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Stransky ML, Bremer-Kamens M, Kistin CJ, Sheldrick RC, Cohen RT. Using Electronic Health Records to Identify Asthma-Related Acute Care Encounters. Acad Pediatr 2024:S1876-2859(24)00158-X. [PMID: 38761891 DOI: 10.1016/j.acap.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/20/2024]
Abstract
OBJECTIVE Leveraging "big data" to improve care requires that clinical concepts be operationalized using available data. Electronic health record (EHR) data can be used to evaluate asthma care, but relying solely on diagnosis codes may misclassify asthma-related encounters. We created streamlined, feasible and transparent prototype algorithms for EHR data to classify emergency department (ED) encounters and hospitalizations as "asthma-related." METHODS As part of an asthma program evaluation, expert clinicians conducted a multi-phase iterative chart review to evaluate 467 pediatric ED encounters and 136 hospitalizations with asthma diagnosis codes from calendar years 2017 and 2019, rating the likelihood that each encounter was actually asthma-related. Using this as a reference standard, we developed rule-based algorithms for EHR data to classify visits. Accuracy was evaluated using sensitivity, specificity, and positive and negative predictive values (PPV, NPV). RESULTS Clinicians categorized 38% of ED encounters as "definitely" or "probably" asthma-related; 13% as "possibly" asthma-related; and 49% as "probably not" or "definitely not" related to asthma. Based on this reference standard, we created two rule-based algorithms to identify "definitely" or "probably" asthma-related encounters, one using text and non-text EHR fields and another using non-text fields only. Sensitivity, specificity, PPV, and NPV were >95% for the algorithm using text and non-text fields and >87% for the algorithm using only non-text fields compared to the reference standard. We created a two-rule algorithm to identify asthma-related hospitalizations using only non-text fields. CONCLUSIONS Diagnostic codes alone are insufficient to identify asthma-related visits, but EHR-based prototype algorithms that include additional methods of identification can predict clinician-identified visits with sufficient accuracy.
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Affiliation(s)
- Michelle L Stransky
- Center for the Urban Child and Healthy Family (ML Stransky and M Bremer-Kamens), Boston Medical Center, Boston, Mass; Department of Pediatrics (ML Stransky, RT Cohen), Boston University Chobanian and Avedisian School of Medicine, Boston, Mass.
| | - Miriam Bremer-Kamens
- Center for the Urban Child and Healthy Family (ML Stransky and M Bremer-Kamens), Boston Medical Center, Boston, Mass
| | - Caroline J Kistin
- Hassenfeld Child Health Innovation Institute (CJ Kistin), Brown University, Providence, RI; Department of Health Services (CJ Kistin), Policy and Practice, Brown University, Providence, RI
| | - R Christopher Sheldrick
- Department of Psychiatry, University of Massachusetts Chan Medical School (RC Sheldrick), Worcester, Mass
| | - Robyn T Cohen
- Department of Pediatrics (ML Stransky, RT Cohen), Boston University Chobanian and Avedisian School of Medicine, Boston, Mass; Division of Pediatric Pulmonary and Allergy (RT Cohen), Boston Medical Center, Boston, MA
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Joshi PR. Pulmonary Diseases in Older Patients: Understanding and Addressing the Challenges. Geriatrics (Basel) 2024; 9:34. [PMID: 38525751 PMCID: PMC10961796 DOI: 10.3390/geriatrics9020034] [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: 01/11/2024] [Revised: 02/22/2024] [Accepted: 03/04/2024] [Indexed: 03/26/2024] Open
Abstract
As the global population ages, pulmonary diseases among older people have emerged as a significant and growing public health concern. The increasing incidence of these conditions has led to higher rates of morbidity and mortality among older adults. This perspective study offers a thorough overview of the prevalent pulmonary diseases affecting the elderly demographic. It delves into the challenges encountered during the diagnosis and management of these conditions in older individuals, considering factors such as comorbidities, functional limitations, and medication complexities. Furthermore, innovative strategies and personalized interventions such as precision medicine, advanced therapies, telemedicine solutions, and patient-centered support systems aimed at enhancing the care provided to older individuals grappling with pulmonary disorders are thoroughly explored. By addressing the unique needs and complexities of this vulnerable population, healthcare systems can strive towards improving outcomes and enhancing the quality of life for elderly individuals affected by pulmonary diseases.
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Affiliation(s)
- Pushpa Raj Joshi
- Institute of General Practice and Family Medicine, Martin-Luther-University Halle-Wittenberg, 06112 Halle (Saale), Germany
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3
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Angelini ED, Yang J, Balte PP, Hoffman EA, Manichaikul AW, Sun Y, Shen W, Austin JHM, Allen NB, Bleecker ER, Bowler R, Cho MH, Cooper CS, Couper D, Dransfield MT, Garcia CK, Han MK, Hansel NN, Hughes E, Jacobs DR, Kasela S, Kaufman JD, Kim JS, Lappalainen T, Lima J, Malinsky D, Martinez FJ, Oelsner EC, Ortega VE, Paine R, Post W, Pottinger TD, Prince MR, Rich SS, Silverman EK, Smith BM, Swift AJ, Watson KE, Woodruff PG, Laine AF, Barr RG. Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans. Thorax 2023; 78:1067-1079. [PMID: 37268414 PMCID: PMC10592007 DOI: 10.1136/thorax-2022-219158] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/03/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations. METHODS New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined. RESULTS The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome. CONCLUSION Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.
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Affiliation(s)
- Elsa D Angelini
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
- LTCI, Institut Polytechnique de Paris, Telecom Paris, Palaiseau, France
- NIHR Imperial Biomedical Research Centre, ITMAT Data Science Group, Imperial College, London, UK
| | - Jie Yang
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
| | - Pallavi P Balte
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Eric A Hoffman
- Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yifei Sun
- Department of Biostatistics, Columbia University Irving Medical Center, New York, New York, USA
| | - Wei Shen
- Department of Pediatrics, Institute of Human Nutrition, Columbia University Irving Medical Center, New York, New York, USA
- Columbia Magnetic Resonance Research Center (CMRRC), Columbia University Irving Medical Center, New York, New York, USA
| | - John H M Austin
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Norrina B Allen
- Institute for Public Health and Medicine (IPHAM) - Center for Epidemiology and Population Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Eugene R Bleecker
- Department of Medicine, University of Arizona Health Sciences, Tucson, Arizona, USA
| | - Russell Bowler
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | | | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Christine Kim Garcia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - MeiLan K Han
- Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Nadia N Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Emlyn Hughes
- Department of Physics, Columbia University, New York, New York, USA
| | - David R Jacobs
- Division of Epidemiology and Community Public Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Silva Kasela
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York, USA
- New York Genome Center, New York, New York, USA
| | - Joel Daniel Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine, and Epidemiology, University of Washington, Seattle, Washington, USA
| | - John Shinn Kim
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Tuuli Lappalainen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York, USA
| | - Joao Lima
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Daniel Malinsky
- Department of Biostatistics, Columbia University Irving Medical Center, New York, New York, USA
| | - Fernando J Martinez
- Department of Medicine, Cornell University Joan and Sanford I Weill Medical College, New York, New York, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Victor E Ortega
- Department of Pulmonary Medicine, Mayo Clinic, Phoenix, Arizona, USA
| | - Robert Paine
- Department of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Wendy Post
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Tess D Pottinger
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Martin R Prince
- Department of Radiology, Cornell University Joan and Sanford I Weill Medical College, New York, New York, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Benjamin M Smith
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Andrew J Swift
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK
| | - Karol E Watson
- Department of Medicine, University of California, Los Angeles, California, USA
| | - Prescott G Woodruff
- Department of Medicine, University of California, San Francisco, California, USA
| | - Andrew F Laine
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
- Columbia Magnetic Resonance Research Center (CMRRC), Columbia University Irving Medical Center, New York, New York, USA
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York, USA
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MacDonald DM, Ji Y, Adabag S, Alonso A, Chen LY, Henkle BE, Juraschek SP, Norby FL, Lutsey PL, Kunisaki KM. Cardiovascular Autonomic Function and Incident Chronic Obstructive Pulmonary Disease Hospitalizations in Atherosclerosis Risk in Communities. Ann Am Thorac Soc 2023; 20:1435-1444. [PMID: 37364277 PMCID: PMC10559138 DOI: 10.1513/annalsats.202211-964oc] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 06/23/2023] [Indexed: 06/28/2023] Open
Abstract
Rationale: The autonomic nervous system extensively innervates the lungs, but its role in chronic obstructive pulmonary disease (COPD) outcomes has not been well studied. Objective: We assessed relationships between cardiovascular autonomic nervous system measures (heart rate variability [HRV] and orthostatic hypotension [OH]) and incident COPD hospitalization in the multicenter ARIC (Atherosclerosis Risk In Communities) study. Methods: We used Cox proportional hazards regression models to estimate hazard ratios and 95% confidence intervals between baseline (1987-1989) autonomic function measures (HRV measures from 2-minute electrocardiograms and OH variables) and incident COPD hospitalizations through 2019. Adjusted analyses included demographic data, smoking status, lung function, comorbidities, and physical activity. We also performed analyses stratified by baseline airflow obstruction. Results: Of the 11,625 participants, (mean age, 53.8 yr), 56.5% were female and 26.3% identified as Black. Baseline mean percentage predicted forced expiratory volume in 1 second was 94 ± 17% (standard deviation), and 2,599 participants (22.4%) had airflow obstruction. During a median follow-up time of 26.9 years, there were 2,406 incident COPD hospitalizations. Higher HRV (i.e., better autonomic function) was associated with a lower risk of incident COPD hospitalization. Markers of worse autonomic function (OH and greater orthostatic changes in systolic and diastolic blood pressure) were associated with a higher risk of incident COPD hospitalization (hazard ratio for the presence of OH, 1.5; 95% confidence interval, 1.25-1.92). In stratified analyses, results were more robust in participants without airflow obstruction at baseline. Conclusions: In this large multicenter prospective community cohort, better cardiovascular autonomic function at baseline was associated with a lower risk of subsequent hospitalization for COPD, particularly among participants without evidence of lung disease at baseline.
