1
|
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. Crit Care 2024; 28:321. [PMID: 39354616 PMCID: PMC11445942 DOI: 10.1186/s13054-024-05061-4] [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: 04/22/2024] [Accepted: 08/07/2024] [Indexed: 10/03/2024] Open
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, considering multi-organ dynamics. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate the generalizability of the derived phenotypes. METHODS We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥ 24 h. Data from two different high-volume academic hospital centers were used, where all phenotypes were derived in MICU of Hospital-I (N = 3225). The derived phenotypes were validated in MICU of Hospital-II (N = 848), SICU of Hospital-I (N = 1112), and SICU of Hospital-II (N = 465). Clinical data from 24 h 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 the MICU of Hospital-II and SICUs from Hospital-I and -II. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p < 0.01) and consistent across MICU and SICU of both Hospital-I and -II. 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.
Collapse
Affiliation(s)
- Tilendra Choudhary
- Department of Surgery, Duke University School of Medicine, Durham, NC, 27707, USA.
| | - Pulakesh Upadhyaya
- Department of Surgery, Duke University School of Medicine, Durham, NC, 27707, USA
| | - Carolyn M Davis
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, 30332, USA
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Philip Yang
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University, Atlanta, GA, 30322, USA
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Simon Tallowin
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
- Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine, Birmingham, UK
| | - Felipe A Lisboa
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
- Department of Surgery, Uniformed Services University of the Health Sciences and Walter Reed National Military Medical Center, Bethesda, MD, 20814, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, 20817, USA
| | - Seth A Schobel
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
- Department of Surgery, Uniformed Services University of the Health Sciences and Walter Reed National Military Medical Center, Bethesda, MD, 20814, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, 20817, USA
| | - Craig M Coopersmith
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, 30332, USA
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric A Elster
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA
- Department of Surgery, Uniformed Services University of the Health Sciences and Walter Reed National Military Medical Center, Bethesda, MD, 20814, USA
| | - Timothy G Buchman
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, 30332, USA
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Christopher J Dente
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, 30332, USA
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Rishikesan Kamaleswaran
- Department of Surgery, Duke University School of Medicine, Durham, NC, 27707, USA.
- Emory Critical Care Center and Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA.
| |
Collapse
|
2
|
Wang JZ, Patil V, Landry AP, Gui C, Ajisebutu A, Liu J, Saarela O, Pugh SL, Won M, Patel Z, Yakubov R, Kaloti R, Wilson C, Cohen-Gadol A, Zaazoue MA, Tabatabai G, Tatagiba M, Behling F, Almiron Bonnin DA, Holland EC, Kruser TJ, Barnholtz-Sloan JS, Sloan AE, Horbinski C, Chotai S, Chambless LB, Gao A, Rebchuk AD, Makarenko S, Yip S, Sahm F, Maas SLN, Tsang DS, Rogers CL, Aldape K, Nassiri F, Zadeh G. Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma. Nat Med 2024:10.1038/s41591-024-03167-4. [PMID: 39169220 DOI: 10.1038/s41591-024-03167-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 07/01/2024] [Indexed: 08/23/2024]
Abstract
Treatment of the tumor and dural margin with surgery and sometimes radiation are cornerstones of therapy for meningioma. Molecular classifications have provided insights into the biology of disease; however, response to treatment remains heterogeneous. In this study, we used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumors and 100 prospective meningiomas, from the RTOG-0539 phase 2 trial to define molecular biomarkers of treatment response. Using propensity score matching, we found that gross tumor resection was associated with longer progression-free survival (PFS) across all molecular groups and longer overall survival in proliferative meningiomas. Dural margin treatment (Simpson grade 1/2) prolonged PFS compared to no treatment (Simpson grade 3). Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. We subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification. This study highlights the potential for molecular profiling to refine surgical and radiotherapy decision-making.
Collapse
Affiliation(s)
- Justin Z Wang
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Vikas Patil
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Alexander P Landry
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Chloe Gui
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Andrew Ajisebutu
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Jeff Liu
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Olli Saarela
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Stephanie L Pugh
- NRG Oncology Statistics and Data Management Center, Philadelphia, PA, USA
| | - Minhee Won
- NRG Oncology Statistics and Data Management Center, Philadelphia, PA, USA
| | - Zeel Patel
- Temerty School of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Rebeca Yakubov
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Ramneet Kaloti
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | | | - Aaron Cohen-Gadol
- Department of Neurological Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Mohamed A Zaazoue
- Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Orthopedic Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ghazaleh Tabatabai
- German Cancer Consortium (DKTK), DKFZ Partner Site Tübingen, Tübingen, Germany
- Cluster of Excellence (EXC 2180) 'Image Guided and Functionally Instructed Tumor Therapies', Eberhard Karls University Tübingen, Tübingen, Germany
- Department of Neurology and Interdisciplinary Neuro-Oncology, Center for Neuro-Oncology, Comprehensive Cancer Center, Hertie Institute for Clinical Brain Research, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Marcos Tatagiba
- Department of Neurosurgery, Center for Neuro-Oncology, Comprehensive Cancer Center, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Felix Behling
- Department of Neurosurgery, Center for Neuro-Oncology, Comprehensive Cancer Center, Eberhard Karls University Tübingen, Tübingen, Germany
| | | | - Eric C Holland
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Tim J Kruser
- Department of Human Oncology, University of Wisconsin Hospitals and Clinics, Madison, WI, USA
| | - Jill S Barnholtz-Sloan
- Central Brain Tumor Registry of the United States, Hinsdale, IL, USA
- Trans Divisional Research Program (TDRP), Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute, Bethesda, MD, USA
- Center for Biomedical Informatics & Information Technology (CBIIT), National Cancer Institute, Bethesda, MD, USA
| | - Andrew E Sloan
- Piedmont Brain Tumor Center, Piedmonth Healthcare System, Atlanta, GA, USA
| | - Craig Horbinski
- Department of Pathology, Northwestern University, Evanston, IL, USA
- Lou & Jean Malnati Brain Tumor Institute at the Lurie Comprehensive Cancer Center, Northwestern University, Evanston, IL, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew Gao
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Alexander D Rebchuk
- Division of Neurosurgery, University of British Columbia, Vancouver, British Columbia, Canada
| | - Serge Makarenko
- Division of Neurosurgery, University of British Columbia, Vancouver, British Columbia, Canada
| | - Stephen Yip
- Department of Pathology & Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Felix Sahm
- Department of Neuropathology, Institute of Pathology, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sybren L N Maas
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pathology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Derek S Tsang
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - C Leland Rogers
- Radiation Oncology, Utah Cancer Specialists, Salt Lake City, UT, USA
| | - Kenneth Aldape
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Farshad Nassiri
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
| | - Gelareh Zadeh
- MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, Ontario, Canada.
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
| |
Collapse
|
3
|
Li L, Guan J, Peng X, Zhou L, Zhang Z, Ding L, Zheng L, Wu L, Hu Z, Liu L, Yao Y. Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury. BMC Med Inform Decis Mak 2024; 24:208. [PMID: 39054463 PMCID: PMC11271185 DOI: 10.1186/s12911-024-02583-3] [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: 05/30/2023] [Accepted: 06/21/2024] [Indexed: 07/27/2024] Open
Abstract
INTRODUCTION Sepsis-associated acute kidney injury (SA-AKI) is strongly associated with poor prognosis. We aimed to build a machine learning (ML)-based clinical model to predict 1-year mortality in patients with SA-AKI. METHODS Six ML algorithms were included to perform model fitting. Feature selection was based on the feature importance evaluated by the SHapley Additive exPlanations (SHAP) values. Area under the receiver operating characteristic curve (AUROC) was used to evaluate the discriminatory ability of the prediction model. Calibration curve and Brier score were employed to assess the calibrated ability. Our ML-based prediction models were validated both internally and externally. RESULTS A total of 12,750 patients with SA-AKI and 55 features were included to build the prediction models. We identified the top 10 predictors including age, ICU stay and GCS score based on the feature importance. Among the six ML algorithms, the CatBoost showed the best prediction performance with an AUROC of 0.813 and Brier score of 0.119. In the external validation set, the predictive value remained favorable (AUROC = 0.784). CONCLUSION In this study, we developed and validated a ML-based prediction model based on 10 commonly used clinical features which could accurately and early identify the individuals at high-risk of long-term mortality in patients with SA-AKI.
Collapse
Affiliation(s)
- Le Li
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Jingyuan Guan
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Xi Peng
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Likun Zhou
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Zhuxin Zhang
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Ligang Ding
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Lihui Zheng
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Lingmin Wu
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Zhicheng Hu
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Limin Liu
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China
| | - Yan Yao
- Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China.
| |
Collapse
|
4
|
Mastenbroek SE, Vogel JW, Collij LE, Serrano GE, Tremblay C, Young AL, Arce RA, Shill HA, Driver-Dunckley ED, Mehta SH, Belden CM, Atri A, Choudhury P, Barkhof F, Adler CH, Ossenkoppele R, Beach TG, Hansson O. Disease progression modelling reveals heterogeneity in trajectories of Lewy-type α-synuclein pathology. Nat Commun 2024; 15:5133. [PMID: 38879548 PMCID: PMC11180185 DOI: 10.1038/s41467-024-49402-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 06/04/2024] [Indexed: 06/19/2024] Open
Abstract
Lewy body (LB) diseases, characterized by the aggregation of misfolded α-synuclein proteins, exhibit notable clinical heterogeneity. This may be due to variations in accumulation patterns of LB neuropathology. Here we apply a data-driven disease progression model to regional neuropathological LB density scores from 814 brain donors with Lewy pathology. We describe three inferred trajectories of LB pathology that are characterized by differing clinicopathological presentation and longitudinal antemortem clinical progression. Most donors (81.9%) show earliest pathology in the olfactory bulb, followed by accumulation in either limbic (60.8%) or brainstem (21.1%) regions. The remaining donors (18.1%) initially exhibit abnormalities in brainstem regions. Early limbic pathology is associated with Alzheimer's disease-associated characteristics while early brainstem pathology is associated with progressive motor impairment and substantial LB pathology outside of the brain. Our data provides evidence for heterogeneity in the temporal spread of LB pathology, possibly explaining some of the clinical disparities observed in Lewy body disease.
Collapse
Affiliation(s)
- Sophie E Mastenbroek
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands.
