflammatory vs 11% and 7% in hypoinflammatory). Both cohorts demonstrated overlap with adult subphenotypes when assessed using parsimonious classifiers. INTERPRETATION We identified hypoinflammatory and hyperinflammatory subphenotypes of paediatric ARDS from two separate cohorts with utility for prognostic and potentially predictive, enrichment. Future paediatric ARDS trials should identify and leverage biomarker-defined subphenotypes in their analysis.
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Affiliation(s)
- Nadir Yehya
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA
| | - Matt S Zinter
- Department of Pediatrics, University of California San Francisco, San Francisco, California, USA
- Division of Allergy, Immunology, and Bone Marrow Transplantation, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Jill M Thompson
- Division of Pediatric Critical Care, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA
| | - Michelle J Lim
- Department of Pediatrics, UC Davis, Davis, California, USA
| | - Mark R Hanudel
- Department of Pediatrics, University of California Los Angeles, Los Angeles, California, USA
| | - Mustafa F Alkhouli
- Department of Pediatrics, University of California San Francisco, San Francisco, California, USA
| | - Hector Wong
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Matthew N Alder
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Daniel J McKeone
- Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - E Scott Halstead
- Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
| | - Pratik Sinha
- Division of Clinical and Translational Research, Washington University School of Medicine, St. Louis, MO, USA
- Division of Critical Care, Department of Anesthesia, Washington University, St. Louis, MO, USA
| | - Anil Sapru
- Department of Pediatrics, University of California Los Angeles, Los Angeles, California, USA
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22
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Dembinski R. [ARDS Diagnostics and Treatment after the Coronavirus Pandemic - Everything as it was?]. Anasthesiol Intensivmed Notfallmed Schmerzther 2024; 59:24-33. [PMID: 38190823 DOI: 10.1055/a-2043-8628] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
ARDS is a syndrome that can develop as a result of various underlying diseases. For a long time, the prevailing belief was that the course of the disease was comparable regardless of the underlying disease. However, even before the COVID-19 pandemic, it was suspected that there were different manifestations that could be treated more individually and thus reduce the high mortality rate of ARDS, which has remained unchanged for years. The various findings on the heterogeneity of the course of the disease in COVID-related ARDS appear to confirm these assumptions. It is therefore to be expected that the diagnosis and treatment of non-COVID-related ARDS will also have to be individualised according to such phenotypes in the future. However, as long as the effectiveness of such strategies has not been proven in clinical trials, the current recommendations for ARDS therapy will remain valid for the time being. However, the adjustments already formulated in this context to individual pathophysiological conditions with regard to respiratory mechanics, ventilation-perfusion distribution and possible cardiac dysfunction should be made more meticulously than has usually been the case to date.
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23
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Grunwell JR. So, You Say You Want a Revolution? You Tell Me That It's Evolution: Associating Temporal Changes in Pediatric Acute Respiratory Distress Syndrome Plasma Biomarkers With Lung Injury Severity. Pediatr Crit Care Med 2024; 25:80-83. [PMID: 38169340 PMCID: PMC10783528 DOI: 10.1097/pcc.0000000000003328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Affiliation(s)
- Jocelyn R Grunwell
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA
- Division of Pediatric Critical Care Medicine, Children's Healthcare of Atlanta, Atlanta, GA
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24
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Matthay MA, Arabi Y, Arroliga AC, Bernard G, Bersten AD, Brochard LJ, Calfee CS, Combes A, Daniel BM, Ferguson ND, Gong MN, Gotts JE, Herridge MS, Laffey JG, Liu KD, Machado FR, Martin TR, McAuley DF, Mercat A, Moss M, Mularski RA, Pesenti A, Qiu H, Ramakrishnan N, Ranieri VM, Riviello ED, Rubin E, Slutsky AS, Thompson BT, Twagirumugabe T, Ware LB, Wick KD. A New Global Definition of Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med 2024; 209:37-47. [PMID: 37487152 PMCID: PMC10870872 DOI: 10.1164/rccm.202303-0558ws] [Citation(s) in RCA: 94] [Impact Index Per Article: 94.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/24/2023] [Indexed: 07/26/2023] Open
Abstract
Background: Since publication of the 2012 Berlin definition of acute respiratory distress syndrome (ARDS), several developments have supported the need for an expansion of the definition, including the use of high-flow nasal oxygen, the expansion of the use of pulse oximetry in place of arterial blood gases, the use of ultrasound for chest imaging, and the need for applicability in resource-limited settings. Methods: A consensus conference of 32 critical care ARDS experts was convened, had six virtual meetings (June 2021 to March 2022), and subsequently obtained input from members of several critical care societies. The goal was to develop a definition that would 1) identify patients with the currently accepted conceptual framework for ARDS, 2) facilitate rapid ARDS diagnosis for clinical care and research, 3) be applicable in resource-limited settings, 4) be useful for testing specific therapies, and 5) be practical for communication to patients and caregivers. Results: The committee made four main recommendations: 1) include high-flow nasal oxygen with a minimum flow rate of ⩾30 L/min; 2) use PaO2:FiO2 ⩽ 300 mm Hg or oxygen saturation as measured by pulse oximetry SpO2:FiO2 ⩽ 315 (if oxygen saturation as measured by pulse oximetry is ⩽97%) to identify hypoxemia; 3) retain bilateral opacities for imaging criteria but add ultrasound as an imaging modality, especially in resource-limited areas; and 4) in resource-limited settings, do not require positive end-expiratory pressure, oxygen flow rate, or specific respiratory support devices. Conclusions: We propose a new global definition of ARDS that builds on the Berlin definition. The recommendations also identify areas for future research, including the need for prospective assessments of the feasibility, reliability, and prognostic validity of the proposed global definition.
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Affiliation(s)
- Michael A. Matthay
- Department of Medicine
- Department of Anesthesia
- Cardiovascular Research Institute, and
| | - Yaseen Arabi
- King Saud Bin Abdulaziz University for Health Sciences and King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
| | | | - Gordon Bernard
- Division of Allergy, Pulmonary, and Critical Care Medicine, Center for Lung Research, and
| | | | - Laurent J. Brochard
- Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Carolyn S. Calfee
- Department of Medicine
- Department of Anesthesia
- Cardiovascular Research Institute, and
| | - Alain Combes
- Médecine Intensive – Réanimation, Sorbonne Université, APHP Hôpital Pitié-Salpêtrière, Paris, France
| | - Brian M. Daniel
- Respiratory Therapy, University of California, San Francisco, San Francisco, California
| | - Niall D. Ferguson
- Interdepartmental Division of Critical Care Medicine and
- Department of Medicine, Toronto General Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Michelle N. Gong
- Department of Medicine, Montefiore Medical Center, Bronx, New York
| | - Jeffrey E. Gotts
- Kaiser Permanente San Francisco Medical Center, San Francisco, California
| | | | - John G. Laffey
- Anesthesia, University Hospital Galway, University of Galway, Galway, Ireland
| | | | - Flavia R. Machado
- Intensive Care Department, Hospital São Paulo, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Thomas R. Martin
- Department of Medicine, University of Washington, Seattle, Washington
| | - Danny F. McAuley
- Centre for Experimental Medicine, Queen’s University Belfast, Belfast, United Kingdom
| | - Alain Mercat
- Medical ICU, Angers University Hospital, Angers, France
| | - Marc Moss
- Department of Medicine, University of Colorado Denver, Aurora, Colorado
| | | | - Antonio Pesenti
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Haibo Qiu
- Critical Care Medicine, Zhongda Hospital, Nanjing, China
| | | | - V. Marco Ranieri
- Emergency and Intensive Care Medicine, Alma Mater Studorium University of Bologna, Bologna, Italy
| | - Elisabeth D. Riviello
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Arthur S. Slutsky
- Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Theogene Twagirumugabe
- Department of Anesthesia, Critical Care, and Emergency Medicine, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda; and
| | - Lorraine B. Ware
- Department of Medicine, Vanderbilt University, Nashville, Tennessee
| | - Katherine D. Wick
- Department of Medicine, University of California, Davis, Davis, California
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25
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Blot PL, Chousterman BG, Santafè M, Cartailler J, Pacheco A, Magret M, Masclans JR, Artigas A, Roca O, García-de-Acilu M. Subphenotypes in patients with acute respiratory distress syndrome treated with high-flow oxygen. Crit Care 2023; 27:419. [PMID: 37915062 PMCID: PMC10619276 DOI: 10.1186/s13054-023-04687-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 10/14/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS) subphenotypes differ in outcomes and treatment responses. Subphenotypes in high-flow nasal oxygen (HFNO)-treated ARDS patients have not been investigated. OBJECTIVES To identify biological subphenotypes in HFNO-treated ARDS patients. METHODS Secondary analysis of a prospective multicenter observational study including ARDS patients supported with HFNO. Plasma inflammation markers (interleukin [IL]-6, IL-8, and IL-33 and soluble suppression of tumorigenicity-2 [sST2]) and lung epithelial (receptor for advanced glycation end products [RAGE] and surfactant protein D [SP-D]) and endothelial (angiopoietin-2 [Ang-2]) injury were measured. These biomarkers and bicarbonate were used in K-means cluster analysis to identify subphenotypes. Logistic regression was performed on biomarker combinations to predict clustering. We chose the model with the best AUROC and the lowest number of variables. This model was used to describe the HAIS (High-flow ARDS Inflammatory Subphenotype) score. RESULTS Among 41 HFNO patients, two subphenotypes were identified. Hyperinflammatory subphenotype (n = 17) showed higher biomarker levels than hypoinflammatory (n = 24). Despite similar baseline characteristics, the hyperinflammatory subphenotype had higher 60-day mortality (47 vs 8.3% p = 0.014) and longer ICU length of stay (22.0 days [18.0-30.0] vs 39.5 [25.5-60.0], p = 0.034). The HAIS score, based on IL-8 and sST2, accurately distinguished subphenotypes (AUROC 0.96 [95%CI: 0.90-1.00]). A HAIS score ≥ 7.45 was predictor of hyperinflammatory subphenotype. CONCLUSION ARDS patients treated with HFNO exhibit two biological subphenotypes that have similar clinical characteristics, but hyperinflammatory patients have worse outcomes. The HAIS score may identify patients with hyperinflammatory subphenotype and might be used for enrichment strategies in future clinical trials.