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Affiliation(s)
| | - Yuekai Ji
- Division of Epidemiology and Community Health, and
| | - Selcuk Adabag
- Cardiology Section, Minneapolis VA Health Care System, Minneapolis, Minnesota
- Cardiovascular Division, University of Minnesota, Minneapolis, Minnesota
| | - Alvaro Alonso
- Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Lin Yee Chen
- Cardiovascular Division, University of Minnesota, Minneapolis, Minnesota
| | | | - Stephen P. Juraschek
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; and
| | - Faye L. Norby
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Health System, Los Angeles, California
| | | | - Ken M. Kunisaki
- Pulmonary Section, and
- Pulmonary, Allergy, Critical Care, and Sleep
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5
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Elmaleh-Sachs A, Balte P, Oelsner EC, Allen NB, Baugh A, Bertoni AG, Hankinson JL, Pankow JS, Post WS, Schwartz JE, Smith BM, Watson K, Barr RG. Reply by Elmaleh-Sachs et al. to Townsend and Cowl, and to Miller et al.. Am J Respir Crit Care Med 2022; 206:792-795. [PMID: 35503649 PMCID: PMC9799126 DOI: 10.1164/rccm.202204-0628le] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Affiliation(s)
| | - Pallavi Balte
- Columbia University Medical CenterNew York, New York
| | | | | | - Aaron Baugh
- University of California San FranciscoSan Francisco, California
| | | | | | - James S. Pankow
- University of Minnesota School of Public HealthMinneapolis, Minnesota
| | - Wendy S. Post
- Johns Hopkins University School of MedicineBaltimore, Maryland
| | | | | | - Karol Watson
- University of California Los AngelesLos Angeles, California
| | - R. Graham Barr
- Columbia University Medical CenterNew York, New York,Corresponding author (e-mail: )
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6
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Oelsner EC, Krishnaswamy A, Balte PP, Allen NB, Ali T, Anugu P, Andrews H, Arora K, Asaro A, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Coady S, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MLK, Henderson JM, Howard VJ, Isasi CR, Jacobs Jr DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Mendoza-Puccini C, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post WS, Postow L, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y, C4R Investigators FT. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. Am J Epidemiol 2022; 191:1153-1173. [PMID: 35279711 PMCID: PMC8992336 DOI: 10.1093/aje/kwac032] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 01/26/2022] [Accepted: 02/09/2022] [Indexed: 01/26/2023] Open
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.
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Affiliation(s)
- Elizabeth C Oelsner
- Correspondence to Dr. Elizabeth C Oelsner, MD MPH, Herbert Irving Associate Professor of Medicine, Division of General Medicine, Columbia University Irving Medical Center, 622 West 168 Street, PH9-105K New York, NY 10032 Tel: 917-880-7099
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7
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Eckhardt CM, Balte PP, Barr RG, Bertoni AG, Bhatt SP, Cuttica M, Cassano PA, Chaves P, Couper D, Jacobs DR, Kalhan R, Kronmal R, Lange L, Loehr L, London SJ, O’Connor GT, Rosamond W, Sanders J, Schwartz JE, Shah A, Shah SJ, Smith L, White W, Yende S, Oelsner EC. Lung function impairment and risk of incident heart failure: the NHLBI Pooled Cohorts Study. Eur Heart J 2022; 43:2196-2208. [PMID: 35467708 PMCID: PMC9631233 DOI: 10.1093/eurheartj/ehac205] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 02/06/2022] [Accepted: 03/22/2022] [Indexed: 12/16/2022] Open
Abstract
AIMS The aim is to evaluate associations of lung function impairment with risk of incident heart failure (HF). METHODS AND RESULTS Data were pooled across eight US population-based cohorts that enrolled participants from 1987 to 2004. Participants with self-reported baseline cardiovascular disease were excluded. Spirometry was used to define obstructive [forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.70] or restrictive (FEV1/FVC ≥0.70, FVC <80%) lung physiology. The incident HF was defined as hospitalization or death caused by HF. In a sub-set, HF events were sub-classified as HF with reduced ejection fraction (HFrEF; EF <50%) or preserved EF (HFpEF; EF ≥50%). The Fine-Gray proportional sub-distribution hazards models were adjusted for sociodemographic factors, smoking, and cardiovascular risk factors. In models of incident HF sub-types, HFrEF, HFpEF, and non-HF mortality were treated as competing risks. Among 31 677 adults, there were 3344 incident HF events over a median follow-up of 21.0 years. Of 2066 classifiable HF events, 1030 were classified as HFrEF and 1036 as HFpEF. Obstructive [adjusted hazard ratio (HR) 1.17, 95% confidence interval (CI) 1.07-1.27] and restrictive physiology (adjusted HR 1.43, 95% CI 1.27-1.62) were associated with incident HF. Obstructive and restrictive ventilatory defects were associated with HFpEF but not HFrEF. The magnitude of the association between restrictive physiology and HFpEF was similar to associations with hypertension, diabetes, and smoking. CONCLUSION Lung function impairment was associated with increased risk of incident HF, and particularly incident HFpEF, independent of and to a similar extent as major known cardiovascular risk factors.