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
| | - Jacob W Vogel
- Department of Clinical Sciences Malmö, Faculty of Medicine, SciLifeLab, Lund University, Lund, Sweden
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | | | | | - Alexandra L Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | | | - Holly A Shill
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Erika D Driver-Dunckley
- Department of Neurology, Parkinson's Disease and Movement Disorders Center, Mayo Clinic, Scottsdale, AZ, USA
| | - Shyamal H Mehta
- Department of Neurology, Parkinson's Disease and Movement Disorders Center, Mayo Clinic, Scottsdale, AZ, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, AZ, USA
- Department of Neurology, Center for Mind/Brain Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, MA, USA
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, The Netherlands
- Institutes of Neurology & Healthcare Engineering, University College London, London, UK
| | - Charles H Adler
- Department of Neurology, Parkinson's Disease and Movement Disorders Center, Mayo Clinic, Scottsdale, AZ, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
5
|
Li L, Zhou L, Peng X, Zhang Z, Zhang Z, Xiong Y, Hu Z, Yao Y. Association of stress hyperglycemia ratio and mortality in patients with sepsis: results from 13,199 patients. Infection 2024:10.1007/s15010-024-02264-3. [PMID: 38679664 DOI: 10.1007/s15010-024-02264-3] [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: 10/25/2023] [Accepted: 04/08/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND The stress hyperglycemia ratio (SHR), adjusted for average glycemic status, is suggested for assessing actual blood glucose levels. Its link with adverse outcomes is known in certain populations, yet its impact on sepsis patients' prognosis is unclear. This study explores the association between SHR and mortality in sepsis. METHODS We included 13,199 sepsis patients in this study and categorized SHR into distinct groups. Additionally, we utilized restricted cubic spline analysis to evaluate the correlation between SHR as a continuous variable and mortality. The primary outcome was 1-year all-cause mortality. Logistic regression and Cox proportional hazards models were employed to assess the associations between the SHR and both in-hospital mortality and 1-year mortality, respectively. RESULTS Among the study participants, 4,690 (35.5%) patients died during the 1-year follow-up. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and 1-year mortality. Using an SHR of 0.99 as the reference point, the hazard ratio for predicted 1-year mortality increased by 1.17 (95% CI 1.08 to 1.27) per standard deviation above 0.99, whereas each standard deviation increase predicted the hazard ratio of 0.52 (95% CI 0.39 to 0.69) below 0.99. Furthermore, we found that SHR could enhance the predictive performance of conventional severity scores. CONCLUSION There exists a U shaped association between SHR and mortality in sepsis patients, where both low and high SHR values are associated with an increased risk of poor outcomes.
Collapse
Affiliation(s)
- Le Li
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Likun Zhou
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Xi Peng
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Zhuxin Zhang
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Zhenhao Zhang
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Yulong Xiong
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Zhao Hu
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China
| | - Yan Yao
- Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Peking Union Medical College, Fuwai Hospital, Beijing, 100037, China.
| |
Collapse
|
6
|
Wang W, Shi Y, Zhang J, Wang Y, Cheteu Wabo TM, Yang Y, He W, Zhu S. Association of dietary overall antioxidant intake with all-cause and cause-specific mortality among adults with depression: evidence from NHANES 2005-2018. Food Funct 2024; 15:4603-4613. [PMID: 38590241 DOI: 10.1039/d4fo00236a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
Higher intakes of individual antioxidants such as vitamins A, C, and E have been linked to mortality in the general population, but the association of overall antioxidant intake with mortality especially in depressed adults remains unclear. We aimed to investigate whether the dietary overall antioxidant intake is associated with all-cause and cause-specific mortality among depressed adults. This study included 3051 US adults with depression, who participated in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. Patient Health Questionnaire-9 (PHQ-9) was used to define depression and evaluate depression severity. The dietary antioxidant quality score (DAQS) and dietary antioxidant index (DAI) were calculated based on the intakes of vitamins A, C, and E, zinc, selenium, and magnesium. A higher DAQS and DAI were significantly associated with lower depression scores (PHQ-9) (all P-trend < 0.05). For individual antioxidants, significant negative associations of vitamins A and E with all-cause mortality were observed. For overall antioxidant intake, the DAQS and DAI were inversely associated with all-cause and cancer mortality. Compared with participants in the lowest categories of DAQS and DAI, the corresponding HRs (95% CIs) in the highest categories were 0.63 (0.42-0.93) and 0.70 (0.49-0.98) for all-cause mortality and 0.39 (0.17-0.87) and 0.43 (0.21-0.88) for cancer mortality, respectively. The overall dietary antioxidant intake was beneficially associated with all-cause and cancer mortality in depressed adults. These findings suggest that comprehensive dietary antioxidant intake may improve depressive symptoms and lower mortality risk among adults with depression.
Collapse
Affiliation(s)
- Wenjie Wang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yuwei Shi
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jiakai Zhang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yifeng Wang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Therese Martin Cheteu Wabo
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yang Yang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wei He
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shankuan Zhu
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, 866 Yu-hang-tang Road, Hangzhou, Zhejiang, 310058, China.
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China
| |
Collapse
|
7
|
Tian Y, Zhou X, Jiang Y, Pan Y, Liu X, Gu X. Bidirectional association between falls and multimorbidity in middle-aged and elderly Chinese adults: a national longitudinal study. Sci Rep 2024; 14:9109. [PMID: 38643241 PMCID: PMC11032330 DOI: 10.1038/s41598-024-59865-z] [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: 08/26/2023] [Accepted: 04/16/2024] [Indexed: 04/22/2024] Open
Abstract
This study explores the bidirectional association between multimorbidity and falls in Chinese middle-aged and elderly adults. Participants aged 45 and above from the China Health and Retirement Longitudinal Study were included. Binary logistic regression assessed the impact of chronic conditions on fall incidence (stage I), while multinomial logistic regression examined the relationship between baseline falls and multimorbidity (stage II). The fully adjusted odds ratios (ORs) for one, two, or three or more chronic conditions were 1.34, 1.65, and 2.02, respectively. Among participants without baseline falls, 28.61% developed two or more chronic conditions during follow-up, compared to 37.4% of those with a history of falls. Fully adjusted ORs for one, two, or three or more chronic conditions in those with a history of falls were 1.21, 1.38 and 1.70, respectively. The bidirectional relationship held in sensitivity and subgroup analyses. A bidirectional relationship exists between multimorbidity and falls in Chinese middle-aged and elderly adults. Strengthening chronic condition screening and treatment in primary healthcare may reduce falls risk, and prioritizing fall prevention and intervention in daily life is recommended.
Collapse
Affiliation(s)
- Ye Tian
- Department of Health Statistics, School of Public Health, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China
| | - Xingzhao Zhou
- Department of Health Statistics, School of Public Health, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China
| | - Yan Jiang
- Department of Health Statistics, School of Public Health, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China
| | - Yidan Pan
- Department of Health Statistics, School of Public Health, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China
| | - Xuefeidan Liu
- Department of Marine Pharmacy, School of Pharmacy, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China
| | - Xingbo Gu
- Department of Health Statistics, School of Public Health, Hainan Medical University, No. 3, Xue Yuan Road, Longhua District, Haikou, 571199, People's Republic of China.
| |
Collapse
|
8
|
Li L, Tu B, Xiong Y, Hu Z, Zhang Z, Liu S, Yao Y. Machine Learning-Based Model for Predicting Prolonged Mechanical Ventilation in Patients with Congestive Heart Failure. Cardiovasc Drugs Ther 2024; 38:359-369. [PMID: 36383267 DOI: 10.1007/s10557-022-07399-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/24/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Mechanical ventilation (MV) is widely used to relieve respiratory failure in patients with congestive heart failure (CHF). Prolonged MV (PMV) is associated with a poor prognosis. We aimed to establish a prediction model based on machine learning (ML) algorithms for the early identification of patients with CHF requiring PMV. METHODS Twelve commonly used ML algorithms were used to build the prediction model. The least absolute shrinkage and selection operator (LASSO) regression was employed to select the key features. We examined the area under the curve (AUC) statistics to evaluate the prediction performance. Data from another database were used to conduct external validation. RESULTS We screened out 10 key features from the initial 65 variables via LASSO regression to improve the practicability of the model. The CatBoost model showed the best performance for predicting PMV among the 12 commonly used ML algorithms, with favorable discrimination (AUC = 0.790) and calibration (Brier score = 0.154). Moreover, hospital mortality could be accurately predicted using the CatBoost model as well (AUC = 0.844). In the external validation, the CatBoost model also showed satisfactory prediction performance (AUC = 0.780), suggesting certain generalizability of the model. Finally, a nomogram with risk classification of PMV was shown in this study. CONCLUSION The present study developed and validated a CatBoost model, which could accurately predict PMV in mechanically ventilated patients with CHF. Moreover, this model has a favorable performance in predicting hospital mortality in these patients.
Collapse
Affiliation(s)
- Le Li
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Bin Tu
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Yulong Xiong
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Zhao Hu
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Zhenghao Zhang
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Shangyu Liu
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China
| | - Yan Yao
- Chinese Academy of Medical Sciences, Peking Union Medical College, National Center for Cardiovascular Diseases, Fu Wai Hospital, Beijing, 100037, China.
| |
Collapse
|
9
|
Tang J, Zhong Z, Nijiati M, Wu C. Systemic inflammation response index as a prognostic factor for patients with sepsis-associated acute kidney injury: a retrospective observational study. J Int Med Res 2024; 52:3000605241235758. [PMID: 38518195 PMCID: PMC10960344 DOI: 10.1177/03000605241235758] [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: 11/09/2023] [Accepted: 02/12/2024] [Indexed: 03/24/2024] Open
Abstract
OBJECTIVE To assess the association between the systemic inflammation response index (SIRI) and the prognosis in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS In this observational study, adult patients with SA-AKI were categorized into three groups based on SIRI tertiles. Survival outcomes were compared across the three groups using Kaplan-Meier survival curves. Various Cox proportional hazards regression models were developed to determine the association between the SIRI and mortality in patients with SA-AKI. Subgroup analyses were also performed to explore the association between different SIRI tertiles and all-cause mortality. RESULTS After adjusting for several confounders, the second SIRI tertile (2.5 < SIRI < 7.6) was found to be an independent risk factor for 30-day mortality [hazard ratio (95% confidence interval): 1.19 (1.01-1.40)], 90-day mortality [1.22 (1.06-1.41)], and 365-day mortality [1.24 (1.09-1.40)]. Furthermore, high SIRI values were associated with increased risks of 30-day, 90-day, and 365-day mortality in patients with SA-AKI across all three models. The third tertile showed a significant association with adverse outcomes in most subgroups. CONCLUSIONS The SIRI serves as a comprehensive biomarker for predicting all-cause mortality of critically ill patients with SA-AKI.