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Affiliation(s)
- Pierre-Louis Blot
- Département d'anesthésie-Réanimation, Hôpital Lariboisière, Paris, France
- INSERM UMRS-942 MASCOT, Hôpital Lariboisière, Paris, France
| | - Benjamin G Chousterman
- Département d'anesthésie-Réanimation, Hôpital Lariboisière, Paris, France
- INSERM UMRS-942 MASCOT, Hôpital Lariboisière, Paris, France
| | - Manel Santafè
- Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Part Taulí (I3PT-CERCA), Parc del Taulí 1, 08028, Sabadell, Spain
| | | | - Andrés Pacheco
- Servei de Medicina Intensiva, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Mònica Magret
- Servei de Medicina Intensiva, Hospital Universitari Joan XXIII, Tarragona, Spain
| | - Joan R Masclans
- Critical Care Department, Hospital del Mar-Parc de Salut MAR. GREPAC-Group Recerca Departamento de Medicina y Ciencias de la Vida Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Director de Docencia PSMAR, Intensive Care Unit Hospital del Mar. Professor of Medicine Universitat Pompeu Fabra (UPF) IMIM (GREPAC - Group Recerca Patologia Critica) Departamento de Medicina Y Ciencias de la Vida (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
| | - Antoni Artigas
- Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Part Taulí (I3PT-CERCA), Parc del Taulí 1, 08028, Sabadell, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
- CIBER de Enfermedades Respiratorias, Insituto de Salud Carlos III, Madrid, Spain
| | - Oriol Roca
- Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Part Taulí (I3PT-CERCA), Parc del Taulí 1, 08028, Sabadell, Spain.
- Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain.
| | - Marina García-de-Acilu
- Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Part Taulí (I3PT-CERCA), Parc del Taulí 1, 08028, Sabadell, Spain
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Sinha P, Kerchberger VE, Willmore A, Chambers J, Zhuo H, Abbott J, Jones C, Wickersham N, Wu N, Neyton L, Langelier CR, Mick E, He J, Jauregui A, Churpek MM, Gomez AD, Hendrickson CM, Kangelaris KN, Sarma A, Leligdowicz A, Delucchi KL, Liu KD, Russell JA, Matthay MA, Walley KR, Ware LB, Calfee CS. Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials. THE LANCET. RESPIRATORY MEDICINE 2023; 11:965-974. [PMID: 37633303 PMCID: PMC10841178 DOI: 10.1016/s2213-2600(23)00237-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/17/2023] [Accepted: 06/20/2023] [Indexed: 08/28/2023]
Abstract
BACKGROUND In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials. METHODS We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect. FINDINGS A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72). INTERPRETATION Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis. FUNDING US National Institutes of Health.
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Affiliation(s)
- Pratik Sinha
- Division of Clinical and Translational Research, Division of Critical Care, Department of Anesthesiology, Washington University School of Medicine, Saint Louis, MO, USA.
| | - V Eric Kerchberger
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Julia Chambers
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Hanjing Zhuo
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Jason Abbott
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Chayse Jones
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Nancy Wickersham
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nelson Wu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lucile Neyton
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Charles R Langelier
- Division of Infectious Diseases, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Eran Mick
- Division of Infectious Diseases, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - June He
- Division of Clinical and Translational Research, Division of Critical Care, Department of Anesthesiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Alejandra Jauregui
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Matthew M Churpek
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Antonio D Gomez
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | | | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Aleksandra Leligdowicz
- Department of Medicine, Division of Critical Care Medicine, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Kevin L Delucchi
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Kathleen D Liu
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Division of Nephrology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - James A Russell
- Division of Critical Care Medicine, St Paul's Hospital, University of British Columbia, Vancouver, BC, Canada; Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
| | - Keith R Walley
- Division of Critical Care Medicine, St Paul's Hospital, University of British Columbia, Vancouver, BC, Canada; Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Lorraine B Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California San Francisco, San Francisco, CA, USA
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Xia F, Chen H, Liu Y, Huang L, Meng S, Xu J, Xie J, Wang G, Guo F. Development of genomic phenotype and immunophenotype of acute respiratory distress syndrome using autophagy and metabolism-related genes. Front Immunol 2023; 14:1209959. [PMID: 37936685 PMCID: PMC10626539 DOI: 10.3389/fimmu.2023.1209959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 10/09/2023] [Indexed: 11/09/2023] Open
Abstract
Background Distinguishing ARDS phenotypes is of great importance for its precise treatment. In the study, we attempted to ascertain its phenotypes based on metabolic and autophagy-related genes and infiltrated immune cells. Methods Transcription datasets of ARDS patients were obtained from Gene expression omnibus (GEO), autophagy and metabolic-related genes were from the Human Autophagy Database and the GeneCards Database, respectively. Autophagy and metabolism-related differentially expressed genes (AMRDEGs) were further identified by machine learning and processed for constructing the nomogram and the risk prediction model. Functional enrichment analyses of differentially expressed genes were performed between high- and low-risk groups. According to the protein-protein interaction network, these hub genes closely linked to increased risk of ARDS were identified with CytoHubba. ssGSEA and CIBERSORT was applied to analyze the infiltration pattern of immune cells in ARDS. Afterwards, immunologically characterized and molecular phenotypes were constructed according to infiltrated immune cells and hub genes. Results A total of 26 AMRDEGs were obtained, and CTSB and EEF2 were identified as crucial AMRDEGs. The predictive capability of the risk score, calculated based on the expression levels of CTSB and EEF2, was robust for ARDS in both the discovery cohort (AUC = 1) and the validation cohort (AUC = 0.826). The mean risk score was determined to be 2.231332, and based on this score, patients were classified into high-risk and low-risk groups. 371 differential genes in high- and low-risk groups were analyzed. ITGAM, TYROBP, ITGB2, SPI1, PLEK, FGR, MPO, S100A12, HCK, and MYC were identified as hub genes. A total of 12 infiltrated immune cells were differentially expressed and have correlations with hub genes. According to hub genes and implanted immune cells, ARDS patients were divided into two different molecular phenotypes (Group 1: n = 38; Group 2: n = 19) and two immune phenotypes (Cluster1: n = 22; Cluster2: n = 35), respectively. Conclusion This study picked up hub genes of ARDS related to autophagy and metabolism and clustered ARDS patients into different molecular phenotypes and immunophenotypes, providing insights into the precision medicine of treating patients with ARDS.
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Affiliation(s)
- Feiping Xia
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hui Chen
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
- Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, Soochow University, Suzhou, China
| | - Yigao Liu
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Lili Huang
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Shanshan Meng
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jingyuan Xu
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jianfeng Xie
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Guozheng Wang
- Department of Clinical Infection Microbiology and Immunology, University of Liverpool, Liverpool, United Kingdom
| | - Fengmei Guo
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
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Sanchez-Pinto LN, Bennett TD, Stroup EK, Luo Y, Atreya M, Bubeck Wardenburg J, Chong G, Geva A, Faustino EVS, Farris RW, Hall MW, Rogerson C, Shah SS, Weiss SL, Khemani RG. Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock. Pediatr Crit Care Med 2023; 24:795-806. [PMID: 37272946 PMCID: PMC10540758 DOI: 10.1097/pcc.0000000000003292] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
OBJECTIVES Untangling the heterogeneity of sepsis in children and identifying clinically relevant phenotypes could lead to the development of targeted therapies. Our aim was to analyze the organ dysfunction trajectories of children with sepsis-associated multiple organ dysfunction syndrome (MODS) to identify reproducible and clinically relevant sepsis phenotypes and determine if they are associated with heterogeneity of treatment effect (HTE) to common therapies. DESIGN Multicenter observational cohort study. SETTING Thirteen PICUs in the United States. PATIENTS Patients admitted with suspected infections to the PICU between 2012 and 2018. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We used subgraph-augmented nonnegative matrix factorization to identify candidate trajectory-based phenotypes based on the type, severity, and progression of organ dysfunction in the first 72 hours. We analyzed the candidate phenotypes to determine reproducibility as well as prognostic, therapeutic, and biological relevance. Overall, 38,732 children had suspected infection, of which 15,246 (39.4%) had sepsis-associated MODS with an in-hospital mortality of 10.1%. We identified an organ dysfunction trajectory-based phenotype (which we termed persistent hypoxemia, encephalopathy, and shock) that was highly reproducible, had features of systemic inflammation and coagulopathy, and was independently associated with higher mortality. In a propensity score-matched analysis, patients with persistent hypoxemia, encephalopathy, and shock phenotype appeared to have HTE and benefit from adjuvant therapy with hydrocortisone and albumin. When compared with other high-risk clinical syndromes, the persistent hypoxemia, encephalopathy, and shock phenotype only overlapped with 50%-60% of patients with septic shock, moderate-to-severe pediatric acute respiratory distress syndrome, or those in the top tier of organ dysfunction burden, suggesting that it represents a nonsynonymous clinical phenotype of sepsis-associated MODS. CONCLUSIONS We derived and validated the persistent hypoxemia, encephalopathy, and shock phenotype, which is highly reproducible, clinically relevant, and associated with HTE to common adjuvant therapies in children with sepsis.