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Affiliation(s)
- Christina M Eckhardt
- Department of Medicine, Columbia University College of Physicians and Surgeons, 630 West 168th Street, Presbyterian Hospital 9th Floor, Suite 105, New York, NY 10032, USA
| | - Pallavi P Balte
- Department of Medicine, Columbia University College of Physicians and Surgeons, 630 West 168th Street, Presbyterian Hospital 9th Floor, Suite 105, New York, NY 10032, USA
| | - Robert Graham Barr
- Department of Medicine, Columbia University College of Physicians and Surgeons, 630 West 168th Street, Presbyterian Hospital 9th Floor, Suite 105, New York, NY 10032, USA
| | - Alain G Bertoni
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Surya P Bhatt
- Division of Pulmonary, University of Alabama at Birmingham, Allergy and Critical Care Medicine, Birmingham, AL, USA
| | - Michael Cuttica
- Department of Medicine, Northwestern University, Chicago, IL, USA
| | - Patricia A Cassano
- Division of Nutritional Sciences, Cornell University, College of Human Ecology, Cornell, NY, USA
| | - Paolo Chaves
- Department of Health and Society, Florida International University, Miami, FL, USA
| | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
| | - David R Jacobs
- Division of Epidemiology and Community Health, University of Minnesota, School of Public Health, Minneapolis, MN, USA
| | - Ravi Kalhan
- Department of Medicine, Northwestern University, Chicago, IL, USA
| | - Richard Kronmal
- Department of Statistics, University of Washington, School of Public Health, Seattle, WA, USA
| | - Leslie Lange
- Department of Medicine, University of Colorado, Denver, CO, USA
| | - Laura Loehr
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | | | - Wayne Rosamond
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Jason Sanders
- Division of Pulmonary Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Joseph E Schwartz
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Amil Shah
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Sanjiv J Shah
- Department of Medicine, Northwestern University, Chicago, IL, USA
| | - Lewis Smith
- Department of Medicine, Northwestern University, Chicago, IL, USA
| | - Wendy White
- Undergraduate Training and Education Center, Tougaloo College, Jackson Heart Study, Jackson, MS, USA
| | - Sachin Yende
- Department of Critical Care Medicine, Veterans Affairs Pittsburgh Healthcare System and University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University College of Physicians and Surgeons, 630 West 168th Street, Presbyterian Hospital 9th Floor, Suite 105, New York, NY 10032, USA
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8
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Seidl E, Schwerk N, Carlens J, Wetzke M, Emiralioğlu N, Kiper N, Lange J, Krenke K, Szepfalusi Z, Stehling F, Baden W, Hämmerling S, Jerkic SP, Proesmans M, Ullmann N, Buchvald F, Knoflach K, Kappler M, Griese M. Acute exacerbations in children's interstitial lung disease. Thorax 2022; 77:799-804. [PMID: 35149584 DOI: 10.1136/thoraxjnl-2021-217941] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 12/22/2021] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Acute exacerbations (AEs) increase morbidity and mortality of patients with chronic pulmonary diseases. Little is known about the characteristics and impact of AEs on children's interstitial lung disease (chILD). METHODS The Kids Lung Register collected data on AEs, the clinical course and quality of life (patient-reported outcomes - PRO) of rare paediatric lung diseases. Characteristics of AEs were obtained. RESULTS Data of 2822 AEs and 2887 register visits of 719 patients with chILD were recorded. AEs were characterised by increased levels of dyspnoea (74.1%), increased respiratory rate (58.6%) and increased oxygen demand (57.4%). Mostly, infections (94.4%) were suspected causing an AE. AEs between two register visits revealed a decline in predicted FEV1 (median -1.6%, IQR -8.0 to 3.9; p=0.001), predicted FVC (median -1.8%, IQR -7.5 to 3.9; p=0.004), chILD-specific questionnaire (median -1.3%, IQR -3.6 to 4.5; p=0.034) and the physical health summary score (median -3.1%, IQR -15.6 to 4.3; p=0.005) compared with no AEs in between visits. During the median observational period of 2.5 years (IQR 1.2-4.6), 81 patients died. For 49 of these patients (60.5%), mortality was associated with an AE. CONCLUSION This is the first comprehensive study analysing the characteristics and impact on the clinical course of AEs in chILD. AEs have a significant and deleterious effect on the clinical course and health-related quality of life in chILD.
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Affiliation(s)
- Elias Seidl
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, German Center for Lung Research, Munich, Germany
| | - Nicolaus Schwerk
- Clinic for Pediatric Pneumology, Allergology, and Neonatology, Hannover Medical School, German Center for Lung Research, Hannover, Germany
| | - Julia Carlens
- Clinic for Pediatric Pneumology, Allergology, and Neonatology, Hannover Medical School, German Center for Lung Research, Hannover, Germany
| | - Martin Wetzke
- Clinic for Pediatric Pneumology, Allergology, and Neonatology, Hannover Medical School, German Center for Lung Research, Hannover, Germany
| | - Nagehan Emiralioğlu
- Division of Pediatric Pulmonology, Hacettepe University Faculty of Medicine, Ankara, Turkey, Ankara, Turkey
| | - Nural Kiper
- Division of Pediatric Pulmonology, Hacettepe University Faculty of Medicine, Ankara, Turkey, Ankara, Turkey
| | - Joanna Lange
- Department of Pediatric Pneumology and Allergy, Medical University of Warsaw, Warsaw, Poland
| | - Katarzyna Krenke
- Department of Pediatric Pneumology and Allergy, Medical University of Warsaw, Warsaw, Poland
| | - Zsolt Szepfalusi
- Division of Pediatric Pulmonology, Allergy and Endocrinology, Departement of Pediatrics and Adolescent Medicine, Comprehensive Center of Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Florian Stehling
- Department of Pediatric Pulmonology and Sleep Medicine, University Children's Hospital Essen, Essen, Germany
| | - Winfried Baden
- Department of Pediatrics 2, Children's Hospital, Eberhard Karls University, Tuebingen, Germany
| | - Susanne Hämmerling
- Division of Pediatric Pulmonology & Allergy and Cystic Fibrosis Center, Department of Pediatrics III, University of Heidelberg, Germany, Heidelberg, Germany
| | - Silvija-Pera Jerkic
- Department of Allergy, Pneumology, and Cystic Fibrosis, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Marijke Proesmans
- Department of Pediatrics, Pediatric Pulmonology, University Hospital of Leuven, Leuven, Flanders, Belgium
| | - Nicola Ullmann
- Pediatric Pulmonology and Respiratory Intermediate Care Unit, Sleep and Long Term Ventilation Unit, Academic Department of Pediatrics (DPUO), Pediatric Hospital "Bambino Gesù" Research Institute, Roma, Italy
| | - Frederik Buchvald
- Department of Paediatrics and Adolescent Medicine, Paediatric Pulmonary Service, Copenhagen University Hospital, Rigshospitalet, Danish PCD & chILD Centre, CF Centre Copenhagen, Copenhagen, Denmark
| | - Katrin Knoflach
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, German Center for Lung Research, Munich, Germany
| | - Matthias Kappler
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, German Center for Lung Research, Munich, Germany
| | | | - Matthias Griese
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, German Center for Lung Research, Munich, Germany
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9
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Elmaleh-Sachs A, Balte P, Oelsner EC, Allen NB, Baugh AD, Bertoni AG, Hankinson JL, Pankow J, Post WS, Schwartz JE, Smith BM, Watson K, Barr RG. Race/Ethnicity, Spirometry Reference Equations and Prediction of Incident Clinical Events: The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study. Am J Respir Crit Care Med 2021; 205:700-710. [PMID: 34913853 DOI: 10.1164/rccm.202107-1612oc] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Normal values for forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) are currently calculated using cross-sectional reference equations that include terms for race/ethnicity, an approach that may reinforce disparities and is of unclear clinical benefit. OBJECTIVES To determine whether race/ethnic-based spirometry reference equations improve the prediction of incident chronic lower respiratory disease (CLRD) events and mortality compared to race/ethnic-neutral equations. METHODS The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study, a population-based, prospective cohort study of White, Black, Hispanic, and Asian adults, performed standardized spirometry in 2004-06. Predicted values for spirometry were calculated using race/ethnic-based equations following guidelines and, alternatively, race/ethnic-neutral equations without terms for race/ethnicity. Participants were followed for events through 2019. MEASUREMENTS AND MAIN RESULTS The mean age of 3,344 participants was 65 years and self-reported race/ethnicity was 36% White, 25% Black, 23% Hispanic, and 17% Asian. There were 181 incident CLRD-related events and 547 deaths over a median of 11.6 years. There was no evidence that percent-predicted FEV1 or FVC calculated by race/ethnic-based equations improved the prediction of CLRD-related events compared to that calculated by race/ethnic-neutral equations (difference in C-statistics -0.005, 95% CI -0.013, 0.003, and -0.008, 95% CI -0.016, -0.0006, respectively). Findings were similar for mortality (difference in C-statistics -0.002, 95% CI -0.008, 0.003, and -0.004, 95% CI -0.009, 0.001, respectively). CONCLUSIONS There was no evidence that race/ethnic-based spirometry reference equations improved the prediction of clinical events compared to race/ethnic-neutral equations. The inclusion of race/ethnicity in spirometry reference equations should be reconsidered.