Collapse
Affiliation(s)
- Jia Tang
- Graduate School of Xinjiang Medical University, Urumqi, China
| | - Zhenguang Zhong
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Muyesai Nijiati
- Xinjiang Emergency Center, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Changdong Wu
- Xinjiang Emergency Center, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China
| |
Collapse
|
10
|
Linz MO, Lorincz-Comi N, Kuwatch AA, Cooper GS. Patient Decisions Regarding Rescheduling Colonoscopies Postponed Due to the COVID-19 Pandemic. Dig Dis Sci 2023; 68:4339-4349. [PMID: 37794293 DOI: 10.1007/s10620-023-08119-5] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 09/19/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND Due to the COVID-19 pandemic, elective colonoscopies were postponed in Ohio from 3/17/2020 to 5/1/2020. When the ban was lifted, canceled patients determined whether to reschedule their colonoscopy in the midst of the ongoing pandemic. AIMS We aim to determine whether demographic, colorectal cancer (CRC) risk, and COVID-19 morbidity and mortality risk factors are associated with rescheduling of colonoscopies canceled by the COVID-19 pandemic. METHODS A medical record review of 420 participants ages 40-74 at a midwestern academic health system with elective colonoscopies canceled from 3/17/2020 to 5/1/2020 due to the COVID-19 pandemic was performed. RESULTS More than half of participants (71.0%) rescheduled their colonoscopy within the next 8 months. Indication for colonoscopy being 'surveillance following adenoma', colonoscopy ordered by primary care provider rather than gastroenterologist, and dyslipidemia were independently associated with rescheduling colonoscopy. Higher body mass index, indication for colonoscopy being simply 'screening for CRC,' and stool testing were associated with not rescheduling. Diagnoses associated with colorectal cancer risk such as adenomas, personal or family history of colorectal cancer, and inflammatory bowel disease were not associated with rescheduling, nor were other comorbidities associated with increased COVID-19 severity. 4.5% (19/420) opted for stool fecal immunochemical test or Cologuard testing. CONCLUSIONS Most patients rescheduled their colonoscopy despite the risk of virus exposure, suggesting that concern of missed colorectal cancer diagnosis outweighed coronavirus concerns. Patient trust in referring providers may be important for rescheduling, and colonoscopy indications were independently associated with rescheduling status.
Collapse
Affiliation(s)
- Marguerite O Linz
- Digestive Health Research Institute, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH, 44106-5066, USA
- Comprehensive Cancer Center (GSC), Case Western Reserve University School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106-5066, USA
| | - Noah Lorincz-Comi
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, 10900 Euclid Ave., Cleveland, OH, 44106-5066, USA
| | - Abigail A Kuwatch
- University Hospitals Quality Care Network, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106-5066, USA
| | - Gregory S Cooper
- Digestive Health Research Institute, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH, 44106-5066, USA.
- Comprehensive Cancer Center (GSC), Case Western Reserve University School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106-5066, USA.
| |
Collapse
|
11
|
Wang Z, Zhang N, Liu J, Liu J. Predicting micropapillary or solid pattern of lung adenocarcinoma with CT-based radiomics, conventional radiographic and clinical features. Respir Res 2023; 24:282. [PMID: 37964254 PMCID: PMC10647174 DOI: 10.1186/s12931-023-02592-2] [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: 11/01/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND To build prediction models with radiomics features, clinical/conventional radiographic signs and combined scores for the discrimination of micropapillary or solid subtypes (high-risk subtypes) of lung adenocarcinoma. METHODS This retrospective study enrolled 351 patients with and without high-risk subtypes. Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation was performed to determine the optimal features of radiomics model. Missing clinical data were imputed by Multiple Imputation with Chain Equations (MICE). Clinical model with radiographic signs was built and scores of both models were integrated to establish combined model. Receiver operating characteristics (ROC) curves, area under ROC curves and decision curve analysis (DCA) were plotted to evaluate the model performance and clinical application. RESULTS Stratified splitting allocated 246 patients into training set. MICE for missing values obtained complete and unbiased data for the following analysis. Ninety radiomic features and four clinical/conventional radiographic signs were used to predict the high-risk subtypes. The radiomic model, clinical model and combined model achieved AUCs of 0.863 (95%CI: 0.817-0.909), 0.771 (95%CI: 0.713-0.713) and 0.872 (95%CI: 0.829-0.916) in the training set, and 0.849 (95%CI: 0.774-0.924), 0.778 (95%CI: 0.687-0.868) and 0.853 (95%CI: 0.782-0.925) in the test set. Decision curve showed that the radiomic and combined models were more clinically useful when the threshold reached 37.5%. CONCLUSIONS Radiomics features could facilitate the prediction of subtypes of lung adenocarcinoma. A simple combination of radiomics and clinical scores generated a robust model with high performance for the discrimination of micropapillary or solid subtype of lung adenocarcinoma.
Collapse
Affiliation(s)
- Zhe Wang
- Hebei Medical University Fourth Hospital, Thoracic Surgery. 12 Jiankang Road, Shijiazhuang, China
| | - Ning Zhang
- Department of Radiology, Hebei Medical University Fourth Hospital, 12 Jiankang Road, Shijiazhuang, China
| | - Junhong Liu
- Hebei Medical University Fourth Hospital, Thoracic Surgery. 12 Jiankang Road, Shijiazhuang, China
| | - Junfeng Liu
- Hebei Medical University Fourth Hospital, Thoracic Surgery. 12 Jiankang Road, Shijiazhuang, China.
| |
Collapse
|
12
|
Zheng R, Qian S, Shi Y, Lou C, Xu H, Pan J. Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database. Cardiovasc Diabetol 2023; 22:307. [PMID: 37940931 PMCID: PMC10634031 DOI: 10.1186/s12933-023-02041-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 10/21/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND This study aimed to explore the association between the triglyceride-glucose (TyG) index and the risk of in-hospital mortality in critically ill patients with sepsis. METHODS This was a retrospective observational cohort study and data were obtained from the Medical Information Mart for Intensive Care-IV (MIMIC IV2.2) database. The participants were grouped into three groups according to the TyG index tertiles. The primary outcome was in-hospital all-cause mortality. Multivariable logistics proportional regression analysis and restricted cubic spline regression was used to evaluate the association between the TyG index and in-hospital mortality in patients with sepsis. In sensitivity analysis, the feature importance of the TyG index was initially determined using machine learning algorithms and subgroup analysis based on different subgroups was also performed. RESULTS 1,257 patients (56.88% men) were included in the study. The in-hospital, 28-day and intensive care unit (ICU) mortality were 21.40%, 26.17%, and 15.43% respectively. Multivariate logistics regression analysis showed that the TyG index was independently associated with an elevated risk of in-hospital mortality (OR 1.440 [95% CI 1.106-1.875]; P = 0.00673), 28-day mortality (OR 1.391; [95% CI 1.52-1.678]; P = 0.01414) and ICU mortality (OR 1.597; [95% CI 1.188-2.147]; P = 0.00266). The restricted cubic spline regression model revealed that the risks of in-hospital, 28-day, and ICU mortality increased linearly with increasing TyG index. Sensitivity analysis indicate that the effect size and direction in different subgroups are consistent, the results is stability. Additionally, the machine learning results suggest that TyG index is an important feature for the outcomes of sepsis. CONCLUSION Our study indicates that a high TyG index is associated with an increased in-hospital mortality in critically ill sepsis patients. Larger prospective studies are required to confirm these findings.
Collapse
Affiliation(s)
- Rui Zheng
- Department of Critical Care Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Songzan Qian
- Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Yiyi Shi
- Department of Anesthesiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
| | - Chen Lou
- School of the First Clinical Medical Sciences, Wenzhou Medical University, Wenzhou, 325000, China
| | - Honglei Xu
- Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
| | - Jingye Pan
- Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
- Key Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang Provincial, Wenzhou, 325000, Zhejiang, People's Republic of China.
- Zhejiang Engineering Research Center for Hospital Emergency and Process Digitization, Wenzhou, 325000, Zhejiang, China.
| |
Collapse
|
13
|
Feng J, Wang Q, Zhang Y. Ideal vitamin D and handgrip strength counteracts the risk effect of APOE genotype on dementia: a population-based longitudinal study. J Transl Med 2023; 21:355. [PMID: 37246226 DOI: 10.1186/s12967-023-04195-3] [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: 01/27/2023] [Accepted: 05/14/2023] [Indexed: 05/30/2023] Open
Abstract
BACKGROUND Higher vitamin D concentrations and grip strength contribute to lower individual-level risk of dementia, while apolipoprotein 4 (APOE e4) genotype carries increases dementia risk, but whether combination of ideal vitamin D and grip strength counteracts the risk effect of dementia related to APOE e4 genotype remains unclear. We aimed to investigate the interactions between vitamin D/grip strength and APOE e4 genotype and their association with dementia. METHODS The UK Biobank cohort comprised 165,688 dementia-free participants (aged at least 60 years) for the dementia analysis. Dementia was ascertained using hospital inpatient, mortality, and self-reported data until 2021. Vitamin D and grip strength were collected at baseline and divided into tertiles. APOE genotype was coded as APOE e4 non-carries and APOE e4 carries. Data were analyzed using Cox proportional hazard models and restricted cubic regression splines, with adjusted for known confounders. RESULTS Over the follow-up (median: 12.0 years), 3917 participants developed dementia. In women and men, respectively, compared with to the lowest tertile of vitamin D, the HRs (95% CIs) of dementia were lower in the middle [0.86 (0.76-0.97)/0.80 (0.72-0.90)] and the highest tertile [0.81 (0.72-0.90)/0.73 (0.66-0.81)]. Tertiles of grip strength showed similar patterns. In women and men, respectively, participants who had both highest tertile of vitamin D and grip strength was associated with a lower risk of dementia compared to those with both lowest tertile of these two exposures among APOE e4 genotype carries (HR = 0.56, 95% CI 0.42-0.76, and HR = 0.48, 95% CI 0.36-0.64) and APOE e4 genotype non-carries (HR = 0.56, 95% CI 0.38-0.81, and HR = 0.34, 95% CI 0.24-0.47). There were significant additive interactions between lower vitamin D/grip strength and APOE e4 genotype on dementia among women and men. CONCLUSIONS Higher vitamin D and grip strength were associated with a lower risk of dementia, and seemed to halve the adverse effects of APOE e4 genotype on dementia. Our findings suggested that vitamin D and grip strength may be imperative for estimating the risks of dementia, especially among APOE e4 genotype carries.
Collapse
Affiliation(s)
- Jiangtao Feng
- Department of Orthopedics, Tianjin NanKai Hospital, Changjiang Road 6, Tianjin, 300100, China
- Department of Orthopedics, Integrated Chinese and Western Medicine Hospital, Tianjin University, Changjiang Road 6, Tianjin, 300100, China
| | - Qi Wang
- Department of Orthopedics, Tianjin NanKai Hospital, Changjiang Road 6, Tianjin, 300100, China
- Department of Orthopedics, Integrated Chinese and Western Medicine Hospital, Tianjin University, Changjiang Road 6, Tianjin, 300100, China
| | - Yuan Zhang
- Department of Orthopedics, Tianjin NanKai Hospital, Changjiang Road 6, Tianjin, 300100, China.