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Affiliation(s)
- L Nelson Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Tellen D Bennett
- Departments of Biomedical Informatics and Pediatrics, University of Colorado School of Medicine, Aurora, CO
| | - Emily K Stroup
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Mihir Atreya
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | | | - Grace Chong
- Department of Pediatrics, University of Chicago Pritzker School of Medicine, Chicago, IL
| | - Alon Geva
- Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children's Hospital, Boston, MA
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA
- Department of Anaesthesia, Harvard Medical School, Boston, MA
| | | | - Reid W Farris
- Department of Pediatrics, University of Washington and Seattle Children's Hospital, Seattle, WA
| | - Mark W Hall
- Department of Pediatrics, The Ohio State University and Nationwide Children's Hospital, Columbus, OH
| | - Colin Rogerson
- Department of Pediatrics, Indiana University School of Medicine, Riley Hospital for Children, Indianapolis, IN
| | - Sareen S Shah
- Department of Pediatrics, Cohen Children's Medical Center, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY
| | - Scott L Weiss
- Department of Anesthesiology and Critical Care, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Robinder G Khemani
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Los Angeles, Los Angeles, CA
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29
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Sanchez-Pinto LN, Bhavani SV, Atreya MR, Sinha P. Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care. Crit Care Clin 2023; 39:627-646. [PMID: 37704331 DOI: 10.1016/j.ccc.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
Precision medicine aims to identify treatments that are most likely to result in favorable outcomes for subgroups of patients with similar clinical and biological characteristics. The gaps for the development and implementation of precision medicine strategies in the critical care setting are many, but the advent of data science and multi-omics approaches, combined with the rich data ecosystem in the intensive care unit, offer unprecedented opportunities to realize the promise of precision critical care. In this article, the authors review the data-driven and technology-based approaches being leveraged to discover and implement precision medicine strategies in the critical care setting.
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Affiliation(s)
- Lazaro N Sanchez-Pinto
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
| | | | - Mihir R Atreya
- Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Avenue, Cincinnati, OH 45229, USA
| | - Pratik Sinha
- Division of Clinical and Translational Research, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA; Division of Critical Care, Department of Anesthesia, Washington University School of Medicine, 1 Barnes Jewish Hospital Plaza, St. Louis, MO 63110, USA
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30
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Ishaque S, Famularo ST, Saleem AF, Siddiqui NUR, Kazi Z, Parkar S, Hotwani A, Thomas NJ, Thompson JM, Lahni P, Varisco B, Yehya N. Biomarker-Based Risk Stratification in Pediatric Sepsis From a Low-Middle Income Country. Pediatr Crit Care Med 2023; 24:563-573. [PMID: 37092821 PMCID: PMC10317305 DOI: 10.1097/pcc.0000000000003244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
OBJECTIVES Most biomarker studies of sepsis originate from high-income countries, whereas mortality risk is higher in low- and middle-income countries. The second version of the Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) has been validated in multiple North American PICUs for prognosis. Given differences in epidemiology, we assessed the performance of PERSEVERE-II in septic children from Pakistan, a low-middle income country. Due to uncertainty regarding how well PERSEVERE-II would perform, we also assessed the utility of other select biomarkers reflecting endotheliopathy, coagulopathy, and lung injury. DESIGN Prospective cohort study. SETTING PICU in Aga Khan University Hospital in Karachi, Pakistan. PATIENTS Children (< 18 yr old) meeting pediatric modifications of adult Sepsis-3 criteria between November 2020 and February 2022 were eligible. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Plasma was collected within 24 hours of admission and biomarkers quantified. The area under the receiver operating characteristic curve for PERSEVERE-II to discriminate 28-day mortality was determined. Additional biomarkers were compared between survivors and nonsurvivors and between subjects with and without acute respiratory distress syndrome. In 86 subjects (20 nonsurvivors, 23%), PERSEVERE-II discriminated mortality (area under the receiver operating characteristic curve, 0.83; 95% CI, 0.72-0.94) and stratified the cohort into low-, medium-, and high-risk of mortality. Biomarkers reflecting endotheliopathy (angiopoietin 2, intracellular adhesion molecule 1) increased across worsening risk strata. Angiopoietin 2, soluble thrombomodulin, and plasminogen activator inhibitor 1 were higher in nonsurvivors, and soluble receptor for advanced glycation end-products and surfactant protein D were higher in children meeting acute respiratory distress syndrome criteria. CONCLUSIONS PERSEVERE-II performs well in septic children from Aga Khan University Hospital, representing the first validation of PERSEVERE-II in a low-middle income country. Patients possessed a biomarker profile comparable to that of sepsis from high-income countries, suggesting that biomarker-based enrichment strategies may be effective in this setting.
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Affiliation(s)
- Sidra Ishaque
- Department of Pediatrics and Child Health, The Aga Khan University Hospital, Karachi, Pakistan
| | - Stephen Thomas Famularo
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care, University of Pennsylvania and Children's Hospital of Philadelphia, Philadelphia, PA
| | - Ali Faisal Saleem
- Department of Pediatrics and Child Health, The Aga Khan University Hospital, Karachi, Pakistan
| | | | - Zaubina Kazi
- Department of Pediatrics and Child Health, The Aga Khan University Hospital, Karachi, Pakistan
| | - Sadia Parkar
- Department of Pediatrics and Child Health, The Aga Khan University Hospital, Karachi, Pakistan
| | - Aneeta Hotwani
- Department of Pediatrics and Child Health, The Aga Khan University Hospital, Karachi, Pakistan
| | - Neal J Thomas
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Penn State University College of Medicine, Hershey, PA
| | - Jill Marie Thompson
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care, University of Pennsylvania and Children's Hospital of Philadelphia, Philadelphia, PA
| | - Patrick Lahni
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Brian Varisco
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
- University of Cincinnati College of Medicine, Cincinnati, OH
| | - Nadir Yehya
- Division of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care, University of Pennsylvania and Children's Hospital of Philadelphia, Philadelphia, PA
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Grasselli G, Calfee CS, Camporota L, Poole D, Amato MBP, Antonelli M, Arabi YM, Baroncelli F, Beitler JR, Bellani G, Bellingan G, Blackwood B, Bos LDJ, Brochard L, Brodie D, Burns KEA, Combes A, D'Arrigo S, De Backer D, Demoule A, Einav S, Fan E, Ferguson ND, Frat JP, Gattinoni L, Guérin C, Herridge MS, Hodgson C, Hough CL, Jaber S, Juffermans NP, Karagiannidis C, Kesecioglu J, Kwizera A, Laffey JG, Mancebo J, Matthay MA, McAuley DF, Mercat A, Meyer NJ, Moss M, Munshi L, Myatra SN, Ng Gong M, Papazian L, Patel BK, Pellegrini M, Perner A, Pesenti A, Piquilloud L, Qiu H, Ranieri MV, Riviello E, Slutsky AS, Stapleton RD, Summers C, Thompson TB, Valente Barbas CS, Villar J, Ware LB, Weiss B, Zampieri FG, Azoulay E, Cecconi M. ESICM guidelines on acute respiratory distress syndrome: definition, phenotyping and respiratory support strategies. Intensive Care Med 2023; 49:727-759. [PMID: 37326646 PMCID: PMC10354163 DOI: 10.1007/s00134-023-07050-7] [Citation(s) in RCA: 172] [Impact Index Per Article: 172.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/24/2023] [Indexed: 06/17/2023]
Abstract
The aim of these guidelines is to update the 2017 clinical practice guideline (CPG) of the European Society of Intensive Care Medicine (ESICM). The scope of this CPG is limited to adult patients and to non-pharmacological respiratory support strategies across different aspects of acute respiratory distress syndrome (ARDS), including ARDS due to coronavirus disease 2019 (COVID-19). These guidelines were formulated by an international panel of clinical experts, one methodologist and patients' representatives on behalf of the ESICM. The review was conducted in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement recommendations. We followed the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence and grade recommendations and the quality of reporting of each study based on the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) network guidelines. The CPG addressed 21 questions and formulates 21 recommendations on the following domains: (1) definition; (2) phenotyping, and respiratory support strategies including (3) high-flow nasal cannula oxygen (HFNO); (4) non-invasive ventilation (NIV); (5) tidal volume setting; (6) positive end-expiratory pressure (PEEP) and recruitment maneuvers (RM); (7) prone positioning; (8) neuromuscular blockade, and (9) extracorporeal life support (ECLS). In addition, the CPG includes expert opinion on clinical practice and identifies the areas of future research.