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Affiliation(s)
- Arielle Elmaleh-Sachs
- Columbia University Irving Medical Center, 21611, General Medicine, New York, New York, United States
| | - Pallavi Balte
- Columbia University, Medicine, New York, New York, United States
| | | | | | - Aaron D Baugh
- UCSF, Division of Pulmonary and Critical Care Medicine, Department of Medicine and CVRI, San Francisco, California, United States
| | - Alain G Bertoni
- Wake Forest University, Department of Epidemiology and Prevention, Winston-Salem, North Carolina, United States
| | | | - Jim Pankow
- University of Minnesota School of Public Health, 43353, Minneapolis, Minnesota, United States
| | - Wendy S Post
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | - Joseph E Schwartz
- Columbia University Medical Center, Department of Medicine, New York, New York, United States
| | - Benjamin M Smith
- Columbia University Medical Center, Medicine, New York, New York, United States
| | - Karol Watson
- University of California at Los Angeles, Medicine, Los Angeles, California, United States
| | - R Graham Barr
- Columbia University, Epidemiology, New York, New York, United States;
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10
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Wan ES, Balte P, Schwartz JE, Bhatt SP, Cassano PA, Couper D, Daviglus ML, Dransfield MT, Gharib SA, Jacobs DR, Kalhan R, London SJ, Acien AN, O’Connor GT, Sanders JL, Smith BM, White W, Yende S, Oelsner EC. Association Between Preserved Ratio Impaired Spirometry and Clinical Outcomes in US Adults. JAMA 2021; 326:2287-2298. [PMID: 34905031 PMCID: PMC8672237 DOI: 10.1001/jama.2021.20939] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 11/03/2021] [Indexed: 11/14/2022]
Abstract
Importance Chronic lung diseases are a leading cause of morbidity and mortality. Unlike chronic obstructive pulmonary disease, clinical outcomes associated with proportional reductions in expiratory lung volumes without obstruction, otherwise known as preserved ratio impaired spirometry (PRISm), are poorly understood. Objective To examine the prevalence, correlates, and clinical outcomes associated with PRISm in US adults. Design, Setting, and Participants The National Heart, Lung, and Blood Institute (NHLBI) Pooled Cohorts Study was a retrospective study with harmonized pooled data from 9 US general population-based cohorts (enrollment, 65 251 participants aged 18 to 102 years of whom 53 701 participants had valid baseline lung function) conducted from 1971-2011 (final follow-up, December 2018). Exposures Participants were categorized into mutually exclusive groups by baseline lung function. PRISm was defined as the ratio of forced expiratory volume in the first second to forced vital capacity (FEV1:FVC) greater than or equal to 0.70 and FEV1 less than 80% predicted; obstructive spirometry FEV1:FVC ratio of less than 0.70; and normal spirometry FEV1:FVC ratio greater than or equal to 0.7 and FEV1 greater than or equal to 80% predicted. Main Outcomes and Measures Main outcomes were all-cause mortality, respiratory-related mortality, coronary heart disease (CHD)-related mortality, respiratory-related events (hospitalizations and mortality), and CHD-related events (hospitalizations and mortality) classified by adjudication or validated administrative criteria. Absolute risks were adjusted for age and smoking status. Poisson and Cox proportional hazards models comparing PRISm vs normal spirometry were adjusted for age, sex, race and ethnicity, education, body mass index, smoking status, cohort, and comorbidities. Results Among all participants (mean [SD] age, 53.2 [15.8] years, 56.4% women, 48.5% never-smokers), 4582 (8.5%) had PRISm. The presence of PRISm relative to normal spirometry was significantly associated with obesity (prevalence, 48.3% vs 31.4%; prevalence ratio [PR], 1.68 [95% CI, 1.55-1.82]), underweight (prevalence, 1.4% vs 1.0%; PR, 2.20 [95% CI, 1.72-2.82]), female sex (prevalence, 60.3% vs 59.0%; PR, 1.07 [95% CI, 1.01-1.13]), and current smoking (prevalence, 25.2% vs 17.5%; PR, 1.33 [95% CI, 1.22-1.45]). PRISm, compared with normal spirometry, was significantly associated with greater all-cause mortality (29.6/1000 person-years vs 18.0/1000 person-years; difference, 11.6/1000 person-years [95% CI, 10.0-13.1]; adjusted hazard ratio [HR], 1.50 [95% CI, 1.42-1.59]), respiratory-related mortality (2.1/1000 person-years vs 1.0/1000 person-years; difference, 1.1/1000 person-years [95% CI, 0.7-1.6]; adjusted HR, 1.95 [95% CI, 1.54-2.48]), CHD-related mortality (5.4/1000 person-years vs 2.6/1000 person-years; difference, 2.7/1000 person-years [95% CI, 2.1-3.4]; adjusted HR, 1.55 [95% CI, 1.36-1.77]), respiratory-related events (12.2/1000 person-years vs 6.0/1000 person-years; difference, 6.2/1000 person-years [95% CI, 4.9-7.5]; adjusted HR, 1.90 [95% CI, 1.69-2.14]), and CHD-related events (11.7/1000 person-years vs 7.0/1000 person-years; difference, 4.7/1000 person-years [95% CI, 3.7-5.8]; adjusted HR, 1.30 [95% CI, 1.18-1.42]). Conclusions and Relevance In a large, population-based sample of US adults, baseline PRISm, compared with normal spirometry, was associated with a small but statistically significant increased risk for mortality and adverse cardiovascular and respiratory outcomes. Further research is needed to explore whether this association is causal.
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Affiliation(s)
- Emily S. Wan
- Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, Massachusetts
- VA Boston Healthcare System, Boston, Massachusetts
| | | | - Joseph E. Schwartz
- Columbia University, New York, New York
- Renaissance School of Medicine at Stony Brook University, Stony Brook, New York
| | | | | | | | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago
| | | | - Sina A. Gharib
- Computational Medicine Core, Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle
| | | | | | - Stephanie J. London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina
| | | | | | - Jason L. Sanders
- Division of Pulmonary and Critical Care, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | | | - Sachin Yende
- University of Pittsburgh, Pittsburgh, Pennsylvania
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11
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Mapel DW, Roberts MH, Sama S, Bobbili PJ, Cheng WY, Duh MS, Nguyen C, Thompson-Leduc P, Van Dyke MK, Rothnie KJ, Sundaresan D, Certa JM, Whiting TS, Brown JL, Roblin DW. Development and Validation of a Healthcare Utilization-Based Algorithm to Identify Acute Exacerbations of Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis 2021; 16:1687-1698. [PMID: 34135580 PMCID: PMC8200149 DOI: 10.2147/copd.s302241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 05/09/2021] [Indexed: 12/02/2022] Open
Abstract
Introduction Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are important events that may precipitate other adverse outcomes. Accurate AECOPD event identification in electronic administrative data is essential for improving population health surveillance and practice management. Objective Develop codified algorithms to identify moderate and severe AECOPD in two US healthcare systems using administrative data and electronic medical records, and validate their performance by calculating positive predictive value (PPV) and negative predictive value (NPV). Methods Data from two large regional integrated health systems were used. Eligible patients were identified using International Classification of Diseases (Ninth Edition) COPD diagnosis codes. Two algorithms were developed: one to identify potential moderate AECOPD by selecting outpatient/emergency visits associated with AECOPD-related codes and antibiotic/systemic steroid prescriptions; the other to identify potential severe AECOPD by selecting inpatient visits associated with corresponding codes. Algorithms were validated via patient chart review, adjudicated by a pulmonologist. To estimate PPV, 300 potential moderate AECOPD and 250 potential severe AECOPD events underwent review. To estimate NPV, 200 patients without any AECOPD identified by the algorithms (100 patients each without moderate or severe AECOPD) during the two years following the index date underwent review to identify AECOPD missed by the algorithm (false negatives). Results The PPVs (95% confidence interval [CI]) for both moderate and severe AECOPD were high: 293/298 (98.3% [96.1-99.5]) and 216/225 (96.0% [92.5-98.2]), respectively. NPV was lower for moderate AECOPD (75.0% [65.3-83.1]) than for severe AECOPD (95.0% [88.7-98.4]). Results were consistent across both healthcare systems. Conclusion This study developed healthcare utilization-based algorithms to identify moderate and severe AECOPD in two separate healthcare systems. PPV for both algorithms was high; NPV was lower for the moderate algorithm. Replication and consistency of results across two healthcare systems support the external validity of these findings.