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- School of Public Health, Tianjin Medical University, Tianjin, 300070, China.
| |
Collapse
|
14
|
Liang Z, Yue S, Zhong J, Wu J, Chen C. Associations of systolic blood pressure and in-hospital mortality in critically ill patients with acute kidney injury. Int Urol Nephrol 2023:10.1007/s11255-023-03510-7. [PMID: 36840802 DOI: 10.1007/s11255-023-03510-7] [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: 11/08/2022] [Accepted: 02/06/2023] [Indexed: 02/26/2023]
Abstract
PURPOSE Although systolic blood pressure (SBP) is associated with acute renal injury (AKI), the relationship between baseline SBP and prognosis in critically ill patients with AKI is unclear. We aimed to assess the linearity and profile of the relationship between SBP at intensive care unit (ICU) admission and in-hospital mortality in these patients. METHODS Data of AKI patients in the ICU settings were extracted from the Medical Information Mart for Intensive Care III database. The association between seven SBP categories (< 100, 100-109, 110-119, 120-129, 130-139, 140-149, and ≥ 150 mmHg) and all-cause in-hospital mortality was assessed by Cox proportional hazard models. Restricted cubic spline analysis for the multivariate Cox model was performed to explore the shape of the relationship between SBP and mortality. RESULTS A total of 24,202 patients with AKI were included in this study. A typically U-shaped relationship was found between SBP at admission and in-hospital mortality. Among all SBP categories, the lowest risk of death was observed in patients with SBP around 110-119 mmHg, whereas the highest was noted in patients with extremely low SBP (< 100 mmHg), followed by those with extremely high SBP (≥ 150 mmHg). SBP showed a significant interaction with vasopressor use and AKI stage in relation to the risk of in-hospital mortality. CONCLUSIONS SBP upon admission showed a non-linear association with all-cause in-hospital mortality in critically ill patients with AKI. Patients with low or high SBP show an increased risk of mortality compared to patients with normal SBP.
Collapse
Affiliation(s)
- Zheng Liang
- The First Clinical Medical College of Jinan University, Guangzhou, 510632, China.,Department of Vasculocardiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, China
| | - Suru Yue
- Clinical Research Service Center, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, Guangdong, China
| | - Jianfeng Zhong
- Department of Vasculocardiology, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, China
| | - Jiayuan Wu
- Clinical Research Service Center, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, Guangdong, China.
| | - Can Chen
- The First Clinical Medical College of Jinan University, Guangzhou, 510632, China.
| |
Collapse
|
15
|
Abdul Rahman H, Ottom MA, Dinov ID. Machine learning-based colorectal cancer prediction using global dietary data. BMC Cancer 2023; 23:144. [PMID: 36765299 PMCID: PMC9921106 DOI: 10.1186/s12885-023-10587-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/27/2023] [Indexed: 02/12/2023] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Active health screening for CRC yielded detection of an increasingly younger adults. However, current machine learning algorithms that are trained using older adults and smaller datasets, may not perform well in practice for large populations. AIM To evaluate machine learning algorithms using large datasets accounting for both younger and older adults from multiple regions and diverse sociodemographics. METHODS A large dataset including 109,343 participants in a dietary-based colorectal cancer ase study from Canada, India, Italy, South Korea, Mexico, Sweden, and the United States was collected by the Center for Disease Control and Prevention. This global dietary database was augmented with other publicly accessible information from multiple sources. Nine supervised and unsupervised machine learning algorithms were evaluated on the aggregated dataset. RESULTS Both supervised and unsupervised models performed well in predicting CRC and non-CRC phenotypes. A prediction model based on an artificial neural network (ANN) was found to be the optimal algorithm with CRC misclassification of 1% and non-CRC misclassification of 3%. CONCLUSIONS ANN models trained on large heterogeneous datasets may be applicable for both younger and older adults. Such models provide a solid foundation for building effective clinical decision support systems assisting healthcare providers in dietary-related, non-invasive screening that can be applied in large studies. Using optimal algorithms coupled with high compliance to cancer screening is expected to significantly improve early diagnoses and boost the success rate of timely and appropriate cancer interventions.
Collapse
Affiliation(s)
- Hanif Abdul Rahman
- University of Michigan, Ann Arbor, USA. .,PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, , Bandar Seri Begawan, Brunei.
| | - Mohammad Ashraf Ottom
- grid.214458.e0000000086837370University of Michigan, Ann Arbor, USA ,grid.14440.350000 0004 0622 5497Yarmouk University, Irbid, Jordan
| | - Ivo D. Dinov
- grid.214458.e0000000086837370University of Michigan, Ann Arbor, USA
| |
Collapse
|
16
|
Techniques for mesoappendix transection and appendix resection: insights from the ESTES SnapAppy study. Eur J Trauma Emerg Surg 2023; 49:17-32. [PMID: 36693948 PMCID: PMC9925585 DOI: 10.1007/s00068-022-02191-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 11/27/2022] [Indexed: 01/25/2023]
Abstract
INTRODUCTION Surgically managed appendicitis exhibits great heterogeneity in techniques for mesoappendix transection and appendix amputation from its base. It is unclear whether a particular surgical technique provides outcome benefit or reduces complications. MATERIAL AND METHODS We undertook a pre-specified subgroup analysis of all patients who underwent laparoscopic appendectomy at index admission during SnapAppy (ClinicalTrials.gov Registration: NCT04365491). We collected routine, anonymized observational data regarding surgical technique, patient demographics and indices of disease severity, without change to clinical care pathway or usual surgeon preference. Outcome measures of interest were the incidence of complications, unplanned reoperation, readmission, admission to the ICU, death, hospital length of stay, and procedure duration. We used Poisson regression models with robust standard errors to calculate incident rate ratios (IRRs) and 95% confidence intervals (CIs). RESULTS Three-thousand seven hundred sixty-eight consecutive adult patients, included from 71 centers in 14 countries, were followed up from date of admission for 90 days. The mesoappendix was divided hemostatically using electrocautery in 1564(69.4%) and an energy device in 688(30.5%). The appendix was amputated by division of its base between looped ligatures in 1379(37.0%), with a stapler in 1421(38.1%) and between clips in 929(24.9%). The technique for securely dividing the appendix at its base in acutely inflamed (AAST Grade 1) appendicitis was equally divided between division between looped ligatures, clips and stapled transection. However, the technique used differed in complicated appendicitis (AAST Grade 2 +) compared with uncomplicated (Grade 1), with a shift toward transection of the appendix base by stapler (58% vs. 38%; p < 0.001). While no statistical difference in outcomes could be detected between different techniques for division of appendix base, decreased risk of any [adjusted IRR (95% CI): 0.58 (0.41-0.82), p = 0.002] and severe [adjusted IRR (95% CI): 0.33 (0.11-0.96), p = 0.045] complications could be detected when using energy devices. CONCLUSIONS Safe mesoappendix transection and appendix resection are accomplished using heterogeneous techniques. Technique selection for both mesoappendix transection and appendix resection correlates with AAST grade. Higher grade led to more ultrasonic tissue transection and stapled appendix resection. Higher AAST appendicitis grade also correlated with infection-related complication occurrence. Despite the overall well-tolerated heterogeneity of approaches to acute appendicitis, increasing disease acuity or complexity appears to encourage homogeneity of intraoperative surgical technique toward advanced adjuncts.
Collapse
|
17
|
Lu X, Kang H, Zhou D, Li Q. Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning. Sci Rep 2022; 12:22621. [PMID: 36587113 PMCID: PMC9805434 DOI: 10.1038/s41598-022-27134-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 12/26/2022] [Indexed: 01/01/2023] Open
Abstract
Sepsis-associated encephalopathy (SAE) is a major complication of sepsis and is associated with high mortality and poor long-term prognosis. The purpose of this study is to develop interpretable machine learning models to predict the occurrence of SAE after ICU admission and implement the individual prediction and analysis. Patients with sepsis admitted to ICU were included. SAE was diagnosed as glasgow coma score (GCS) less than 15. Statistical analysis at baseline was performed between SAE and non-SAE. Six machine learning classifiers were employed to predict the occurrence of SAE, and the adjustment of model super parameters was performed by using Bayesian optimization method. Finally, the optimal algorithm was selected according to the prediction efficiency. In addition, professional physicians were invited to evaluate our model prediction results for further quantitative assessment of the model interpretability. The preliminary analysis of variance showed significant differences in the incidence of SAE among patients with pathogen infection. There were significant differences in physical indicators like respiratory rate, temperature, SpO2 and mean arterial pressure (P < 0.001). In addition, the laboratory results were also significantly different. The optimal classification model (XGBoost) indicated that the best risk factors (cut-off points) were creatinine (1.1 mg/dl), mean respiratory rate (18), pH (7.38), age (72), chlorine (101 mmol/L), sodium (138.5 k/ul), SAPSII score (23), platelet count (160), and phosphorus (2.4 and 5.0 mg/dL). The ranked features derived from the best model (AUC is 0.8837) were mechanical ventilation, duration of mechanical ventilation, phosphorus, SOFA score, and vasopressin usage. The SAE risk prediction model based on XGBoost created here can make very accurate predictions using simple indicators and support the visual explanation. The interpretable model was effectively evaluated by professional physicians and can help them predict the occurrence of SAE more intuitively.