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Affiliation(s)
- Giacomo Grasselli
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Luigi Camporota
- Department of Adult Critical Care, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Centre for Human and Applied Physiological Sciences, King's College London, London, UK
| | - Daniele Poole
- Operative Unit of Anesthesia and Intensive Care, S. Martino Hospital, Belluno, Italy
| | | | - Massimo Antonelli
- Department of Anesthesiology Intensive Care and Emergency Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
- Università Cattolica del Sacro Cuore, Rome, Italy
| | - Yaseen M Arabi
- Intensive Care Department, Ministry of the National Guard - Health Affairs, Riyadh, Kingdom of Saudi Arabia
- King Saud bin Abdulaziz University for Health Sciences, Riyadh, Kingdom of Saudi Arabia
- King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Francesca Baroncelli
- Department of Anesthesia and Intensive Care, San Giovanni Bosco Hospital, Torino, Italy
| | - Jeremy R Beitler
- Center for Acute Respiratory Failure and Division of Pulmonary, Allergy and Critical Care Medicine, Columbia University, New York, NY, USA
| | - Giacomo Bellani
- Centre for Medical Sciences - CISMed, University of Trento, Trento, Italy
- Department of Anesthesia and Intensive Care, Santa Chiara Hospital, APSS Trento, Trento, Italy
| | - Geoff Bellingan
- Intensive Care Medicine, University College London, NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Bronagh Blackwood
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
| | - Lieuwe D J Bos
- Intensive Care, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laurent Brochard
- Keenan Research Center, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
| | - Daniel Brodie
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Karen E A Burns
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
- Department of Medicine, Division of Critical Care, Unity Health Toronto - Saint Michael's Hospital, Toronto, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Alain Combes
- Sorbonne Université, INSERM, UMRS_1166-ICAN, Institute of Cardiometabolism and Nutrition, F-75013, Paris, France
- Service de Médecine Intensive-Réanimation, Institut de Cardiologie, APHP Sorbonne Université Hôpital Pitié-Salpêtrière, F-75013, Paris, France
| | - Sonia D'Arrigo
- Department of Anesthesiology Intensive Care and Emergency Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Daniel De Backer
- Department of Intensive Care, CHIREC Hospitals, Université Libre de Bruxelles, Brussels, Belgium
| | - Alexandre Demoule
- Sorbonne Université, INSERM, UMRS1158 Neurophysiologie Respiratoire Expérimentale et Clinique, Paris, France
- AP-HP, Groupe Hospitalier Universitaire APHP-Sorbonne Université, site Pitié-Salpêtrière, Service de Médecine Intensive - Réanimation (Département R3S), Paris, France
| | - Sharon Einav
- Shaare Zedek Medical Center and Hebrew University Faculty of Medicine, Jerusalem, Israel
| | - Eddy Fan
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
| | - Niall D Ferguson
- Department of Medicine, Division of Respirology and Critical Care, Toronto General Hospital Research Institute, University Health Network, Toronto, Canada
- Departments of Medicine and Physiology, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Jean-Pierre Frat
- CHU De Poitiers, Médecine Intensive Réanimation, Poitiers, France
- INSERM, CIC-1402, IS-ALIVE, Université de Poitiers, Faculté de Médecine et de Pharmacie, Poitiers, France
| | - Luciano Gattinoni
- Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany
| | - Claude Guérin
- University of Lyon, Lyon, France
- Institut Mondor de Recherches Biomédicales, INSERM 955 CNRS 7200, Créteil, France
| | - Margaret S Herridge
- Critical Care and Respiratory Medicine, University Health Network, Toronto General Research Institute, Institute of Medical Sciences, Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
| | - Carol Hodgson
- The Australian and New Zealand Intensive Care Research Center, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Department of Intensive Care, Alfred Health, Melbourne, Australia
| | - Catherine L Hough
- Division of Pulmonary, Allergy and Critical Care Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Samir Jaber
- Anesthesia and Critical Care Department (DAR-B), Saint Eloi Teaching Hospital, University of Montpellier, Research Unit: PhyMedExp, INSERM U-1046, CNRS, 34295, Montpellier, France
| | - Nicole P Juffermans
- Laboratory of Translational Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Christian Karagiannidis
- Department of Pneumology and Critical Care Medicine, Cologne-Merheim Hospital, ARDS and ECMO Centre, Kliniken Der Stadt Köln gGmbH, Witten/Herdecke University Hospital, Cologne, Germany
| | - Jozef Kesecioglu
- Department of Intensive Care Medicine, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Arthur Kwizera
- Makerere University College of Health Sciences, School of Medicine, Department of Anesthesia and Intensive Care, Kampala, Uganda
| | - John G Laffey
- Anesthesia and Intensive Care Medicine, School of Medicine, College of Medicine Nursing and Health Sciences, University of Galway, Galway, Ireland
- Anesthesia and Intensive Care Medicine, Galway University Hospitals, Saolta University Hospitals Groups, Galway, Ireland
| | - Jordi Mancebo
- Intensive Care Department, Hospital Universitari de La Santa Creu I Sant Pau, Barcelona, Spain
| | - Michael A Matthay
- Departments of Medicine and Anesthesia, Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Daniel F McAuley
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
- Regional Intensive Care Unit, Royal Victoria Hospital, Belfast Health and Social Care Trust, Belfast, UK
| | - Alain Mercat
- Département de Médecine Intensive Réanimation, CHU d'Angers, Université d'Angers, Angers, France
| | - Nuala J Meyer
- University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Marc Moss
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado, School of Medicine, Aurora, CO, USA
| | - Laveena Munshi
- Interdepartmental Division of Critical Care Medicine, Sinai Health System, University of Toronto, Toronto, Canada
| | - Sheila N Myatra
- Department of Anesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Michelle Ng Gong
- Division of Pulmonary and Critical Care Medicine, Montefiore Medical Center, Bronx, New York, NY, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, NY, USA
| | - Laurent Papazian
- Bastia General Hospital Intensive Care Unit, Bastia, France
- Aix-Marseille University, Faculté de Médecine, Marseille, France
| | - Bhakti K Patel
- Section of Pulmonary and Critical Care, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Mariangela Pellegrini
- Anesthesia and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Anders Perner
- Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Antonio Pesenti
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Lise Piquilloud
- Adult Intensive Care Unit, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Haibo Qiu
- Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Marco V Ranieri
- Alma Mater Studiorum - Università di Bologna, Bologna, Italy
- Anesthesia and Intensive Care Medicine, IRCCS Policlinico di Sant'Orsola, Bologna, Italy
| | - Elisabeth Riviello
- Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Arthur S Slutsky
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada
| | - Renee D Stapleton
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Charlotte Summers
- Department of Medicine, University of Cambridge Medical School, Cambridge, UK
| | - Taylor B Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Carmen S Valente Barbas
- University of São Paulo Medical School, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Jesús Villar
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario Dr. Negrin, Las Palmas de Gran Canaria, Spain
| | - Lorraine B Ware
- Departments of Medicine and Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Björn Weiss
- Department of Anesthesiology and Intensive Care Medicine (CCM CVK), Charitè - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Fernando G Zampieri
- Academic Research Organization, Albert Einstein Hospital, São Paulo, Brazil
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada
| | - Elie Azoulay
- Médecine Intensive et Réanimation, APHP, Hôpital Saint-Louis, Paris Cité University, Paris, France
| | - Maurizio Cecconi
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
- Department of Anesthesia and Intensive Care Medicine, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
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Zhou W, He MM, Wang F, Xu RH, Wang F, Zhao Q. Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer. NPJ Precis Oncol 2023; 7:60. [PMID: 37353681 DOI: 10.1038/s41698-023-00412-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 06/05/2023] [Indexed: 06/25/2023] Open
Abstract
The molecular subtypes of colorectal cancer (CRC) represent a comprehensive dissection of CRC heterogeneity. However, molecular feature-based classification systems have limitations in accurately prognosticating stratification due to the inability to distinguish cancer-specific deaths. This study aims to establish a classification system that bridges clinical characteristics, cause-specific deaths, and molecular features. We adopted latent class analysis (LCA) on 491,107 first primary CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database to reveal hidden profiles of CRC. The LCA-derived classification scheme was further applied to The Cancer Genome Atlas (TCGA) to assess its effectiveness in improving the accurate stratification of molecular-based subtypes of CRC. Four classes were identified based on latent class analysis integrating demographic and clinicopathological information of CRC patients. The LCA-derived Class 1 (LCAC1) and the LCAC2 showed a high risk of dying from non-CRC, while patients in LCAC3 had a risk of dying from CRC 1.41 times that of LCAC1 (95% confidence interval [CI] = 1.39-1.43). LCAC4 had the lowest probability to die from non-CRC (hazard ratio [HR] = 0.22, 95% CI = 0.21-0.24) compared with LCAC1. Since the LCA-derived classification can identify patients susceptible to CRC-specific death, adjusting for this classification allows molecular-based subtypes to achieve more accurate survival stratification. We provided a classification system capable of distinguish CRC-specific death, which will improve the accuracy of consensus molecular subtypes for CRC patients' survival stratification. Further studies are warranted to confirm the molecular features of LCA-derived classification to inform potential therapeutic strategies and treatment recommendations.
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Affiliation(s)
- Wen Zhou
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China
- Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese Academy of Medical Sciences, 510060, Guangzhou, P. R. China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Sun Yat-sen University, 510060, Guangzhou, P. R. China
| | - Ming-Ming He
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Sun Yat-sen University, 510060, Guangzhou, P. R. China
| | - Feng Wang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Sun Yat-sen University, 510060, Guangzhou, P. R. China
| | - Rui-Hua Xu
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Sun Yat-sen University, 510060, Guangzhou, P. R. China
| | - Fang Wang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China.
- Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese Academy of Medical Sciences, 510060, Guangzhou, P. R. China.
| | - Qi Zhao
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, 510060, Guangzhou, P. R. China.
- Department of Molecular Diagnostics, Sun Yat-sen University Cancer Center, Sun Yat-sen University, 510060, Guangzhou, P. R. China.
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Tenda ED, Henrina J, Samosir J, Amalia R, Yulianti M, Pitoyo CW, Setiati S. Machine learning-based COVID-19 acute respiratory distress syndrome phenotyping and clinical outcomes: A systematic review. Heliyon 2023; 9:e17276. [PMID: 37366530 PMCID: PMC10275654 DOI: 10.1016/j.heliyon.2023.e17276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 06/02/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023] Open
Abstract
COVID-19-related acute respiratory distress syndrome (CARDS) has been suggested to differ from the typical ARDS. While distinct phenotypes of ARDS have been identified through latent class analysis (LCA), it is unclear whether such phenotypes exist for CARDS and how they affect clinical outcomes. To address this question, we conducted a systematic review of the current evidence.We searched several, including PubMed, EBSCO Host, and Web of Science, from inception to July 1, 2022. Our exposure and outcome of interest were different CARDS phenotypes identified and their associated outcomes, such as 28-day, 90-day, 180-day mortality, ventilator-free days, and other relevant outcomes.We identified four studies comprising a total of 1776 CARDS patients.Of the four studies, three used LCA to identify subphenotypes (SPs) of CARDS. One study based on longitudinal data identified two SPs, with SP2 associated with worse ventilation and mechanical parameters than SP1. The other two studies based on baseline data also identified two SPs, with SP2 and SP1 were associated with hyperinflammatory and hypoinflammatory CARDS, respectively. The fourth study identified three SPs primarily stratified by comorbidities using multifactorial analysis.All studies identified a subphenotype associated with poorer outcomes, including mortality, ventilator-free days, multiple-organ injury, and pulmonary embolism. Two studies reported differential responses to corticosteroids among the SPs, with improved mortality in the hyperinflammatory and worse in the hypoinflammatory SPs.Overall, our review highlights the importance of phenotyping in understanding CARDS and its impact on disease management and prognostication. However, a consensus approach to phenotyping is necessary to ensure consistency and comparability across studies. We recommend that randomized clinical trials stratified by phenotype should only be initiated after such consensus is reached. Short title COVID-19 ARDS subphenotypes and outcomes.