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Affiliation(s)
- Douglas W Mapel
- College of Pharmacy, University of New Mexico, Albuquerque, NM, USA
| | | | - Susan Sama
- Reliant Medical Group, Inc., Worcester, MA, USA
| | | | | | | | | | | | | | | | | | - Julia M Certa
- Kaiser Permanente Mid-Atlantic States (KPMAS), Mid-Atlantic Permanente Research Institute (MAPRI), Rockville, MD, USA
| | - Thomas S Whiting
- Kaiser Permanente Mid-Atlantic States (KPMAS), Mid-Atlantic Permanente Research Institute (MAPRI), Rockville, MD, USA
| | - Jennifer L Brown
- Kaiser Permanente Mid-Atlantic States (KPMAS), Mid-Atlantic Permanente Research Institute (MAPRI), Rockville, MD, USA
| | - Douglas W Roblin
- Kaiser Permanente Mid-Atlantic States (KPMAS), Mid-Atlantic Permanente Research Institute (MAPRI), Rockville, MD, USA
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12
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Albogami Y, Cusi K, Daniels MJ, Wei YJJ, Winterstein AG. Glucagon-Like Peptide 1 Receptor Agonists and Chronic Lower Respiratory Disease Exacerbations Among Patients With Type 2 Diabetes. Diabetes Care 2021; 44:1344-1352. [PMID: 33875487 PMCID: PMC8247488 DOI: 10.2337/dc20-1794] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 03/01/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Emerging data from animal and human pilot studies suggest potential benefits of glucagon-like peptide 1 receptor agonists (GLP-1RA) on lung function. We aimed to assess the association of GLP-1RA and chronic lower respiratory disease (CLRD) exacerbation in a population with comorbid type 2 diabetes (T2D) and CLRD. RESEARCH DESIGN AND METHODS A new-user active-comparator analysis was conducted with use of a national claims database of beneficiaries with employer-sponsored health insurance spanning 2005-2017. We included adults with T2D and CLRD who initiated GLP-1RA or dipeptidyl peptidase 4 inhibitors (DPP-4I) as an add-on therapy to their antidiabetes regimen. The primary outcome was time to first hospital admission for CLRD. The secondary outcome was a count of any CLRD exacerbation associated with an inpatient or outpatient visit. We estimated incidence rates using inverse probability of treatment weighting for each study group and compared via risk ratios. RESULTS The study sample consisted of 4,150 GLP-1RA and 12,540 DPP-4I new users with comorbid T2D and CLRD. The adjusted incidence rate of first CLRD admission during follow-up was 10.7 and 20.3 per 1,000 person-years for GLP-1RA and DPP-4I users, respectively, resulting in an adjusted hazard ratio of 0.52 (95% CI 0.32-0.85). For the secondary outcome, the adjusted incidence rate ratio was 0.70 (95% CI 0.57-0.87). CONCLUSIONS GLP-1RA users had fewer CLRD exacerbations in comparison with DPP-4I users. Considering both plausible mechanistic pathways and this real-world evidence, potential beneficial effects of GLP-1RA may be considered in selection of an antidiabetes treatment regimen. Randomized clinical trials are warranted to confirm our findings.
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Affiliation(s)
- Yasser Albogami
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, FL .,Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL.,Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Kenneth Cusi
- Division of Endocrinology, Diabetes and Metabolism, University of Florida, Gainesville, FL
| | | | - Yu-Jung J Wei
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, FL.,Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, FL.,Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL
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13
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Oelsner EC, Allen NB, Ali T, Anugu P, Andrews H, Asaro A, Balte PP, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MK, Henderson JM, Howard VJ, Isasi CR, Jacobs DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Krishnaswamy A, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post W, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.03.19.21253986. [PMID: 33758891 PMCID: PMC7987050 DOI: 10.1101/2021.03.19.21253986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.
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14
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Balte PP, Chaves PHM, Couper DJ, Enright P, Jacobs DR, Kalhan R, Kronmal RA, Loehr LR, London SJ, Newman AB, O'Connor GT, Schwartz JE, Smith BM, Smith LJ, White WB, Yende S, Oelsner EC. Association of Nonobstructive Chronic Bronchitis With Respiratory Health Outcomes in Adults. JAMA Intern Med 2020; 180:676-686. [PMID: 32119036 PMCID: PMC7052787 DOI: 10.1001/jamainternmed.2020.0104] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
IMPORTANCE Chronic bronchitis has been associated with cigarette smoking as well as with e-cigarette use among young adults, but the association of chronic bronchitis in persons without airflow obstruction or clinical asthma, described as nonobstructive chronic bronchitis, with respiratory health outcomes remains uncertain. OBJECTIVE To assess whether nonobstructive chronic bronchitis is associated with adverse respiratory health outcomes in adult ever smokers and never smokers. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 22 325 adults without initial airflow obstruction (defined as the ratio of forced expiratory volume in the first second [FEV1] to forced vital capacity [FVC] of <0.70) or clinical asthma at baseline. The National Heart, Lung, and Blood Institute (NHLBI) Pooled Cohorts Study harmonized and pooled data from 9 US general population-based cohorts. Thus present study is based on data from 5 of these cohorts. Participants were enrolled from August 1971 through May 2007 and were followed up through December 2018. EXPOSURES Nonobstructive chronic bronchitis was defined by questionnaire at baseline as both cough and phlegm for at least 3 months for at least 2 consecutive years. MAIN OUTCOMES AND MEASURES Lung function was measured by prebronchodilator spirometry. Hospitalizations and deaths due to chronic lower respiratory disease and respiratory disease-related mortality were defined by events adjudication and administrative criteria. Models were stratified by smoking status and adjusted for anthropometric, sociodemographic, and smoking-related factors. The comparison group was participants without nonobstructive chronic bronchitis. RESULTS Among 22 325 adults included in the analysis, mean (SD) age was 53.0 (16.3) years (range, 18.0-95.0 years), 58.2% were female, 65.9% were non-Hispanic white, and 49.6% were ever smokers. Among 11 082 ever smokers with 99 869 person-years of follow-up, participants with nonobstructive chronic bronchitis (300 [2.7%]) had accelerated decreases in FEV1 (4.1 mL/y; 95% CI, 2.1-6.1 mL/y) and FVC (4.7 mL/y; 95% CI, 2.2-7.2 mL/y), increased risks of chronic lower respiratory disease-related hospitalization or mortality (hazard ratio [HR], 2.2; 95% CI, 1.7-2.7), and greater respiratory disease-related (HR, 2.0; 95% CI, 1.1-3.8) and all-cause mortality (HR, 1.5; 95% CI, 1.3-1.8) compared with ever smokers without nonobstructive chronic bronchitis. Among 11 243 never smokers with 120 004 person-years of follow-up, participants with nonobstructive chronic bronchitis (151 [1.3%]) had greater rates of chronic lower respiratory disease-related hospitalization or mortality (HR, 3.1; 95% CI, 2.1-4.5) compared with never smokers without nonobstructive chronic bronchitis. Nonobstructive chronic bronchitis was not associated with FEV1:FVC decline or incident airflow obstruction. The presence of at least 1 of the component symptoms of nonobstructive chronic bronchitis (ie, chronic cough or phlegm), which was common in both ever smokers (11.0%) and never smokers (6.7%), was associated with adverse respiratory health outcomes. CONCLUSIONS AND RELEVANCE The findings suggest that nonobstructive chronic bronchitis is associated with adverse respiratory health outcomes, particularly in ever smokers, and may be a high-risk phenotype suitable for risk stratification and targeted therapies.