Collapse
Affiliation(s)
- Xiao Lu
- grid.43555.320000 0000 8841 6246Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, 100081 China
| | - Hongyu Kang
- grid.43555.320000 0000 8841 6246Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, 100081 China ,grid.506261.60000 0001 0706 7839Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100020 China
| | - Dawei Zhou
- grid.24696.3f0000 0004 0369 153XDepartment of Critical Care Medicine, Beijing Tongren Hospital, Capital Medical University, Beijing, 100005 China
| | - Qin Li
- grid.43555.320000 0000 8841 6246Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, 100081 China
| |
Collapse
|
18
|
Zhang Y, Yang R, Hou Y, Chen Y, Li S, Wang Y, Yang H. Association of cardiovascular health with diabetic complications, all-cause mortality, and life expectancy among people with type 2 diabetes. Diabetol Metab Syndr 2022; 14:158. [PMID: 36307875 PMCID: PMC9615235 DOI: 10.1186/s13098-022-00934-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 10/21/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND We aimed to assess the impact of healthy cardiovascular health (CVH) on diabetic complications, mortality, and life expectancy among people with type 2 diabetes and to explore whether inflammation marker mediate these associations. METHODS This prospective cohort study included 33,236 participants (aged 40-72) with type 2 diabetes from the UK Biobank with annual follow-up from 2006 to 2010 to 2020. Type 2 diabetes was ascertained from self-report, glycated hemoglobin ≥ 6.5%, hospital inpatient registry, or glucose-lowering medication use. Information on mortality was derived from the national death registry. Favorable CVH metrics consisted of non-smoker, regular physical activity, a healthy diet, non-overweight, untreated resting blood pressure < 120/<80 mm Hg, and untreated total cholesterol < 200 mg/dL. Participants were categorized into three groups according to the number of favorable CVH metrics: unfavorable (0 or 1); intermediate (any 2 or 3); and favorable (4 or more). Inflammation marker, as measured by C-reactive protein (CRP), was assessed at baseline and categorized as low (≤ 3 mg/L) and high (> 3 mg/L). Data were analyzed using Cox regression models, flexible parametric survival models, and mediation models. RESULTS During the follow-up (median: 11.7 years), 3133 (9.4%) cases of diabetes complications and 4701 (14.1%) deaths occurred. Compared to unfavorable CVH, favorable CVH was associated with a reduced risk of diabetes complications (HR, 0.35; 95% CI, 0.26-0.47) and all-cause mortality (HR, 0.53; 95% CI, 0.43-0.65). In participants with unfavorable CVH, life expectancy at age 45 had a significantly reduction of 7.20 (95% CI, 5.48-8.92) years compared to those with a favorable CVH. Among people with type 2 diabetes, the proportions of diabetes complications and all-cause mortality that would be reduced by promoting the favorable CVH was 61.5% and 39.1%, respectively. CRP level mediated 14.3% and 29.7% of the associations between CVH and diabetic complication and all-cause mortality, respectively. CONCLUSION A favorable CVH was associated with lower risk of diabetes complications and mortality risk, and was associated with a longer life expectancy among people with type 2 diabetes. This association may be in part accounted for by inflammatory processes. Our findings highlight the importance of favorable CVH for the prevention of diabetic complications and all-cause mortality among people with type 2 diabetes, and underscores the need to monitor inflammation among people with unfavorable CVH.
Collapse
Affiliation(s)
- Yuan Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Rongrong Yang
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yabing Hou
- Yanjing medical college, Capital Medical University, Beijing, China
| | - Yanchun Chen
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shu Li
- School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China
- The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Qixiangtai Road 22, Heping District, Tianjin, 300070, China.
| |
Collapse
|
19
|
Lee DU, Hastie DJ, Lee KJ, Fan GH, Addonizio EA, Han J, Suh J, Karagozian R. The clinical impact of frailty on the postoperative outcomes of patients undergoing appendectomy: propensity score-matched analysis of 2011-2017 US hospitals. Aging Clin Exp Res 2022; 34:2057-2070. [PMID: 35723857 DOI: 10.1007/s40520-022-02163-3] [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: 02/28/2022] [Accepted: 05/19/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND The presence of clinical frailty can pose an escalated risk toward surgical outcomes including in cases that involve minimally invasive procedures. Given this premise, we evaluate the effects of frailty on post-appendectomy outcomes using a national in-hospital registry. METHODS 2011-2017 National Inpatient Sample was used to isolate inpatient appendectomy cases; the population as stratified using Johns Hopkins ACG clinical frailty, expressed as either binary or ternary (prefrailty, frailty, and without frailty) indicators. The controls were matched to frailty-present groups using propensity score matching and compared to various endpoints, including mortality, length of stay (LOS), hospitalization costs, and postoperative complications. RESULTS Post-match, there were 11,758 with and without frailty per binary; and 1236 frail, 10,522 pre-frail with respective equal number controls per ternary indicator. Using binary term, frail patients had higher mortality (4.22 vs 1.49% OR 2.92 95%CI 2.45-3.47), LOS (14.3 vs 5.35d p < 0.001), and costs ($160,700 vs $64,141 p < 0.001). In multivariate, frail patients had higher mortality (aOR 2.77 95%CI 2.32-3.31), as well as higher rates of postoperative complications. Using ternary term, frail patients had higher mortality (5.02 vs 2.27% OR 2.28 95%CI 1.45-3.59), LOS (18.9 vs 5.66 day p < 0.001) and costs ($200,517 vs $66,193 p < 0.001). In multivariate, frail patients had higher mortality (aOR 2.16 95%CI 1.35-3.43) and complications. Those with pre-frailty had higher mortality (4.12 vs 1.47% OR 2.88 95%CI 2.39-3.46), LOS (13.8 vs 5.34 day p < 0.001) and costs ($156,022 vs $63,772 p < 0.001). In multivariate, pre-frailty patients had higher mortality (aOR 2.79 95%CI 2.31-3.37) and complications. CONCLUSIONS Frailty and prefrailty (using the ternary indicator) are associated with increased postoperative mortality and complication in patients who undergo appendectomy; given this finding, it is imperative that these vulnerable patients are identified early in the preoperative phase and are provided risk-modifying measures to ameliorate risks and optimize outcomes.
Collapse
Affiliation(s)
- David Uihwan Lee
- Division of Gastroenterology and Hepatology, University of Maryland, 22 S Greene St, Baltimore, MD, 21201, USA.
| | - David Jeffrey Hastie
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - Ki Jung Lee
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - Gregory Hongyuan Fan
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - Elyse Ann Addonizio
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - John Han
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - Julie Suh
- Liver Center, Division of Gastroenterology, Tufts Medical Center, 800 Washington Street, Boston, MA, 02111, USA
| | - Raffi Karagozian
- Division of Gastroenterology and Hepatology, University of Maryland, 22 S Greene St, Baltimore, MD, 21201, USA
| |
Collapse
|
20
|
Shi Y, Men J, Sun H, Tan J. The Identification and Analysis of MicroRNAs Combined Biomarkers for Hepatocellular Carcinoma Diagnosis. Med Chem 2022; 18:1073-1085. [PMID: 35379158 DOI: 10.2174/1573406418666220404084532] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/22/2021] [Accepted: 01/24/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is a common malignant tumor with high morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs) were novel biomarkers with higher accuracy. OBJECTIVE We aimed to identify combinatorial biomarkers of miRNAs to construct a classification model for the diagnosis of HCC. METHOD The mature miRNAs expression profile data of six cancers (liver, lung, gastric, breast, prostate and colon) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database with accession number GSE36915, GSE29250, GSE99417, GSE41970, GSE64333 and GSE35982. The messenger RNA (mRNA) expression profile data of these six cancers were obtained from TCGA. Three R software packages, student's t-test and a normalized fold-change method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs). Using all combinations of obtained HCC- specific DEMs as input features, we construct a classification model by support vector machine searching for the optimal combination. Furthermore, target genes prediction was conducted on the miRWalk 2.0 website to obtain differentially expressed mRNAs (DEmRNAs), and KEGG pathway enrichment was analyzed on the DAVID website. RESULTS The optimal combination consisted of four miRNAs (hsa-miR-130a-3p, hsa-miR-450b-5p, hsa-miR-136-5p and hsa-miR-24-1-5p), of which the last one has not been currently reported to be relevant to HCC. The target genes of hsa-miR-24-1-5p (CDC7, ACACA, CTNNA1, and NF2) were involved in the cell cycle, AMPK signaling pathway, Hippo signaling pathway and insulin signaling pathway, which affect the proliferation, metastasis, and apoptosis of cancer cells. Moreover, the area under the receiver operating characteristic curves of the four miRNAs were all higher than 0.85. CONCLUSION These results suggest that the miRNAs combined biomarkers were reliable for the diagnosis of HCC. Hsa-miR-24-1-5p was a novel biomarker for HCC diagnosis identified in this study.
Collapse
Affiliation(s)
- Yi Shi
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jingrui Men
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Hongliang Sun
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Jianjun Tan
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| |
Collapse
|
21
|
External Validation of a Risk Score for Daily Prediction of Atrial Fibrillation among Critically Ill Patients with Sepsis. Ann Am Thorac Soc 2022; 19:697-701. [PMID: 34914569 PMCID: PMC8996280 DOI: 10.1513/annalsats.202107-787rl] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
|
22
|
Explainable machine learning model for predicting spontaneous bacterial peritonitis in cirrhotic patients with ascites. Sci Rep 2021; 11:21639. [PMID: 34737270 PMCID: PMC8569162 DOI: 10.1038/s41598-021-00218-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 09/21/2021] [Indexed: 11/12/2022] Open
Abstract
Spontaneous bacterial peritonitis (SBP) is a life-threatening complication in patients with cirrhosis. We aimed to develop an explainable machine learning model to achieve the early prediction and outcome interpretation of SBP. We used CatBoost algorithm to construct MODEL-1 with 46 variables. After dimensionality reduction, we constructed MODEL-2. We calculated and compared the sensitivity and negative predictive value (NPV) of MODEL-1 and MODEL-2. Finally, we used the SHAP (SHapley Additive exPlanations) method to provide insights into the model’s outcome or prediction. MODEL-2 (AUROC: 0.822; 95% confidence interval [CI] 0.783–0.856), liked MODEL-1 (AUROC: 0.822; 95% CI 0.784–0.856), could well predict the risk of SBP in cirrhotic ascites patients. The 6 most influential predictive variables were total protein, C-reactive protein, prothrombin activity, cholinesterase, lymphocyte ratio and apolipoprotein A1. For binary classifier, the sensitivity and NPV of MODEL-1 were 0.894 and 0.885, respectively, while for MODEL-2 they were 0.927 and 0.904, respectively. We applied CatBoost algorithm to establish a practical and explainable prediction model for risk of SBP in cirrhotic patients with ascites. We also identified 6 important variables closely related to the occurrence of SBP.
Collapse
|
23
|
Clinical impact of visually assessed right ventricular dysfunction in patients with septic shock. Sci Rep 2021; 11:18823. [PMID: 34552188 PMCID: PMC8458318 DOI: 10.1038/s41598-021-98397-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 09/06/2021] [Indexed: 12/18/2022] Open
Abstract
We retrospectively analyzed data from the Medical Information Mart for Intensive Care-III critical care database to determine whether visually-assessed right ventricular (RV) dysfunction was associated with clinical outcomes in septic shock patients. Associations between visually-assessed RV dysfunction by echocardiography and in-hospital mortality, lethal arrhythmia, and hemodynamic indicators to determine the prognostic value of RV dysfunction in patients with septic shock were analyzed. Propensity score analysis showed RV dysfunction was associated with increased risk of in-hospital death in patients with septic shock (adjusted odds ratio [OR] 2.15; 95% confidence interval [CI] 1.99–2.32; P < 0.001). In multivariate logistic regression analysis, RV dysfunction was associated with in-hospital death (OR 2.19; 95% CI 1.91–2.53; P < 0.001), lethal arrhythmia (OR 2.19; 95% CI 1.34–3.57; P < 0.001), and tendency for increased blood lactate levels (OR 1.31; 95% CI 1.14–1.50; P < 0.001) independent of left ventricular (LV) dysfunction. RV dysfunction was associated with lower cardiac output, pulmonary artery pressure index, and RV stroke work index. In patients with septic shock, visually-assessed RV dysfunction was associated with in-hospital mortality, lethal arrhythmia, and circulatory insufficiency independent of LV dysfunction. Visual assessment of RV dysfunction using echocardiography might help to identify the short-term prognosis of patients with septic shock by reflecting hemodynamic status.