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Affiliation(s)
- Eric Daniel Tenda
- Division of Respirology and Critical Care, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Joshua Henrina
- Division of Respirology and Critical Care, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Jistrani Samosir
- Department of Internal Medicine, Dr.T.C. Hillers General Public Hospital, East Nusa Tenggara, Kabupaten Sikka, Indonesia
| | - Ridha Amalia
- University of Indonesia Hospital, Depok, Indonesia
| | - Mira Yulianti
- Division of Respirology and Critical Care, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Ceva Wicaksono Pitoyo
- Division of Respirology and Critical Care, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Siti Setiati
- Division of Geriatric Medicine, Department of Internal Medicine, Faculty of Medicine Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
- Clinical Epidemiology and Evidence-Based Medicine Unit, Faculty of Medicine, Cipto Mangunkusumo Hospital, Universitas Indonesia, Jakarta, Indonesia
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Chotalia M, Patel JM, Bangash MN, Parekh D. Cardiovascular Subphenotypes in ARDS: Diagnostic and Therapeutic Implications and Overlap with Other ARDS Subphenotypes. J Clin Med 2023; 12:jcm12113695. [PMID: 37297890 DOI: 10.3390/jcm12113695] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 04/27/2023] [Accepted: 05/15/2023] [Indexed: 06/12/2023] Open
Abstract
Acute respiratory distress syndrome (ARDS) is a highly heterogeneous clinical condition. Shock is a poor prognostic sign in ARDS, and heterogeneity in its pathophysiology may be a barrier to its effective treatment. Although right ventricular dysfunction is commonly implicated, there is no consensus definition for its diagnosis, and left ventricular function is neglected. There is a need to identify the homogenous subgroups within ARDS, that have a similar pathobiology, which can then be treated with targeted therapies. Haemodynamic clustering analyses in patients with ARDS have identified two subphenotypes of increasingly severe right ventricular injury, and a further subphenotype of hyperdynamic left ventricular function. In this review, we discuss how phenotyping the cardiovascular system in ARDS may align with haemodynamic pathophysiology, can aid in optimally defining right ventricular dysfunction and can identify tailored therapeutic targets for shock in ARDS. Additionally, clustering analyses of inflammatory, clinical and radiographic data describe other subphenotypes in ARDS. We detail the potential overlap between these and the cardiovascular phenotypes.
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Affiliation(s)
- Minesh Chotalia
- Birmingham Acute Care Research Group, University of Birmingham, Birmingham B15 2SQ, UK
- Department of Anaesthetics and Critical Care, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
| | - Jaimin M Patel
- Birmingham Acute Care Research Group, University of Birmingham, Birmingham B15 2SQ, UK
- Department of Anaesthetics and Critical Care, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
| | - Mansoor N Bangash
- Birmingham Acute Care Research Group, University of Birmingham, Birmingham B15 2SQ, UK
- Department of Anaesthetics and Critical Care, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
| | - Dhruv Parekh
- Birmingham Acute Care Research Group, University of Birmingham, Birmingham B15 2SQ, UK
- Department of Anaesthetics and Critical Care, Queen Elizabeth Hospital Birmingham, Birmingham B15 2GW, UK
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Brister D, Wahab M, Rashad M, Diab N, Kolb M, Satia I. Emerging drugs in the treatment of chronic cough. Expert Opin Emerg Drugs 2023:1-11. [PMID: 37060576 DOI: 10.1080/14728214.2023.2203912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2023]
Abstract
INTRODUCTION Chronic cough is a debilitating condition that is among the most common reasons for seeking medical attention yet remains challenging to manage. Identifying an underlying respiratory, nasal or upper gastrointestinal disease triggering cough is the first step in assessment, but once this has been ruled out or adequately treated, many patients remain troubled with chronic cough. AREAS COVERED This narrative review discusses the role of existing treatments and describes the current research landscape for the development of new therapies for chronic cough greater than 8 weeks that is refractory (RCC) or unexplained (UCC). The literature search includes published studies found on pubmed and conference abstracts until 2023. EXPERT OPINION RCC/UCC can occur due to neuronal dysregulation of the vagus nerve or central nervous system. Hence, novel anti-tussives have targeted ion channels involved in the neuronal signaling which triggers cough. Although some therapies targeting receptors such as TRPV1 have failed to show efficacy, P2X3 antagonists have emerged as the most promising therapy for patients impacted by chronic cough. Disease specific therapies such as for idiopathic pulmonary fibrosis are in early development.
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Affiliation(s)
- Danica Brister
- McMaster University Department of Medicine, Hamilton, Canada
| | - Mustafaa Wahab
- McMaster University Department of Medicine, Hamilton, Canada
| | - Moaaz Rashad
- McMaster University Department of Medicine, Hamilton, Canada
| | - Nermin Diab
- McMaster University Department of Medicine, Hamilton, Canada
| | - Martin Kolb
- McMaster University Department of Medicine, Hamilton, Canada
- Firestone Institute for Respiratory Health, St Joseph's Healthcare, Hamilton, Canada
| | - Imran Satia
- McMaster University Department of Medicine, Hamilton, Canada
- Firestone Institute for Respiratory Health, St Joseph's Healthcare, Hamilton, Canada
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Singer JP, Calfee CS, Delucchi K, Diamond JM, Anderson MA, Benvenuto LA, Gao Y, Wang P, Arcasoy SM, Lederer DJ, Hays SR, Kukreja J, Venado A, Kolaitis NA, Leard LE, Shah RJ, Kleinhenz ME, Golden J, Betancourt L, Oyster M, Brown M, Zaleski D, Medikonda N, Kalman L, Balar P, Patel S, Calabrese DR, Greenland JR, Christie JD. Subphenotypes of frailty in lung transplant candidates. Am J Transplant 2023; 23:531-539. [PMID: 36740192 PMCID: PMC11005295 DOI: 10.1016/j.ajt.2023.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 12/16/2022] [Accepted: 12/30/2022] [Indexed: 02/05/2023]
Abstract
Heterogeneous frailty pathobiology might explain the inconsistent associations observed between frailty and lung transplant outcomes. A Subphenotype analysis could refine frailty measurement. In a 3-center pilot cohort study, we measured frailty by the Short Physical Performance Battery, body composition, and serum biomarkers reflecting causes of frailty. We applied latent class modeling for these baseline data. Next, we tested class construct validity with disability, waitlist delisting/death, and early postoperative complications. Among 422 lung transplant candidates, 2 class model fit the best (P = .01). Compared with Subphenotype 1 (n = 333), Subphenotype 2 (n = 89) was characterized by systemic and innate inflammation (higher IL-6, CRP, PTX3, TNF-R1, and IL-1RA); mitochondrial stress (higher GDF-15 and FGF-21); sarcopenia; malnutrition; and lower hemoglobin and walk distance. Subphenotype 2 had a worse disability and higher risk of waitlist delisting or death (hazards ratio: 4.0; 95% confidence interval: 1.8-9.1). Of the total cohort, 257 underwent transplant (Subphenotype 1: 196; Subphenotype 2: 61). Subphenotype 2 had a higher need for take back to the operating room (48% vs 28%; P = .005) and longer posttransplant hospital length of stay (21 days [interquartile range: 14-33] vs 18 days [14-28]; P = .04). Subphenotype 2 trended toward fewer ventilator-free days, needing more postoperative extracorporeal membrane oxygenation and dialysis, and higher need for discharge to rehabilitation facilities (P ≤ .20). In this early phase study, we identified biological frailty Subphenotypes in lung transplant candidates. A hyperinflammatory, sarcopenic Subphenotype seems to be associated with worse clinical outcomes.