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Affiliation(s)
- Pallavi P Balte
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Paulo H M Chaves
- Benjamin Leon Jr Family Center for Geriatric Research and Education, Florida International University, Miami, Florida
| | - David J Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill
| | - Paul Enright
- Department of Medicine, University of Arizona, Tucson, Arizona
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois
| | - Richard A Kronmal
- Department of Biostatistics, School of Public Health, University of Washington, Seattle
| | - Laura R Loehr
- Division of General Medicine and Clinical Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill
| | - Stephanie J London
- Epidemiology Branch, Genetics, Environment, and Respiratory Disease Group, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | - Anne B Newman
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | - Joseph E Schwartz
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Benjamin M Smith
- Department of Medicine, McGill University Health Centre Research Institute, Montreal, Quebec, Canada
| | - Lewis J Smith
- Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois
| | - Wendy B White
- Jackson Heart Study Undergraduate Training and Education Center, Tougaloo College, Tougaloo, Mississippi
| | - Sachin Yende
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, New York
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15
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Donnelly JP, Dai Y, Colantonio LD, Zhao H, Safford MM, Baddley JW, Muntner P, Wang HE. Agreement of claims-based methods for identifying sepsis with clinical criteria in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. BMC Med Res Methodol 2020; 20:54. [PMID: 32131746 PMCID: PMC7057471 DOI: 10.1186/s12874-020-00937-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 02/24/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Claims-based algorithms are commonly used to identify sepsis in health services research because the laboratory features required to define clinical criteria may not be available in administrative data. METHODS We evaluated claims-based sepsis algorithms among adults in the US aged ≥65 years with Medicare health insurance enrolled in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Suspected infections from baseline (2003-2007) through December 31, 2012 were analyzed. Two claims-based algorithms were evaluated: (1) infection plus organ dysfunction diagnoses or sepsis diagnoses (Medicare-Implicit/Explicit) and (2) Centers for Medicare and Medicaid Services Severe Sepsis/Septic Shock Measure diagnoses (Medicare-CMS). Three classifications based on clinical criteria were used as standards for comparison: (1) the sepsis-related organ failure assessment (SOFA) score (REGARDS-SOFA), (2) "quick" SOFA (REGARDS-qSOFA), and (3) Centers for Disease Control and Prevention electronic health record criteria (REGARDS-EHR). RESULTS There were 2217 suspected infections among 9522 participants included in the current study. The total number of suspected infections classified as sepsis was 468 for Medicare-Implicit/Explicit, 249 for Medicare-CMS, 541 for REGARDS-SOFA, 185 for REGARDS-qSOFA, and 331 for REGARDS-EHR. The overall agreement between Medicare-Implicit/Explicit and REGARDS-SOFA, REGARDS-qSOFA, and REGARDS-EHR was 77, 79, and 81%, respectively, sensitivity was 46, 53, and 57%, and specificity was 87, 82, and 85%. Comparing Medicare-CMS and REGARDS-SOFA, REGARDS-qSOFA, and REGARDS-EHR, agreement was 77, 87, and 85%, respectively, sensitivity was 27, 41, and 36%, and specificity was 94, 92, and 93%. Events meeting the REGARDS-SOFA classification had a lower 90-day mortality rate (140.7 per 100 person-years) compared with the Medicare-CMS (296.1 per 100 person-years), REGARDS-qSOFA (238.6 per 100 person-years), Medicare-Implicit/Explicit (219.4 per 100 person-years), and REGARDS-EHR classifications (201.8 per 100 person-years). CONCLUSION Claims-based sepsis algorithms have high agreement and specificity but low sensitivity when compared with clinical criteria. Both claims-based algorithms identified a patient population with similar 90-day mortality rates as compared with classifications based on qSOFA and EHR criteria but higher mortality relative to SOFA criteria.
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Affiliation(s)
- John P. Donnelly
- Department of Learning Health Sciences, University of Michigan Medical School, NCRC Building 14, #G100, G014-130, 2800 Plymouth Rd, Ann Arbor, MI 48109 USA
- Institute for Healthcare Policy & Innovation, University of Michigan, Ann Arbor, MI USA
| | - Yuling Dai
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL USA
| | - Lisandro D. Colantonio
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL USA
| | - Hong Zhao
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL USA
| | | | - John W. Baddley
- Department of Medicine, Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL USA
| | - Paul Muntner
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL USA
| | - Henry E. Wang
- Department of Emergency Medicine, The University of Texas Health Science Center at Houston, Houston, TX USA
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16
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Gothe H, Rajsic S, Vukicevic D, Schoenfelder T, Jahn B, Geiger-Gritsch S, Brixner D, Popper N, Endel G, Siebert U. Algorithms to identify COPD in health systems with and without access to ICD coding: a systematic review. BMC Health Serv Res 2019; 19:737. [PMID: 31640678 PMCID: PMC6805625 DOI: 10.1186/s12913-019-4574-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Accepted: 09/30/2019] [Indexed: 02/03/2023] Open
Abstract
Background Chronic obstructive pulmonary disease (COPD) causes significant morbidity and mortality worldwide. Estimation of incidence, prevalence and disease burden through routine insurance data is challenging because of under-diagnosis and under-treatment, particularly for early stage disease in health care systems where outpatient International Classification of Diseases (ICD) diagnoses are not collected. This poses the question of which criteria are commonly applied to identify COPD patients in claims datasets in the absence of ICD diagnoses, and which information can be used as a substitute. The aim of this systematic review is to summarize previously reported methodological approaches for the identification of COPD patients through routine data and to compile potential criteria for the identification of COPD patients if ICD codes are not available. Methods A systematic literature review was performed in Medline via PubMed and Google Scholar from January 2000 through October 2018, followed by a manual review of the included studies by at least two independent raters. Study characteristics and all identifying criteria used in the studies were systematically extracted from the publications, categorized, and compiled in evidence tables. Results In total, the systematic search yielded 151 publications. After title and abstract screening, 38 publications were included into the systematic assessment. In these studies, the most frequently used (22/38) criteria set to identify COPD patients included ICD codes, hospitalization, and ambulatory visits. Only four out of 38 studies used methods other than ICD coding. In a significant proportion of studies, the age range of the target population (33/38) and hospitalization (30/38) were provided. Ambulatory data were included in 24, physician claims in 22, and pharmaceutical data in 18 studies. Only five studies used spirometry, two used surgery and one used oxygen therapy. Conclusions A variety of different criteria is used for the identification of COPD from routine data. The most promising criteria set in data environments where ambulatory diagnosis codes are lacking is the consideration of additional illness-related information with special attention to pharmacotherapy data. Further health services research should focus on the application of more systematic internal and/or external validation approaches.
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Affiliation(s)
- Holger Gothe
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria. .,Medical Faculty "Carl Gustav Carus", Technical University Dresden, Loescherstrasse 18, D-01307, Dresden, Germany.