Collapse
|
24
|
Kasugai D, Ozaki M, Nishida K, Goto Y, Takahashi K, Matsui S, Matsuda N. Relative platelet reductions provide better pathophysiologic signatures of coagulopathies in sepsis. Sci Rep 2021; 11:14033. [PMID: 34234257 PMCID: PMC8263719 DOI: 10.1038/s41598-021-93635-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/22/2021] [Indexed: 11/25/2022] Open
Abstract
In sepsis-associated coagulopathies and disseminated intravascular coagulation, relative platelet reductions may reflect coagulopathy severity. However, limited evidence supports their clinical significance and most sepsis-associated coagulopathy criteria focus on the absolute platelet counts. To estimate the impact of relative platelet reductions and absolute platelet counts on sepsis outcomes. A multicenter retrospective observational study was performed using the eICU Collaborative Research Database, comprising 335 intensive care units (ICUs) in the United States. Patients with sepsis and an ICU stay > 2 days were included. Estimated effects of relative platelet reductions and absolute platelet counts on mortality and coagulopathy-related complications were evaluated. Overall, 26,176 patients were included. Multivariate mixed-effect logistic regression analysis revealed marked in-hospital mortality risk with larger platelet reductions between days one and two, independent from the resultant absolute platelet counts. The adjusted odds ratio (OR) [95% confidence intervals (CI)] for in-hospital mortality was 1.28[1.23–1.32], 1.86[1.75–1.97], 2.99[2.66–3.36], and 6.05[4.40–8.31] for 20–40%, 40–60%, 60–80%, and > 80% reductions, respectively, when compared with a < 20% decrease in platelets (P < 0.001 for each). In the multivariate logistic regression analysis, platelet reductions ≥ 11% and platelet counts ≤ 100,000/μL on day 2 were associated with high coagulopathy-related complications (OR [95%CI], 2.03 and 1.18; P < 0.001 and P < 0.001), while only platelet reduction was associated with thromboembolic complications (OR [95%CI], 1.43 [1.03–1.98], P < 0.001). The magnitude of platelet reductions represent mortality risk and provides a better signature of coagulopathies in sepsis; therefore, it is a plausible criterion for sepsis-associated coagulopathies.
Collapse
Affiliation(s)
- Daisuke Kasugai
- Department of Emergency and Critical Care Medicine, Nagoya University Graduate School of Medicine, Tsurumai-cho 64, Showa-ku, Nagoya, Aichi, Japan.
| | - Masayuki Ozaki
- Department of Emergency and Critical Care Medicine, Nagoya University Graduate School of Medicine, Tsurumai-cho 64, Showa-ku, Nagoya, Aichi, Japan
| | - Kazuki Nishida
- Department of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yukari Goto
- Department of Emergency and Critical Care Medicine, Nagoya University Graduate School of Medicine, Tsurumai-cho 64, Showa-ku, Nagoya, Aichi, Japan
| | - Kunihiko Takahashi
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Shigeyuki Matsui
- Department of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Naoyuki Matsuda
- Department of Emergency and Critical Care Medicine, Nagoya University Graduate School of Medicine, Tsurumai-cho 64, Showa-ku, Nagoya, Aichi, Japan
| |
Collapse
|
25
|
Kuiper LM, Ikram MK, Kavousi M, Vernooij MW, Ikram MA, Bos D. C-factor: a summary measure for systemic arterial calcifications. BMC Cardiovasc Disord 2021; 21:317. [PMID: 34187369 PMCID: PMC8243490 DOI: 10.1186/s12872-021-02126-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/15/2021] [Indexed: 11/24/2022] Open
Abstract
Background Arterial calcification, the hallmark of arteriosclerosis, has a widespread distribution in the human body with only moderate correlation among sites. Hitherto, a single measure capturing the systemic burden of arterial calcification was lacking. In this paper, we propose the C-factor as an overall measure of calcification burden. Methods To quantify calcification in the coronary arteries, aortic arch, extra- and intracranial carotid arteries, and vertebrobasilar arteries, 2384 Rotterdam Study participants underwent cardiac and extra-cardiac non-enhanced CT. We performed principal component analyses on the calcification volumes of all twenty-six possible combinations of these vessel beds. Each analysis’ first principal component represents the C-factor. Subsequently, we determined the correlation between the C-factor derived from all vessel beds and the other C-factors with intraclass correlation coefficient (ICC) analyses. Finally, we examined the association of the C-factor and calcification in the separate vessel beds with cardiovascular, non-cardiovascular, and overall mortality using Cox–regression analyses. Results The ICCs ranged from 0.80 to 0.99. Larger calcification volumes and a higher C-factor were all individually associated with higher risk of cardiovascular, non-cardiovascular, and overall mortality. When included simultaneously in a model, the C-factor was still associated with all three mortality types (adjusted hazard ratio per standard deviation increase (HR) > 1.52), whereas associations of the separate vessel beds with mortality attenuated substantially (HR < 1.26). Conclusions The C-factor summarizes the systemic component of arterial calcification on an individual level and appears robust among different combinations of vessel beds. Importantly, when mutually adjusted, the C-factor retains its strength of association with mortality while the site-specific associations attenuate. Supplementary Information The online version contains supplementary material available at 10.1186/s12872-021-02126-y.
Collapse
Affiliation(s)
- Lieke M Kuiper
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - M Kamran Ikram
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Maryam Kavousi
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Daniel Bos
- Departments of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands. .,Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
| |
Collapse
|
26
|
Alaa AM, Gurdasani D, Harris AL, Rashbass J, van der Schaar M. Machine learning to guide the use of adjuvant therapies for breast cancer. NAT MACH INTELL 2021. [DOI: 10.1038/s42256-021-00353-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
27
|
Garcia MA, Rucci JM, Thai KK, Lu Y, Kipnis P, Go AS, Desai M, Bosch NA, Martinez A, Clancy H, Devis Y, Myers LC, Liu VX, Walkey AJ. Association Between Troponin I Levels During Sepsis and Post-Sepsis Cardiovascular Complications. Am J Respir Crit Care Med 2021; 204:557-565. [PMID: 34038701 DOI: 10.1164/rccm.202103-0613oc] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Sepsis commonly results in elevated serum troponin I levels and increased risk for post-sepsis cardiovascular complications; however, the association between troponin I level during sepsis and cardiovascular complications after sepsis is unclear. OBJECTIVES To evaluate the association between serum troponin levels during sepsis and 1-year post-sepsis cardiovascular risks. METHODS We included patients aged >40 years without a prior diagnosis of cardiovascular disease within 5-years, admitted with sepsis across 21 hospitals from 2011 to 2017. Peak serum troponin I levels during sepsis were grouped as normal (<0.04ng/mL) or tertiles of abnormal (>0.04 to <0.09ng/mL, >0.09 to <0.42ng/mL, or >0.42ng/mL). Multivariable adjusted, cause-specific, Cox proportional hazards models that treated death as a competing risk were used to assess associations between peak sepsis troponin I levels and a composite cardiovascular outcome (atherosclerotic cardiovascular disease, atrial fibrillation, and heart failure) in the year following sepsis. Models were adjusted for pre-sepsis and intra-sepsis factors considered potential confounders. MEASUREMENTS AND MAIN RESULTS Among 14,046 patients with troponin I measured during sepsis, 2,012 (14.3%) patients experienced the composite cardiovascular outcome in the year following sepsis hospitalization. Compared with patients with normal troponin levels, those with elevated troponins had increased risks of adverse cardiovascular events (adjusted Hazard Ratiotroponin 0.04-0.09=1.37 (95% CI 1.20-1.55), aHRtroponin 0.09-0.42=1.44 (95% CI 1.27-1.63), and aHRtroponin > 0.42=1.77 (95% CI 1.56-2.00)). CONCLUSIONS Among patients without pre-existing cardiovascular disease, troponin elevation during sepsis identified patients at increased risk for post-sepsis cardiovascular complications. Strategies to mitigate cardiovascular complications among this high-risk subset of patients is warranted.
Collapse
Affiliation(s)
- Michael A Garcia
- Boston University School of Medicine, 12259, Department of Medicine, Division of Pulmonary, Allergy, Sleep, and Critical Care, Boston, Massachusetts, United States;
| | - Justin M Rucci
- Boston University School of Medicine, 12259, Department of Medicine, Division of Pulmonary, Allergy, Sleep, and Critical Care, Boston, Massachusetts, United States
| | - Khanh K Thai
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Yun Lu
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Patricia Kipnis
- Kaiser Permanente Division of Research, 73265, Oakland, California, United States
| | - Alan S Go
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Manisha Desai
- Stanford University, 6429, Department of Medicine, Division of Biostatistics, Stanford, California, United States
| | | | - Adriana Martinez
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Heather Clancy
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Ycar Devis
- Boston University School of Medicine, 12259, Boston, Massachusetts, United States
| | - Laura C Myers
- Massachusetts General Hospital, 2348, Division of Pulmonary and Critical Care Medicine, Boston, Massachusetts, United States
| | - Vincent X Liu
- Kaiser Permanente, 6152, Division of Research, Oakland, California, United States
| | - Allan J Walkey
- Boston University School of Medicine, 12259, Pulmonary Center, Boston, Massachusetts, United States
| |
Collapse
|
28
|
Dufournet M, Moutet C, Achi S, Delphin-Combe F, Krolak-Salmon P, Dauphinot V. Proposition of a corrected measure of the Lawton instrumental activities of daily living score. BMC Geriatr 2021; 21:39. [PMID: 33430781 PMCID: PMC7802257 DOI: 10.1186/s12877-020-01995-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 12/29/2020] [Indexed: 11/18/2022] Open
Abstract
Background We aimed to propose a correction of the Lawton instrumental activity of daily living (IADL) score to take into account the possibility to have never done some activities, and measured its agreement and reliability with the usual IADL score. Methods A cross-sectional study was conducted in outpatients attending French memory clinics between 2014 and 2017. Lawton IADL, cognitive performance, diagnosis, neuropsychiatric symptoms, and sociodemographics characteristics were collected. A corrected IADL was calculated and its agreement with the usual IADL was assessed. Results The study included of 2391 patients (79.9 years old, 61.7% female). Based on the usual IADL, 36.9% of patients had never carried out at least one of the activities. This proportion reached 68.8% for men and 17.7% for women. Women had a mean IADL higher than men: 4.72 vs 3.49, this difference decreased when considering the corrected IADL: 4.82 vs 4.26 respectively. Based on Bland-Altman method, 93.5% of observations lied within the limits agreement. The ICC between the 2 scores was 0.98. The relationships between patients’ characteristics and the IADL scores were similar, regardless the usual or corrected version. Conclusions This corrected IADL score had an excellent degree of agreement with the usual version based the ICC. This simple correction could benefit both for the clinical practice by providing a more accurate description of the real clinical state of the patients allowing to manage them more precisely, and for research involving the evaluation of the functional abilities of patients.