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Affiliation(s)
- Jonathan P Singer
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA.
| | - Carolyn S Calfee
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Kevin Delucchi
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA
| | - Joshua M Diamond
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michaela A Anderson
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Luke A Benvenuto
- Division of Pulmonary, Allergy and Critical Care Medicine, Columbia University Medical Center, New York City, New York, USA
| | - Ying Gao
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Ping Wang
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA; San Francisco Veterans Affairs Health Care System, San Francisco, California, USA
| | - Selim M Arcasoy
- Division of Pulmonary, Allergy and Critical Care Medicine, Columbia University Medical Center, New York City, New York, USA
| | | | - Steven R Hays
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Jasleen Kukreja
- Division of Cardiothoracic Surgery, University of California, San Francisco, California, USA
| | - Aida Venado
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Nicholas A Kolaitis
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Lorianna E Leard
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Rupal J Shah
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Mary Ellen Kleinhenz
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Jeffrey Golden
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Legna Betancourt
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Michelle Oyster
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Melanie Brown
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Derek Zaleski
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nikhila Medikonda
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA
| | - Laurel Kalman
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Priya Balar
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Shreena Patel
- Division of Pulmonary, Allergy and Critical Care Medicine, Columbia University Medical Center, New York City, New York, USA
| | - Daniel R Calabrese
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA; San Francisco Veterans Affairs Health Care System, San Francisco, California, USA
| | - John R Greenland
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, California, USA; San Francisco Veterans Affairs Health Care System, San Francisco, California, USA
| | - Jason D Christie
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Sinha P, Lawler PR. Are There Distinct Cardiovascular Subclasses in Acute Respiratory Distress Syndrome? Maybe. Crit Care Med 2023; 51:546-549. [PMID: 36928014 DOI: 10.1097/ccm.0000000000005816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Affiliation(s)
- Pratik Sinha
- Division of Clinical and Translational Research, Department of Anesthesia, Washington University School of Medicine, St. Louis, MO
- Division of Critical Care, Department of Anesthesia, Washington University School of Medicine, St. Louis, MO
| | - Patrick R Lawler
- Peter Munk Cardiac Centre, Toronto General Hospital, Toronto, ON, Canada
- Division of Cardiology and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
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Alipanah-Lechner N, Neyton L, Mick E, Willmore A, Leligdowicz A, Contrepois K, Jauregui A, Zhuo H, Hendrickson C, Gomez A, Sinha P, Kangelaris KN, Liu KD, Matthay MA, Rogers AJ, Calfee CS. Plasma metabolic profiling implicates dysregulated lipid metabolism and glycolytic shift in hyperinflammatory ARDS. Am J Physiol Lung Cell Mol Physiol 2023; 324:L297-L306. [PMID: 36648136 PMCID: PMC9988532 DOI: 10.1152/ajplung.00278.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/16/2022] [Accepted: 01/09/2023] [Indexed: 01/18/2023] Open
Abstract
Using latent class analysis (LCA) of clinical and protein biomarkers, researchers have identified two phenotypes of the acute respiratory distress syndrome (ARDS) with divergent clinical trajectories and treatment responses. We investigated whether plasma metabolites differed among patients with LCA-derived hyperinflammatory and hypoinflammatory ARDS, and we tested the prognostic utility of adding metabolic clusters to LCA phenotypes. We analyzed data from 93 patients with ARDS and sepsis enrolled in a multicenter prospective cohort of critically ill patients, comparing 970 metabolites between the two LCA-derived phenotypes. In all, 188 metabolites were differentially abundant between the two LCA-derived phenotypes. After adjusting for age, sex, confounding medications, and comorbid liver and kidney disease, 82 metabolites remained significantly different. Patients with hyperinflammatory ARDS had reduced circulating lipids but high levels of pyruvate, lactate, and malate. Metabolic cluster and LCA-derived phenotypes were each significantly and independently associated with survival. Patients with hyperinflammatory ARDS may be experiencing a glycolytic shift leading to dysregulated lipid metabolism. Metabolic profiling offers prognostic information beyond what is captured by LCA phenotypes alone. Deeper biological profiling may identify key differences in pathogenesis among patients with ARDS and may lead to novel targeted therapies.
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Affiliation(s)
- Narges Alipanah-Lechner
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Lucile Neyton
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Eran Mick
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, California, United States
- Chan Zuckerberg Biohub, San Francisco, California, United States
| | - Andrew Willmore
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Aleksandra Leligdowicz
- Cardiovascular Research Institute, University of California, San Francisco, California, United States
- Interdepartmental Division of Critical Care Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States
| | - Alejandra Jauregui
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Hanjing Zhuo
- Cardiovascular Research Institute, University of California, San Francisco, California, United States
- Department of Anesthesia, University of California, San Francisco, California, United States
| | - Carolyn Hendrickson
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital, San Francisco, California, United States
| | - Antonio Gomez
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital, San Francisco, California, United States
| | - Pratik Sinha
- Division of Clinical and Translational Research, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States
- Division of Critical Care, Department of Anesthesia, Washington University, St. Louis, Missouri, United States
| | - Kirsten N Kangelaris
- Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Kathleen D Liu
- Cardiovascular Research Institute, University of California, San Francisco, California, United States
- Division of Nephrology, Department of Medicine, University of California, San Francisco, California, United States
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Department of Anesthesia, University of California, San Francisco, California, United States
| | - Angela J Rogers
- Division of Pulmonary and Critical Care, Department of Medicine, Stanford University, Stanford, California, United States
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Department of Anesthesia, University of California, San Francisco, California, United States
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Rizzo AN, Aggarwal NR, Thompson BT, Schmidt EP. Advancing Precision Medicine for the Diagnosis and Treatment of Acute Respiratory Distress Syndrome. J Clin Med 2023; 12:1563. [PMID: 36836098 PMCID: PMC9966442 DOI: 10.3390/jcm12041563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
Acute respiratory distress syndrome (ARDS) is a common and life-threatening cause of respiratory failure. Despite decades of research, there are no effective pharmacologic therapies to treat this disease process and mortality remains high. The shortcomings of prior translational research efforts have been increasingly attributed to the heterogeneity of this complex syndrome, which has led to an increased focus on elucidating the mechanisms underlying the interpersonal heterogeneity of ARDS. This shift in focus aims to move the field towards personalized medicine by defining subgroups of ARDS patients with distinct biology, termed endotypes, to quickly identify patients that are most likely to benefit from mechanism targeted treatments. In this review, we first provide a historical perspective and review the key clinical trials that have advanced ARDS treatment. We then review the key challenges that exist with regards to the identification of treatable traits and the implementation of personalized medicine approaches in ARDS. Lastly, we discuss potential strategies and recommendations for future research that we believe will aid in both understanding the molecular pathogenesis of ARDS and the development of personalized treatment approaches.
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Affiliation(s)
- Alicia N. Rizzo
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA
| | - Neil R. Aggarwal
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA
| | - Eric P. Schmidt
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA
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Bai Y, Huang X, Xia J, Zhan Q. A narrative review of progress in the application of artificial intelligence in acute respiratory distress syndrome: subtypes and predictive models. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:128. [PMID: 36819521 PMCID: PMC9929814 DOI: 10.21037/atm-22-3153] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 11/09/2022] [Indexed: 12/24/2022]
Abstract
Background and Objective Acute respiratory distress syndrome (ARDS) occurs in different populations, and it is very challenging to manage heterogeneous patient groups. Artificial intelligence (AI) aids in interpreting complex data of patients with ARDS and can be used to detect adverse events as it can automatically capture complex relationships. This review aimed to explore the application and progress of AI in ARDS (e.g., subgroup classification of patients with ARDS via unsupervised clustering and supervised predictive models for early detection) and identify the current ARDS-related problems that can be solved using AI. Methods This comprehensive and narrative review was performed to obtain information about the application of AI in ARDS and summarize its subtypes and predictive models. Key Content and Findings The current applications of AI and machine learning in ARDS include ARDS subgroup classification, diagnosis, and survival prediction. In this review, the current problems that should be addressed by AI in ARDS were identified, and our findings may serve as a useful reference for its translational use in the ARDS field. Conclusions Owing to the discovery of hyper- and hypoinflammatory subtypes, individualized treatment of ARDS is possible, and diagnosis and survival prediction are essential in disease management and planning. However, prospective studies should clarify the reliability and generalizability of the results using AI and machine learning and performing bedside testing in larger populations to establish a more stable and time-resilient model. Therefore, a consensus on conducting and reporting machine learning studies in medicine should be urgently established.
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Affiliation(s)
- Yu Bai
- Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China;,Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Xu Huang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Jingen Xia
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Qingyuan Zhan
- Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China;,Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
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Abstract
Heterogeneity in sepsis and acute respiratory distress syndrome (ARDS) is increasingly being recognized as one of the principal barriers to finding efficacious targeted therapies. The advent of multiple high-throughput biological data ("omics"), coupled with the widespread access to increased computational power, has led to the emergence of phenotyping in critical care. Phenotyping aims to use a multitude of data to identify homogenous subgroups within an otherwise heterogenous population. Increasingly, phenotyping schemas are being applied to sepsis and ARDS to increase understanding of these clinical conditions and identify potential therapies. Here we present a selective review of the biological phenotyping schemas applied to sepsis and ARDS. Further, we outline some of the challenges involved in translating these conceptual findings to bedside clinical decision-making tools.