| | - Sasa Rajsic
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria
| | - Djurdja Vukicevic
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria
| | - Tonio Schoenfelder
- Medical Faculty "Carl Gustav Carus", Technical University Dresden, Loescherstrasse 18, D-01307, Dresden, Germany
| | - Beate Jahn
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria
| | - Sabine Geiger-Gritsch
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria
| | - Diana Brixner
- University of Utah, School of Medicine, Salt Lake City, UT, 84132, USA
| | - Niki Popper
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria.,, dwh Gmbh, Neustiftgasse 57-59, A-1070, Vienna, Austria.,TU Wien, Research Unit of Information and Software Engineering, Vienna, Austria
| | - Gottfried Endel
- Evidence-Based Medicine and Health Technology Assessment, Main Association of Austrian Social Insurance Institutions, Kundmanngasse 21, A-1031, Vienna, Austria
| | - Uwe Siebert
- Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Zentrum 1, A-6060, Hall i.T., Austria.,Division of Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.,Center for Health Decision Science, Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, 718 Huntington Ave, Boston, MA, 02115, USA.,Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac St, Boston, MA, 02114, USA
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17
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Mendy A, Gopal R, Alcorn JF, Forno E. Reduced mortality from lower respiratory tract disease in adult diabetic patients treated with metformin. Respirology 2019; 24:646-651. [PMID: 30761687 PMCID: PMC6579707 DOI: 10.1111/resp.13486] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 11/21/2018] [Accepted: 01/08/2019] [Indexed: 01/11/2023]
Abstract
BACKGROUND AND OBJECTIVE Chronic lower respiratory diseases (CLRD) increase the risk of type 2 diabetes, which in turn may worsen lung function. Metformin, a common antidiabetic with anti-inflammatory and antioxidant properties, may improve respiratory outcomes. Therefore, we examined the association of metformin use with the risk of mortality from CLRD. METHODS We analysed data from the National Health and Nutrition Examination Survey during 1988-1994 and 1999-2010 for participants aged 40 years or older who had diabetes and were followed up for mortality through 2011. Information on prescription medicine was collected at baseline and CLRD-related mortality during follow-up was defined using the 10th Revision of the International Classification of Diseases (ICD-10). Cox proportional hazards modelling was used to determine the mortality hazard ratio (HR) associated with metformin use, adjusting for relevant covariates. RESULTS A total of 5266 participants with a median follow-up of 6.1 years were included. The prevalence of metformin use was 31.9% and 1869 participants died during follow-up, including 72 of CLRD. In the adjusted Cox proportional regression analysis, metformin was associated with a decreased risk of CLRD mortality in the overall population (HR: 0.39, 95% CI: 0.15-0.99) and among participants with baseline CLRD (HR: 0.30, 95% CI: 0.10-0.93), after adjusting for age, gender, race/ethnicity, cigarette smoking, body mass index, current asthma and chronic obstructive pulmonary disease (COPD), insulin and other diabetic medications, and glycohaemoglobin level. We found no association between other antidiabetic medications and CLRD mortality. CONCLUSION In this sample representative of the U.S. population, metformin was associated with lower CLRD mortality in adults with diabetes.
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Affiliation(s)
- Angelico Mendy
- College of Public Health, University of Iowa, Iowa City, IA
| | - Radha Gopal
- Division of Pulmonary Medicine, Dept. of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - John F. Alcorn
- Division of Pulmonary Medicine, Dept. of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Erick Forno
- Division of Pulmonary Medicine, Dept. of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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18
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Bhatt SP, Balte PP, Schwartz JE, Cassano PA, Couper D, Jacobs DR, Kalhan R, O’Connor GT, Yende S, Sanders JL, Umans JG, Dransfield MT, Chaves PH, White WB, Oelsner EC. Discriminative Accuracy of FEV1:FVC Thresholds for COPD-Related Hospitalization and Mortality. JAMA 2019; 321:2438-2447. [PMID: 31237643 PMCID: PMC6593636 DOI: 10.1001/jama.2019.7233] [Citation(s) in RCA: 118] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 05/23/2019] [Indexed: 12/12/2022]
Abstract
Importance According to numerous current guidelines, the diagnosis of chronic obstructive pulmonary disease (COPD) requires a ratio of the forced expiratory volume in the first second to the forced vital capacity (FEV1:FVC) of less than 0.70, yet this fixed threshold is based on expert opinion and remains controversial. Objective To determine the discriminative accuracy of various FEV1:FVC fixed thresholds for predicting COPD-related hospitalization and mortality. Design, Setting, and Participants The National Heart, Lung, and Blood Institute (NHLBI) Pooled Cohorts Study harmonized and pooled data from 4 US general population-based cohorts (Atherosclerosis Risk in Communities Study; Cardiovascular Health Study; Health, Aging, and Body Composition Study; and Multi-Ethnic Study of Atherosclerosis). Participants aged 45 to 102 years were enrolled from 1987 to 2000 and received follow-up longitudinally through 2016. Exposures Presence of airflow obstruction, which was defined by a baseline FEV1:FVC less than a range of fixed thresholds (0.75 to 0.65) or less than the lower limit of normal as defined by Global Lung Initiative reference equations (LLN). Main Outcomes and Measures The primary outcome was a composite of COPD hospitalization and COPD-related mortality, defined by adjudication or administrative criteria. The optimal fixed FEV1:FVC threshold was defined by the best discrimination for these COPD-related events as indexed using the Harrell C statistic from unadjusted Cox proportional hazards models. Differences in C statistics were compared with respect to less than 0.70 and less than LLN thresholds using a nonparametric approach. Results Among 24 207 adults in the pooled cohort (mean [SD] age at enrollment, 63 [10.5] years; 12 990 [54%] women; 16 794 [69%] non-Hispanic white; 15 181 [63%] ever smokers), complete follow-up was available for 11 077 (77%) at 15 years. During a median follow-up of 15 years, 3925 participants experienced COPD-related events over 340 757 person-years of follow-up (incidence density rate, 11.5 per 1000 person-years), including 3563 COPD-related hospitalizations and 447 COPD-related deaths. With respect to discrimination of COPD-related events, the optimal fixed threshold (0.71; C statistic for optimal fixed threshold, 0.696) was not significantly different from the 0.70 threshold (difference, 0.001 [95% CI, -0.002 to 0.004]) but was more accurate than the LLN threshold (difference, 0.034 [95% CI, 0.028 to 0.041]). The 0.70 threshold provided optimal discrimination in the subgroup analysis of ever smokers and in adjusted models. Conclusions and Relevance Defining airflow obstruction as FEV1:FVC less than 0.70 provided discrimination of COPD-related hospitalization and mortality that was not significantly different or was more accurate than other fixed thresholds and the LLN. These results support the use of FEV1:FVC less than 0.70 to identify individuals at risk of clinically significant COPD.
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Affiliation(s)
- Surya P. Bhatt
- Division of Pulmonary, Allergy, and Critical Care Medicine and the UAB Lung Health Center, University of Alabama at Birmingham
| | - Pallavi P. Balte
- Division of General Medicine, Columbia University Medical Center, New York, New York
| | - Joseph E. Schwartz
- Division of General Medicine, Columbia University Medical Center, New York, New York
| | - Patricia A. Cassano
- Division of Nutritional Sciences, Weill Cornell Medical College, Ithaca, New York
| | - David Couper
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois
| | - George T. O’Connor
- Division of Pulmonary, Allergy, Sleep, and Critical Care, Boston University, Boston, Massachusetts
| | - Sachin Yende
- Department of Critical Care Medicine, University of Pittsburgh and Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | - Jason L. Sanders
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Jason G. Umans
- MedStar Health Research Institute, Hyattsville, Maryland
| | - Mark T. Dransfield
- Division of Pulmonary, Allergy, and Critical Care Medicine and the UAB Lung Health Center, University of Alabama at Birmingham
| | - Paulo H. Chaves
- Benjamin Leon Center for Geriatric Research and Education, Florida International University, Miami
| | - Wendy B. White
- Undergraduate Training and Education Center, Tougaloo College, Tougaloo, Mississippi
| | - Elizabeth C. Oelsner
- Division of General Medicine, Columbia University Medical Center, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, New York
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19
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Oelsner EC, Balte PP, Grams ME, Cassano PA, Jacobs DR, Barr RG, Burkart KM, Kalhan R, Kronmal R, Loehr LR, O’Connor GT, Schwartz JE, Shlipak M, Tracy RP, Tsai MY, White W, Yende S. Albuminuria, Lung Function Decline, and Risk of Incident Chronic Obstructive Pulmonary Disease. The NHLBI Pooled Cohorts Study. Am J Respir Crit Care Med 2019; 199:321-332. [PMID: 30261735 PMCID: PMC6363973 DOI: 10.1164/rccm.201803-0402oc] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 09/28/2018] [Indexed: 12/30/2022] Open
Abstract
RATIONALE Chronic lower respiratory diseases (CLRDs), including chronic obstructive pulmonary disease (COPD) and asthma, are the fourth leading cause of death. Prior studies suggest that albuminuria, a biomarker of endothelial injury, is increased in patients with COPD. OBJECTIVES To test whether albuminuria was associated with lung function decline and incident CLRDs. METHODS Six U.S. population-based cohorts were harmonized and pooled. Participants with prevalent clinical lung disease were excluded. Albuminuria (urine albumin-to-creatinine ratio) was measured in spot samples. Lung function was assessed by spirometry. Incident CLRD-related hospitalizations and deaths were classified via adjudication and/or administrative criteria. Mixed and proportional hazards models were used to test individual-level associations adjusted for age, height, weight, sex, race/ethnicity, education, birth year, cohort, smoking status, pack-years of smoking, renal function, hypertension, diabetes, and medications. MEASUREMENTS AND MAIN RESULTS Among 10,961 participants with preserved lung function, mean age at albuminuria measurement was 60 years, 51% were never-smokers, median albuminuria was 5.6 mg/g, and mean FEV1 decline was 31.5 ml/yr. For each SD increase in log-transformed albuminuria, there was 2.81% greater FEV1 decline (95% confidence interval [CI], 0.86-4.76%; P = 0.0047), 11.02% greater FEV1/FVC decline (95% CI, 4.43-17.62%; P = 0.0011), and 15% increased hazard of incident spirometry-defined moderate-to-severe COPD (95% CI, 2-31%, P = 0.0021). Each SD log-transformed albuminuria increased hazards of incident COPD-related hospitalization/mortality by 26% (95% CI, 18-34%, P < 0.0001) among 14,213 participants followed for events. Asthma events were not significantly associated. Associations persisted in participants without current smoking, diabetes, hypertension, or cardiovascular disease. CONCLUSIONS Albuminuria was associated with greater lung function decline, incident spirometry-defined COPD, and incident COPD-related events in a U.S. population-based sample.