Collapse
Affiliation(s)
- Marine Dufournet
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France
| | - Claire Moutet
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France
| | - Sarah Achi
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France
| | - Floriane Delphin-Combe
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France.,Research Clinic Centre Aging Brain Frailty (CRC - VCF), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France.,University Lyon 1, INSERM, U1028, UMR CNRS 5292, Research Centre of Neurosciences of Lyon, Lyon, France
| | - Virginie Dauphinot
- Clinical and Research Memory Centre of Lyon of Lyon (CMRR Lyon), Lyon Institute For Elderly (Institut du vieillissement I-Vie), Hospices civils de Lyon, Lyon, France. .,Hôpital des Charpennes, 27 avenue Gabriel Péri, 69 100, Villeurbanne, France.
| | | |
Collapse
|
29
|
Performance of a Severity Score on Admission Chest Radiography in Predicting Clinical Outcomes in Hospitalized Patients With Coronavirus Disease (COVID-19). AJR Am J Roentgenol 2020; 217:623-632. [PMID: 33112201 DOI: 10.2214/ajr.20.24801] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND. Chest radiographs (CXRs) are typically obtained early in patients admitted with coronavirus disease (COVID-19) and may help guide prognosis and initial management decisions. OBJECTIVE. The purpose of this study was to assess the performance of an admission CXR severity scoring system in predicting hospital outcomes in patients admitted with COVID-19. METHODS. This retrospective study included 240 patients (142 men, 98 women; median age, 65 [range, 50-80] years) admitted to the hospital from March 16 to April 13, 2020, with COVID-19 confirmed by real-time reverse-transcriptase polymerase chain reaction who underwent chest radiography within 24 hours of admission. Three attending chest radiologists and three radiology residents independently scored patients' admission CXRs using a 0- to 24-point composite scale (sum of scores that range from 0 to 3 for extent and severity of disease in upper and lower zones of left and right lungs). Interrater reliability of the score was assessed using the Kendall W coefficient. The mean score was obtained from the six readers' scores for further analyses. Demographic variables, clinical characteristics, and admission laboratory values were collected from electronic medical records. ROC analysis was performed to assess the association between CXR severity and mortality. Additional univariable and multivariable logistic regression models incorporating patient characteristics and laboratory values were tested for associations between CXR severity and clinical outcomes. RESULTS. Interrater reliability of CXR scores ranged from 0.687 to 0.737 for attending radiologists, from 0.653 to 0.762 for residents, and from 0.575 to 0.666 for all readers. A composite CXR score of 10 or higher on admission achieved 53.0% (35/66) sensitivity and 75.3% (131/174) specificity for predicting hospital mortality. Hospital mortality occurred in 44.9% (35/78) of patients with a high-risk admission CXR score (≥ 10) versus 19.1% (31/162) of patients with a low-risk CXR score (< 10) (p < .001). Admission composite CXR score was an independent predictor of death (odds ratio [OR], 1.17; 95% CI, 1.10-1.24; p < .001). composite CXR score was a univariable predictor of intubation (OR, 1.23; 95% CI, 1.12-1.34; p < .001) and continuous renal replacement therapy (CRRT) (OR, 1.15; 95% CI, 1.04-1.27; p = .007) but was not associated with these in multivariable models (p > .05). CONCLUSION. For patients admitted with COVID-19, an admission CXR severity score may help predict hospital mortality, intubation, and CRRT. CLINICAL IMPACT. CXR may assist risk assessment and clinical decision-making early in the course of COVID-19.
Collapse
|
30
|
Zhang Z, Ho KM, Gu H, Hong Y, Yu Y. Defining persistent critical illness based on growth trajectories in patients with sepsis. Crit Care 2020; 24:57. [PMID: 32070393 PMCID: PMC7029548 DOI: 10.1186/s13054-020-2768-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 02/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Persistent critical illness is common in critically ill patients and is associated with vast medical resource use and poor clinical outcomes. This study aimed to define when patients with sepsis would be stabilized and transitioned to persistent critical illness, and whether such transition time varies between latent classes of patients. METHODS This was a retrospective cohort study involving sepsis patients in the eICU Collaborative Research Database. Persistent critical illness was defined at the time when acute physiological characteristics were no longer more predictive of in-hospital mortality (i.e., vital status at hospital discharge) than antecedent characteristics. Latent growth mixture modeling was used to identify distinct trajectory classes by using Sequential Organ Failure Assessment score measured during intensive care unit stay as the outcome, and persistent critical illness transition time was explored in each latent class. RESULTS The mortality was 16.7% (3828/22,868) in the study cohort. Acute physiological model was no longer more predictive of in-hospital mortality than antecedent characteristics at 15 days after intensive care unit admission in the overall population. Only a minority of the study subjects (n = 643, 2.8%) developed persistent critical illness, but they accounted for 19% (15,834/83,125) and 10% (19,975/198,833) of the total intensive care unit and hospital bed-days, respectively. Five latent classes were identified. Classes 1 and 2 showed increasing Sequential Organ Failure Assessment score over time and transition to persistent critical illness occurred at 16 and 27 days, respectively. The remaining classes showed a steady decline in Sequential Organ Failure Assessment scores and the transition to persistent critical illness occurred between 6 and 8 days. Elevated urea-to-creatinine ratio was a good biochemical signature of persistent critical illness. CONCLUSIONS While persistent critical illness occurred in a minority of patients with sepsis, it consumed vast medical resources. The transition time differs substantially across latent classes, indicating that the allocation of medical resources should be tailored to different classes of patients.
Collapse
Affiliation(s)
- Zhongheng Zhang
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016 China
| | - Kwok M. Ho
- 0000 0004 1936 7910grid.1012.2Department of intensive care Medicine, Royal Perth Hospital, School of Population & Global Health, University of Western Australia, Crawley, Australia
| | - Hongqiu Gu
- 0000 0004 0369 153Xgrid.24696.3fChina National Clinical Research Center for Neurological Diseases; National Center for Healthcare Quality Management in Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, 10070 China
| | - Yucai Hong
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016 China
| | - Yunsong Yu
- 0000 0004 1759 700Xgrid.13402.34Department of Infectious Diseases, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang, 310016 Hangzhou China
- Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, Zhejiang, 310016 China
| |
Collapse
|
31
|
Zhang Z, Yao M, Ho KM, Hong Y. Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database. Sci Rep 2019; 9:13644. [PMID: 31541172 PMCID: PMC6754393 DOI: 10.1038/s41598-019-50178-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 09/05/2019] [Indexed: 02/07/2023] Open
Abstract
Cardiac arrest (CA) may occur due to a variety of causes with heterogeneity in their clinical presentation and outcomes. This study aimed to identify clinical patterns or subphenotypes of CA patients admitted to the intensive care unit (ICU). The clinical and laboratory data of CA patients in a large electronic healthcare database were analyzed by latent profile analysis (LPA) to identify whether subphenotypes existed. Multivariable Logistic regression was used to assess whether mortality outcome was different between subphenotypes. A total of 1,352 CA patients fulfilled the eligibility criteria were included. The LPA identified three distinct subphenotypes: Profile 1 (13%) was characterized by evidence of significant neurological injury (low GCS). Profile 2 (15%) was characterized by multiple organ dysfunction with evidence of coagulopathy (prolonged aPTT and INR, decreased platelet count), hepatic injury (high bilirubin), circulatory shock (low mean blood pressure and elevated serum lactate); Profile 3 was the largest proportion (72%) of all CA patients without substantial derangement in major organ function. Profile 2 was associated with a significantly higher risk of death (OR: 2.09; 95% CI: 1.30 to 3.38) whilst the mortality rates of Profiles 3 was not significantly different from Profile 1 in multivariable model. LPA using routinely collected clinical data could identify three distinct subphenotypes of CA; those with multiple organ failure were associated with a significantly higher risk of mortality than other subphenotypes. LPA profiling may help researchers to identify the most appropriate subphenotypes of CA patients for testing effectiveness of a new intervention in a clinical trial.
Collapse
Affiliation(s)
- Zhongheng Zhang
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China.
| | - Min Yao
- Department of Surgery, Wound Care Clinical Research Program, boston University School of Medicine and Boston Medical Center, Boston, MA, 02118, USA
| | - Kwok M Ho
- Department of Intensive Care Medicine, Royal Perth Hospital, School of Population & Global Health, University of Western Australia, Perth, WA, 6000, Australia
| | - Yucai Hong
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
| |
Collapse
|
32
|
Zhang Z, Zheng B, Liu N, Ge H, Hong Y. Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome. Intensive Care Med 2019; 45:856-864. [PMID: 31062050 DOI: 10.1007/s00134-019-05627-9] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 04/22/2019] [Indexed: 02/07/2023]
Abstract
PURPOSE Protective mechanical ventilation based on multiple ventilator parameters such as tidal volume, plateau pressure, and driving pressure has been widely used in acute respiratory distress syndrome (ARDS). More recently, mechanical power (MP) was found to be associated with mortality. The study aimed to investigate whether MP normalized to predicted body weight (norMP) was superior to other ventilator variables and to prove that the discrimination power cannot be further improved with a sophisticated machine learning method. METHODS The study included individual patient data from eight randomized controlled trials conducted by the ARDSNet. The data was split 3:1 into training and testing subsamples. The discrimination of each ventilator variable was calculated in the testing subsample using the area under receiver operating characteristic curve. The gradient boosting machine was used to examine whether the discrimination could be further improved. RESULTS A total of 5159 patients with acute onset ARDS were included for analysis. The discrimination of norMP in predicting mortality was significantly better than the absolute MP (p = 0.011 for DeLong's test). The gradient boosting machine was not able to improve the discrimination as compared to norMP (p = 0.913 for DeLong's test). The multivariable regression model showed a significant interaction between norMP and ARDS severity (p < 0.05). While the norMP was not significantly associated with mortality outcome (OR 0.99; 95% CI 0.91-1.07; p = 0.862) in patients with mild ARDS, it was associated with increased risk of mortality in moderate (OR 1.11; 95% CI 1.02-1.23; p = 0.021) and severe (OR 1.13; 95% CI 1.03-1.24; p < 0.008) ARDS. CONCLUSIONS The study showed that norMP was a good ventilator variable associated with mortality, and its predictive discrimination cannot be further improved with a sophisticated machine learning method. Further experimental trials are needed to investigate whether adjusting ventilator variables according to norMP will significantly improve clinical outcomes.