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Affiliation(s)
- Pratik Sinha
- Division of Clinical & Translational Research and Division of Critical Care, Department of Anesthesia, Washington University, St. Louis, Missouri, USA;
| | - Nuala J Meyer
- Division of Pulmonary, Allergy, and Critical Care Medicine; Center for Translational Lung Biology; and Lung Biology Institute, University of Pennsylvania Perelman School of Medicine; Philadelphia, Pennsylvania, USA
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy & Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, USA
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Bai Y, Xia J, Huang X, Chen S, Zhan Q. Using machine learning for the early prediction of sepsis-associated ARDS in the ICU and identification of clinical phenotypes with differential responses to treatment. Front Physiol 2022; 13:1050849. [PMID: 36579020 PMCID: PMC9791185 DOI: 10.3389/fphys.2022.1050849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
Background: An early diagnosis model with clinical phenotype classification is key for the early identification and precise treatment of sepsis-associated acute respiratory distress syndrome (ARDS). This study aimed to: 1) build a machine learning diagnostic model for patients with sepsis-associated ARDS using easily accessible early clinical indicators, 2) conduct rapid classification of clinical phenotypes in this population, and 3) explore the differences in clinical characteristics, outcomes, and treatment responses of different phenotypes. Methods: This study is based on data from the Telehealth Intensive Care Unit (eICU) and Medical Information Mart for Intensive Care IV (MIMIC-IV). We trained and tested the early diagnostic model of sepsis-associated ARDS patients in the eICU. We used key predictive indicators to cluster sepsis-associated ARDS patients and determine the characteristics and clinical outcomes of different phenotypes, as well to explore the differences of in-hospital mortality among different the positive end-expiratory pressure (PEEP) levels in different phenotypes. These results are verified in MIMIC-IV to evaluate whether they are repeatable. Results: Among the diagnostic models constructed in 19,249 sepsis patients and 5,947 sepsis-associated ARDS patients, the AdaBoost (Decision Tree) model achieved the best performance with an area under the receiver operating characteristic curve (AUC) of 0.895, which is higher than that of the traditional Logistic Regression model (Z = -2.40,p = 0.013), and the accuracy of 70.06%, sensitivity of 78.11% and specificity of 78.74%. We simultaneously identified three sepsis-associated ARDS phenotypes. Cluster 0 (n = 3,669) had the lowest in-hospital mortality rate (6.51%) and fewer laboratory abnormalities (lower WBC (median:15.000 K/mcL), lower blood glucose (median:158.000 mg/dl), lower creatinine (median:1.200 mg/dl), lower lactic acid (median:3.000 mmol/L); p < 0.001). Cluster 1 (n = 1,554) had the highest in-hospital mortality rate (75.29%) and the most laboratory abnormalities (higher WBC (median:18.300 K/mcL), higher blood glucose (median:188.000 mg/dl), higher creatinine (median:2.300 mg/dl), higher lactic acid (median:3.900 mmol/L); p < 0.001). Cluster 2 (n = 724) had the most complex condition, with a moderate in-hospital mortality rate (29.7%) and the longest intensive care unit stay. In Clusters 0 and 1, patients with high PEEP had higher in-hospital mortality rate than those with low PEEP, but the opposite trend was seen in Cluster 2. These results were repeatable in 11,935 patients with sepsis and 2,699 patients with sepsis-associated ARDS patients in the MIMIC-IV cohort. Conclusion: A machine learning diagnostic model of sepsis-associated ARDS patients was established. Three phenotypes with different clinical features and outcomes were clustered, and these had different therapeutic responses. These findings are helpful for the early and rapid identification of sepsis-associated ARDS patients and their precise individualized treatment.
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Affiliation(s)
- Yu Bai
- Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China,Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Jingen Xia
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Xu Huang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Shengsong Chen
- Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China,Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Qingyuan Zhan
- Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China,Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China,*Correspondence: Qingyuan Zhan,
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Leligdowicz A, Harhay MO, Calfee CS. Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead. NEJM EVIDENCE 2022; 1:EVIDra2200118. [PMID: 38319856 DOI: 10.1056/evidra2200118] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.
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Affiliation(s)
- Aleksandra Leligdowicz
- Department of Medicine, Division of Critical Care Medicine, Western University, London, ON, Canada
- Robarts Research Institute, Western University, London, ON, Canada
| | - Michael O Harhay
- Clinical Trials Methods and Outcomes Lab, Palliative and Advanced Illness Research (PAIR) Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Carolyn S Calfee
- Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco
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Bos LDJ, Ware LB. Acute respiratory distress syndrome: causes, pathophysiology, and phenotypes. Lancet 2022; 400:1145-1156. [PMID: 36070787 DOI: 10.1016/s0140-6736(22)01485-4] [Citation(s) in RCA: 158] [Impact Index Per Article: 79.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/14/2022] [Accepted: 07/27/2022] [Indexed: 12/15/2022]
Abstract
Acute respiratory distress syndrome (ARDS) is a common clinical syndrome of acute respiratory failure as a result of diffuse lung inflammation and oedema. ARDS can be precipitated by a variety of causes. The pathophysiology of ARDS is complex and involves the activation and dysregulation of multiple overlapping and interacting pathways of injury, inflammation, and coagulation, both in the lung and systemically. Mechanical ventilation can contribute to a cycle of lung injury and inflammation. Resolution of inflammation is a coordinated process that requires downregulation of proinflammatory pathways and upregulation of anti-inflammatory pathways. The heterogeneity of the clinical syndrome, along with its biology, physiology, and radiology, has increasingly been recognised and incorporated into identification of phenotypes. A precision-medicine approach that improves the identification of more homogeneous ARDS phenotypes should lead to an improved understanding of its pathophysiological mechanisms and how they differ from patient to patient.
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Affiliation(s)
- Lieuwe D J Bos
- Intensive Care, Amsterdam UMC-location AMC, University of Amsterdam, Amsterdam, Netherlands
| | - Lorraine B Ware
- Vanderbilt University School of Medicine, Medical Center North, Vanderbilt University, Nashville, TN, USA.
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Wick KD, Aggarwal NR, Curley MAQ, Fowler AA, Jaber S, Kostrubiec M, Lassau N, Laterre PF, Lebreton G, Levitt JE, Mebazaa A, Rubin E, Sinha P, Ware LB, Matthay MA. Opportunities for improved clinical trial designs in acute respiratory distress syndrome. THE LANCET. RESPIRATORY MEDICINE 2022; 10:916-924. [PMID: 36057279 DOI: 10.1016/s2213-2600(22)00294-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 07/02/2022] [Accepted: 07/19/2022] [Indexed: 02/08/2023]
Abstract
The acute respiratory distress syndrome (ARDS) is a common critical illness syndrome with high morbidity and mortality. There are no proven pharmacological therapies for ARDS. The current definition of ARDS is based on shared clinical characteristics but does not capture the heterogeneity in clinical risk factors, imaging characteristics, physiology, timing of onset and trajectory, and biology of the syndrome. There is increasing interest within the ARDS clinical trialist community to design clinical trials that reduce heterogeneity in the trial population. This effort must be balanced with ongoing work to craft an inclusive, global definition of ARDS, with important implications for trial design. Ultimately, the two aims-to design trials that are applicable to the diverse global ARDS population while also advancing opportunities to identify targetable traits-should coexist. In this Personal View, we recommend two primary strategies to improve future ARDS trials: the development of new methods to target treatable traits in clinical trial populations, and improvements in the representativeness of ARDS trials, with the inclusion of global populations. We emphasise that these two strategies are complementary. We also discuss how a proposed expansion of the definition of ARDS could affect the future of clinical trials.
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Affiliation(s)
- Katherine D Wick
- Cardiovascular Research Institute, University of California, San Francisco, CA, USA
| | - Neil R Aggarwal
- Division of Pulmonary Sciences and Critical Care, Department of Medicine, University of Colorado, Aurora, CO, USA; National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Martha A Q Curley
- Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - Alpha A Fowler
- Division of Pulmonary Disease and Critical Care, Virginia Commonwealth University, Richmond, VA, USA
| | - Samir Jaber
- University Hospital, CHU de Montpellier Hôpital Saint Eloi, Intensive Care Unit and Transplantation, Department of Anesthesiology DAR B, Montpellier, France
| | - Maciej Kostrubiec
- Department of Internal Medicine and Cardiology, Medical University of Warsaw, Warsaw, Poland
| | - Nathalie Lassau
- Department of Imaging, Gustave Roussy, Université Paris Saclay, Villejuif, France; Biomaps, UMR1281 INSERM, CEA, CNRS, Université Paris Saclay, Villejuif, France
| | - Pierre François Laterre
- Intensive Care Medicine, Saint-Luc University Hospital, Université Catholique de Louvain, Brussels, Belgium
| | - Guillaume Lebreton
- Institute of Cardiometabolism and Nutrition, Inserm, UMRS 1166-ICAN, Sorbonne University, Paris, France; Cardiac Surgery Service, Institute of Cardiology, AP-HP, Sorbonne University, Paris, France
| | - Joseph E Levitt
- Division of Pulmonary, Allergy, and Critical Care Medicine, Stanford University, Stanford, CA, USA
| | - Alexandre Mebazaa
- Department of Anesthesiology and Critical Care Medicine, AP-HP, Saint Louis and Lariboisière University Hospitals, Paris, France
| | | | - Pratik Sinha
- Department of Anesthesiology, Washington University in St Louis, St Louis, MO, USA
| | - Lorraine B Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael A Matthay
- Cardiovascular Research Institute, University of California, San Francisco, CA, USA; Departments of Medicine and Anesthesia, University of California, San Francisco, CA, USA.
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Martin TR, Zemans RL, Ware LB, Schmidt EP, Riches DWH, Bastarache L, Calfee CS, Desai TJ, Herold S, Hough CL, Looney MR, Matthay MA, Meyer N, Parikh SM, Stevens T, Thompson BT. New Insights into Clinical and Mechanistic Heterogeneity of the Acute Respiratory Distress Syndrome: Summary of the Aspen Lung Conference 2021. Am J Respir Cell Mol Biol 2022; 67:284-308. [PMID: 35679511 PMCID: PMC9447141 DOI: 10.1165/rcmb.2022-0089ws] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/09/2022] [Indexed: 12/15/2022] Open
Abstract
Clinical and molecular heterogeneity are common features of human disease. Understanding the basis for heterogeneity has led to major advances in therapy for many cancers and pulmonary diseases such as cystic fibrosis and asthma. Although heterogeneity of risk factors, disease severity, and outcomes in survivors are common features of the acute respiratory distress syndrome (ARDS), many challenges exist in understanding the clinical and molecular basis for disease heterogeneity and using heterogeneity to tailor therapy for individual patients. This report summarizes the proceedings of the 2021 Aspen Lung Conference, which was organized to review key issues related to understanding clinical and molecular heterogeneity in ARDS. The goals were to review new information about ARDS phenotypes, to explore multicellular and multisystem mechanisms responsible for heterogeneity, and to review how best to account for clinical and molecular heterogeneity in clinical trial design and assessment of outcomes. The report concludes with recommendations for future research to understand the clinical and basic mechanisms underlying heterogeneity in ARDS to advance the development of new treatments for this life-threatening critical illness.
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Affiliation(s)
- Thomas R. Martin
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, Washington
| | - Rachel L. Zemans
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine and Program in Cellular and Molecular Biology, University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Lorraine B. Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine and
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Pathology, Microbiology, and Immunology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Eric P. Schmidt
- Division of Pulmonary Sciences and Critical Care, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado
| | - David W. H. Riches
- Division of Pulmonary Sciences and Critical Care, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado
- Program in Cell Biology, Department of Pediatrics, National Jewish Health, Denver, Colorado
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Carolyn S. Calfee
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Anesthesia
| | - Tushar J. Desai
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Stem Cell Institute, Stanford University School of Medicine, Stanford, California
| | - Susanne Herold
- Department of Internal Medicine VI and Cardio-Pulmonary Institute (CPI), Universities of Giessen and Marburg Lung Center (UGMLC), Giessen, Germany
| | - Catherine L. Hough
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Oregon Health & Science University, Portland, Oregon
| | | | - Michael A. Matthay
- Departments of Medicine and Anesthesia, Cardiovascular Research Institute, University of California San Francisco, San Francisco, California
| | - Nuala Meyer
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Samir M. Parikh
- Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
- Division of Nephrology, University of Texas Southwestern, Dallas, Texas
| | - Troy Stevens
- Department of Physiology and Cell Biology, College of Medicine, Center for Lung Biology, University of South Alabama, Mobile, Alabama; and
| | - B. Taylor Thompson
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
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Vaara ST, Bhatraju PK, Stanski NL, McMahon BA, Liu K, Joannidis M, Bagshaw SM. Subphenotypes in acute kidney injury: a narrative review. Crit Care 2022; 26:251. [PMID: 35986336 PMCID: PMC9389711 DOI: 10.1186/s13054-022-04121-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 07/20/2022] [Indexed: 11/26/2022] Open
Abstract
Acute kidney injury (AKI) is a frequently encountered syndrome especially among the critically ill. Current diagnosis of AKI is based on acute deterioration of kidney function, indicated by an increase in creatinine and/or reduced urine output. However, this syndromic definition encompasses a wide variety of distinct clinical features, varying pathophysiology, etiology and risk factors, and finally very different short- and long-term outcomes. Lumping all AKI together may conceal unique pathophysiologic processes specific to certain AKI populations, and discovering these AKI subphenotypes might help to develop targeted therapies tackling unique pathophysiological processes. In this review, we discuss the concept of AKI subphenotypes, current knowledge regarding both clinical and biomarker-driven subphenotypes, interplay with AKI subphenotypes and other ICU syndromes, and potential future and clinical implications.
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Affiliation(s)
- Suvi T Vaara
- Division of Intensive Care Medicine, Department of Anesthesiology, Intensive Care and Pain Medicine, Meilahti Hospital, University of Helsinki and Helsinki University Hospital, PO Box 340, 00290, Helsinki, Finland.
| | - Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, USA
- Sepsis Center of Research Excellence (SCORE), University of Washington, Seattle, USA
| | - Natalja L Stanski
- Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, USA
| | - Blaithin A McMahon
- Division of Nephrology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Kathleen Liu
- Divisions of Nephrology and Critical Care, Departments of Medicine and Anesthesia, University of California, San Francisco, USA
| | - Michael Joannidis
- Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Sean M Bagshaw
- Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, Edmonton, Canada
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Wildi K, Bouquet M, Ainola C, Livingstone S, Colombo SM, Heinsar S, Sato N, Sato K, Wilson E, Abbate G, Passmore MR, Hyslop K, Liu K, Li Bassi G, Suen JY, Fraser JF. Differential Protein Expression among Two Different Ovine ARDS Phenotypes-A Preclinical Randomized Study. Metabolites 2022; 12:metabo12070655. [PMID: 35888779 PMCID: PMC9319228 DOI: 10.3390/metabo12070655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/08/2022] [Accepted: 07/13/2022] [Indexed: 01/25/2023] Open
Abstract
Despite decades of comprehensive research, Acute Respiratory Distress Syndrome (ARDS) remains a disease with high mortality and morbidity worldwide. The discovery of inflammatory subphenotypes in human ARDS provides a new approach to study the disease. In two different ovine ARDS lung injury models, one induced by additional endotoxin infusion (phenotype 2), mimicking some key features as described in the human hyperinflammatory group, we aim to describe protein expression among the two different ovine models. Nine animals on mechanical ventilation were included in this study and were randomized into (a) phenotype 1, n = 5 (Ph1) and (b) phenotype 2, n = 4 (Ph2). Plasma was collected at baseline, 2, 6, 12, and 24 h. After protein extraction, data-independent SWATH-MS was applied to inspect protein abundance at baseline, 2, 6, 12, and 24 h. Cluster analysis revealed protein patterns emerging over the study observation time, more pronounced by the factor of time than different injury models of ARDS. A protein signature consisting of 33 proteins differentiated among Ph1/2 with high diagnostic accuracy. Applying network analysis, proteins involved in the inflammatory and defense response, complement and coagulation cascade, oxygen binding, and regulation of lipid metabolism were activated over time. Five proteins, namely LUM, CA2, KNG1, AGT, and IGJ, were more expressed in Ph2.
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Affiliation(s)
- Karin Wildi
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
- Department of Cardiology, Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, 4031 Basel, Switzerland
- Correspondence:
| | - Mahe Bouquet
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Carmen Ainola
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Samantha Livingstone
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Sebastiano Maria Colombo
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Department of Anaesthesia and Intensive Care Medicine, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Silver Heinsar
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Noriko Sato
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
| | - Kei Sato
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Emily Wilson
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Gabriella Abbate
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Margaret R. Passmore
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Kieran Hyslop
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - Keibun Liu
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
| | - Gianluigi Li Bassi
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
- Medical Faculty, Queensland University of Technology, Brisbane 4059, Australia
- Uniting Care Hospitals, St Andrews War Memorial and The Wesley Intensive Care Units, Brisbane 4001, Australia
| | - Jacky Y. Suen
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
| | - John F. Fraser
- Critical Care Research Group, The Prince Charles Hospital, Brisbane 4032, Australia; (M.B.); (C.A.); (S.L.); (S.M.C.); (S.H.); (N.S.); (K.S.); (E.W.); (G.A.); (M.R.P.); (K.H.); (K.L.); (G.L.B.); (J.Y.S.); (J.F.F.)
- Medical Faculty, The University of Queensland, St. Lucia, Brisbane 4067, Australia
- Uniting Care Hospitals, St Andrews War Memorial and The Wesley Intensive Care Units, Brisbane 4001, Australia
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Diamond JM. Don't Inhale: Acute Respiratory Distress Syndrome Risk and Tobacco Exposure in Patients with Sepsis. Am J Respir Crit Care Med 2022; 205:866-867. [PMID: 35130469 PMCID: PMC9838625 DOI: 10.1164/rccm.202201-0034ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Affiliation(s)
- Joshua M Diamond
- Pulmonary, Allergy, and Critical Care Division Perelman School of Medicine at the University of Pennsylvania Philadelphia, Pennsylvania
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Maddali MV, Churpek M, Pham T, Rezoagli E, Zhuo H, Zhao W, He J, Delucchi KL, Wang C, Wickersham N, McNeil JB, Jauregui A, Ke S, Vessel K, Gomez A, Hendrickson CM, Kangelaris KN, Sarma A, Leligdowicz A, Liu KD, Matthay MA, Ware LB, Laffey JG, Bellani G, Calfee CS, Sinha P. Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis. THE LANCET. RESPIRATORY MEDICINE 2022; 10:367-377. [PMID: 35026177 PMCID: PMC8976729 DOI: 10.1016/s2213-2600(21)00461-6] [Citation(s) in RCA: 63] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/12/2021] [Accepted: 10/12/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. METHODS In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. FINDINGS The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90-0·95) in EARLI and 0·88 (0·84-0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81-0·94] vs 0·92 [0·88-0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). INTERPRETATION Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. FUNDING US National Institutes of Health and European Society of Intensive Care Medicine.
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Affiliation(s)
- Manoj V Maddali
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Matthew Churpek
- Division of Allergy, Pulmonary, and Critical Care, Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Tai Pham
- Service de Médecine Intensive-Réanimation, AP-HP, Hôpital de Bicêtre, DMU 4 CORREVE Maladies du Cœur et des Vaisseaux, FHU Sepsis, Groupe de Recherche Clinique CARMAS, Le Kremlin-Bicêtre, France; Université Paris-Saclay, UVSQ, Université Paris-Sud, Inserm U1018, Equipe d'Epidémiologie Respiratoire Intégrative, CESP, 94807, Villejuif, France
| | - Emanuele Rezoagli
- Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Hanjing Zhuo
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Wendi Zhao
- Division of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - June He
- Division of Clinical and Translational Research, Washington University School of Medicine, St Louis, MO, USA
| | - Kevin L Delucchi
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Chunxue Wang
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy Wickersham
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - J Brennan McNeil
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alejandra Jauregui
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Serena Ke
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Kathryn Vessel
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Antonio Gomez
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | - Carolyn M Hendrickson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA
| | - Kirsten N Kangelaris
- Division of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Aartik Sarma
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Aleksandra Leligdowicz
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Kathleen D Liu
- Division of Nephrology, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Michael A Matthay
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Lorraine B Ware
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John G Laffey
- School of Medicine, Regenerative Medicine Institute at CÚRAM Centre for Research in Medical Devices, National University of Ireland Galway, Galway, Ireland; Anaesthesia and Intensive Care Medicine, Galway University Hospitals, Galway, Ireland
| | - Giacomo Bellani
- Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy; Department of Anesthesia and Intensive Care Medicine, ASST Monza-Ospedale San Gerardo, Monza, Italy
| | - Carolyn S Calfee
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Anesthesia, University of California, San Francisco, San Francisco, CA, USA
| | - Pratik Sinha
- Division of Clinical and Translational Research, Washington University School of Medicine, St Louis, MO, USA; Department of Anesthesia, Division of Critical Care, Washington University, St Louis, MO, USA.
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