Collapse
Affiliation(s)
- Zhongheng Zhang
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No 3, East Qingchun Road, Hangzhou, 310016, Zhejiang, China.
| | - Bin Zheng
- Department of Surgery, 2D, Walter C Mackenzie Health Sciences Centre, University of Alberta, Edmonton, AB, Canada
| | - Nan Liu
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
- Health Services Research Centre, Singapore Health Services, Singapore, Singapore
| | - Huiqing Ge
- Department of Respiratory Care, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yucai Hong
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No 3, East Qingchun Road, Hangzhou, 310016, Zhejiang, China
| |
Collapse
|
33
|
Zhang Z, Ho KM, Hong Y. Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care. Crit Care 2019; 23:112. [PMID: 30961662 PMCID: PMC6454725 DOI: 10.1186/s13054-019-2411-z] [Citation(s) in RCA: 156] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 03/26/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challenges. This study aimed to develop a prediction model that can be used to differentiate between volume-responsive (VR) and volume-unresponsive (VU) AKI. METHODS AKI patients with urine output < 0.5 ml/kg/h for the first 6 h after ICU admission and fluid intake > 5 l in the following 6 h in the US-based critical care database (Medical Information Mart for Intensive Care (MIMIC-III)) were considered. Patients who received diuretics and renal replacement on day 1 were excluded. Two predictive models, using either machine learning extreme gradient boosting (XGBoost) or logistic regression, were developed to predict urine output > 0.65 ml/kg/h during 18 h succeeding the initial 6 h for assessing oliguria. Established models were assessed by using out-of-sample validation. The whole sample was split into training and testing samples by the ratio of 3:1. MAIN RESULTS Of the 6682 patients included in the analysis, 2456 (36.8%) patients were volume responsive with an increase in urine output after receiving > 5 l fluid. Urinary creatinine, blood urea nitrogen (BUN), age, and albumin were the important predictors of VR. The machine learning XGBoost model outperformed the traditional logistic regression model in differentiating between the VR and VU groups (AU-ROC, 0.860; 95% CI, 0.842 to 0.878 vs. 0.728; 95% CI 0.703 to 0.753, respectively). CONCLUSIONS The XGBoost model was able to differentiate between patients who would and would not respond to fluid intake in urine output better than a traditional logistic regression model. This result suggests that machine learning techniques have the potential to improve the development and validation of predictive modeling in critical care research.
Collapse
Affiliation(s)
- Zhongheng Zhang
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3, East Qingchun Road, Hangzhou, 310016 Zhejiang Province China
| | - Kwok M. Ho
- 0000 0004 1936 7910grid.1012.2School of Population and Global Health, University of Western Australia, Perth, Australia
| | - Yucai Hong
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3, East Qingchun Road, Hangzhou, 310016 Zhejiang Province China
| |
Collapse
|
34
|
Zhang Z, Zhang G, Goyal H, Mo L, Hong Y. Identification of subclasses of sepsis that showed different clinical outcomes and responses to amount of fluid resuscitation: a latent profile analysis. Crit Care 2018; 22:347. [PMID: 30563548 PMCID: PMC6299613 DOI: 10.1186/s13054-018-2279-3] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 11/26/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND AND OBJECTIVE Sepsis is a heterogeneous disease and identification of its subclasses may facilitate and optimize clinical management. This study aimed to identify subclasses of sepsis and its responses to different amounts of fluid resuscitation. METHODS This was a retrospective study conducted in an intensive care unit at a large tertiary care hospital. The patients fulfilling the diagnostic criteria of sepsis from June 1, 2001 to October 31, 2012 were included. Clinical and laboratory variables were used to perform the latent profile analysis (LPA). A multivariable logistic regression model was used to explore the independent association of fluid input and mortality outcome. RESULTS In total, 14,993 patients were included in the study. The LPA identified four subclasses of sepsis: profile 1 was characterized by the lowest mortality rate and having the largest proportion and was considered the baseline type; profile 2 was characterized by respiratory dysfunction; profile 3 was characterized by multiple organ dysfunction (kidney, coagulation, liver, and shock), and profile 4 was characterized by neurological dysfunction. Profile 3 showed the highest mortality rate (45.4%), followed by profile 4 (27.4%), 2 (18.2%), and 1 (16.9%). Overall, the amount of fluid needed for resuscitation was the largest on day 1 (median 5115 mL, interquartile range (IQR) 2662 to 8800 mL) and decreased rapidly on day 2 (median 2140 mL, IQR 900 to 3872 mL). Higher cumulative fluid input in the first 48 h was associated with reduced risk of hospital mortality for profile 3 (odds ratio (OR) 0.89, 95% CI 0.83 to 0.95 for each 1000 mL increase in fluid input) and with increased risk of death for profile 4 (OR 1.20, 95% CI 1.11 to 1.30). CONCLUSION The study identified four subphenotypes of sepsis, which showed different mortality outcomes and responses to fluid resuscitation. Prospective trials are needed to validate our findings.
Collapse
Affiliation(s)
- Zhongheng Zhang
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3, East Qingchun Road, Hangzhou, 310016 Zhejiang Province China
| | - Gensheng Zhang
- 0000 0004 1759 700Xgrid.13402.34Department of Critical Care Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 Zhejiang China
| | - Hemant Goyal
- 0000 0001 2162 9738grid.259906.1Department of Internal Medicine, Mercer University School of Medicine, Macon, GA 31201 USA
| | - Lei Mo
- Department of Biostatistics, Lejiu Healthcare Technology Co., Ltd, Shanghai, China
| | - Yucai Hong
- 0000 0004 1759 700Xgrid.13402.34Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, No. 3, East Qingchun Road, Hangzhou, 310016 Zhejiang Province China
| |
Collapse
|
35
|
Chai W, Zou G, Shi J, Chen W, Gong X, Wei X, Ling L. Evaluation of the effectiveness of a WHO-5A model based comprehensive tobacco control program among migrant workers in Guangdong, China: a pilot study. BMC Public Health 2018; 18:296. [PMID: 29486753 PMCID: PMC6389256 DOI: 10.1186/s12889-018-5182-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 02/19/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND As a vulnerable population in China, migrant workers have a higher smoking rate than the general population. This study aims to assess the effectiveness of a WHO-5A based comprehensive tobacco control program in workplaces aggregated with migrants. METHODS Using a controlled before and after design, four purposely selected manufacturing factories were assigned to either intervention or control groups. Participants in the intervention arm received adapted 5A group counseling regularly supported by social-media and traditional health education approaches. The primary outcome was the change of smoking rate based on salivary cotinine concentration at three-month follow-up as compared to the control arm. Secondary outcomes were changes in smoking-related knowledge and attitudes assessed using questionnaires. Difference-in-differences approach (DID) and generalized estimating equations (GEE) models were used to conduct the effectiveness analysis. RESULTS 149 and 166 workers were enrolled in the intervention and control arm respectively. The multiple imputed and adjusted GEE models demonstrated that, compared to those in the control arm, participants in the intervention arm had nearly 2.4 times odds of improving smoking-related knowledge (OR = 2.40, 95% CI = 1.32-4.36, P = 0.02) and three times the odds of improving smoking-related attitude (OR = 3.07, 95% CI = 1.28-7.41, P = 0.03). However, no significant difference was found regarding the change of smoking rate between the two arms (P > 0.05). The regression analysis showed that attendance at the 5A group counseling sections was an important determinant of stopping smoking or improving smoking-related knowledge and attitudes in the intervention group. CONCLUSIONS This WHO-5A comprehensive intervention was effective in improving migrant workers' knowledge of smoking and anti-smoking attitudes. A large-scale, long-term trial is recommended to determine the effectiveness of this intervention. TRIAL REGISTRATION ChiCTR-OPC-17011637 at Chinese Clinical Trial Registry. Retrospectively registered on 12th June 2017.
Collapse
Affiliation(s)
- Wenxin Chai
- Faculty of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China.,Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Guanyang Zou
- Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China.,Institute for Global Health and Development, Queen Margaret University, Edinburgh, UK
| | - Jingrong Shi
- Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Wen Chen
- Faculty of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China.,Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xiao Gong
- Faculty of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China.,Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xiaolin Wei
- Division of Clinical Public Health and Institute for Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Li Ling
- Faculty of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China. .,Sun Yat-sen Center for Migrant Health Policy, Sun Yat-sen University, Guangzhou, People's Republic of China.
| |
Collapse
|
36
|
Robles-Espinoza CD, Roberts ND, Chen S, Leacy FP, Alexandrov LB, Pornputtapong N, Halaban R, Krauthammer M, Cui R, Timothy Bishop D, Adams DJ. Germline MC1R status influences somatic mutation burden in melanoma. Nat Commun 2016; 7:12064. [PMID: 27403562 PMCID: PMC4945874 DOI: 10.1038/ncomms12064] [Citation(s) in RCA: 96] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 05/27/2016] [Indexed: 01/07/2023] Open
Abstract
The major genetic determinants of cutaneous melanoma risk in the general population are disruptive variants (R alleles) in the melanocortin 1 receptor (MC1R) gene. These alleles are also linked to red hair, freckling, and sun sensitivity, all of which are known melanoma phenotypic risk factors. Here we report that in melanomas and for somatic C>T mutations, a signature linked to sun exposure, the expected single-nucleotide variant count associated with the presence of an R allele is estimated to be 42% (95% CI, 15-76%) higher than that among persons without an R allele. This figure is comparable to the expected mutational burden associated with an additional 21 years of age. We also find significant and similar enrichment of non-C>T mutation classes supporting a role for additional mutagenic processes in melanoma development in individuals carrying R alleles.
Collapse
Affiliation(s)
- Carla Daniela Robles-Espinoza
- Experimental Cancer Genetics, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Boulevard Juriquilla 3001, Santiago de Querétaro 76230, Mexico
| | - Nicola D. Roberts
- Experimental Cancer Genetics, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
- The Cancer Genome Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Shuyang Chen
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine. Boston, Massachusetts 02118, USA
| | - Finbarr P. Leacy
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK
- Division of Population Health Sciences, Royal College of Surgeons in Ireland, Lower Mercer Street, Dublin 2, Ireland
| | - Ludmil B. Alexandrov
- The Cancer Genome Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Natapol Pornputtapong
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06519, USA
| | - Ruth Halaban
- Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut 06519, USA
| | - Michael Krauthammer
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06519, USA
- Program in Computational Biology and Bioinformatics, Yale University School of Medicine, New Haven, Connecticut 06519, USA
| | - Rutao Cui
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine. Boston, Massachusetts 02118, USA
| | - D. Timothy Bishop
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK
| | - David J. Adams
- Experimental Cancer Genetics, The Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
| |
Collapse
|