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Affiliation(s)
- Elizabeth C. Oelsner
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Pallavi P. Balte
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Morgan E. Grams
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Patricia A. Cassano
- Division of Nutritional Sciences, College of Human Ecology, Cornell University, Cornell, New York
| | | | - R. Graham Barr
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Kristin M. Burkart
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Ravi Kalhan
- Department of Medicine, Northwestern University, Chicago, Illinois
| | - Richard Kronmal
- Department of Statistics, School of Public Health, University of Washington, Seattle, Washington
| | - Laura R. Loehr
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
| | | | - Joseph E. Schwartz
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Department of Psychiatry and Behavioral Sciences, Stony Brook University, Stony Brook, New York
| | - Michael Shlipak
- Department of Medicine, University of California, San Francisco, San Francisco, California
| | - Russell P. Tracy
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, Vermont
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota
| | - Wendy White
- Jackson Heart Study, Undergraduate Training and Education Center, Tougaloo College, Jackson, Mississippi; and
| | - Sachin Yende
- Veterans Affairs Pittsburgh Healthcare System and
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
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20
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Guillien A, Soumagne T, Dalphin JC, Degano B. COPD, airflow limitation and chronic bronchitis in farmers: a systematic review and meta-analysis. Occup Environ Med 2018; 76:58-68. [DOI: 10.1136/oemed-2018-105310] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 10/27/2018] [Accepted: 11/06/2018] [Indexed: 01/11/2023]
Abstract
IntroductionThe current definition of chronic obstructive pulmonary disease (COPD) associates persistent airflow limitation and chronic respiratory symptoms. Agricultural work has been associated with an increased risk of developing COPD, but the prevalence and definition of the disease vary greatly between studies. This meta-analysis aimed to assess the association between agricultural work and COPD using the most widely used definitions of the disease.MethodsInclusion criteria were: (1) design: cross-sectional or longitudinal, (2) groups: at least one group of farmers and a control group of non-farmers, (3) outcome: prevalence or unadjusted OR of COPD, airflow limitation and/or chronic bronchitis, (4) study subjects: groups of exposed subjects comprising ≥30 individuals and with a mean age ≥40 years and (5) language: English and French language, full-length, original publications in peer-reviewed journals.ResultsIn total, 22 manuscripts were included in the meta-analysis. Eight studies assessed only the prevalence of airflow limitation, nine assessed only the prevalence of chronic bronchitis and four assessed the prevalence of both these parameters. Only one assessed the prevalence of COPD according to its current definition, and this study also provided the prevalence of airflow limitation. Ten studies showed a positive association between farming exposure and airflow limitation or chronic bronchitis, and 12 showed no association (OR (95% CI)=1.77 (1.50 to 2.08), p<0.001). Cattle, swine, poultry and crop farming were associated with either airflow limitation or chronic bronchitis.ConclusionAlthough some features of COPD are associated with some agricultural work, well-designed studies with appropriate diagnostic criteria should be conducted to draw strong conclusions about the relationship between COPD and farming.
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21
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Oelsner EC, Balte PP, Cassano PA, Couper D, Enright PL, Folsom AR, Hankinson J, Jacobs DR, Kalhan R, Kaplan R, Kronmal R, Lange L, Loehr LR, London SJ, Navas Acien A, Newman AB, O’Connor GT, Schwartz JE, Smith LJ, Yeh F, Zhang Y, Moran AE, Mwasongwe S, White WB, Yende S, Barr RG. Harmonization of Respiratory Data From 9 US Population-Based Cohorts: The NHLBI Pooled Cohorts Study. Am J Epidemiol 2018; 187:2265-2278. [PMID: 29982273 PMCID: PMC6211239 DOI: 10.1093/aje/kwy139] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 04/13/2018] [Accepted: 04/17/2018] [Indexed: 12/13/2022] Open
Abstract
Chronic lower respiratory diseases (CLRDs) are the fourth leading cause of death in the United States. To support investigations into CLRD risk determinants and new approaches to primary prevention, we aimed to harmonize and pool respiratory data from US general population-based cohorts. Data were obtained from prospective cohorts that performed prebronchodilator spirometry and were harmonized following 2005 ATS/ERS standards. In cohorts conducting follow-up for noncardiovascular events, CLRD events were defined as hospitalizations/deaths adjudicated as CLRD-related or assigned relevant administrative codes. Coding and variable names were applied uniformly. The pooled sample included 65,251 adults in 9 cohorts followed-up for CLRD-related mortality over 653,380 person-years during 1983-2016. Average baseline age was 52 years; 56% were female; 49% were never-smokers; and racial/ethnic composition was 44% white, 22% black, 28% Hispanic/Latino, and 5% American Indian. Over 96% had complete data on smoking, clinical CLRD diagnoses, and dyspnea. After excluding invalid spirometry examinations (13%), there were 105,696 valid examinations (median, 2 per participant). Of 29,351 participants followed for CLRD hospitalizations, median follow-up was 14 years; only 5% were lost to follow-up at 10 years. The NHLBI Pooled Cohorts Study provides a harmonization standard applied to a large, US population-based sample that may be used to advance epidemiologic research on CLRD.
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MESH Headings
- Adolescent
- Adult
- Aged
- Aged, 80 and over
- Body Weights and Measures
- Bronchiectasis/epidemiology
- Bronchiectasis/physiopathology
- Chronic Disease
- Cohort Studies
- Ethnicity/statistics & numerical data
- Female
- Hispanic or Latino/statistics & numerical data
- Hospitalization/statistics & numerical data
- Humans
- Indians, North American/statistics & numerical data
- Inhalation Exposure/statistics & numerical data
- Lung Diseases, Obstructive/epidemiology
- Lung Diseases, Obstructive/ethnology
- Lung Diseases, Obstructive/mortality
- Lung Diseases, Obstructive/physiopathology
- Male
- Middle Aged
- National Heart, Lung, and Blood Institute (U.S.)/organization & administration
- National Heart, Lung, and Blood Institute (U.S.)/standards
- Phenotype
- Racial Groups/statistics & numerical data
- Respiratory Function Tests
- Risk Factors
- Smoking/epidemiology
- Socioeconomic Factors
- United States/epidemiology
- White People/statistics & numerical data
- Young Adult
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Affiliation(s)
- Elizabeth C Oelsner
- Division of General Medicine, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Pallavi P Balte
- Division of General Medicine, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Patricia A Cassano
- Division of Nutritional Sciences, Weill Cornell Medical College, Ithaca, New York
| | - David Couper
- Collaborative Studies Coordinating Center, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina
| | - Paul L Enright
- Department of Medicine, College of Medicine, University of Arizona, Tucson, Arizona
| | - Aaron R Folsom
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | | | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | | | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, New York
| | - Richard Kronmal
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington
| | - Leslie Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado, Denver, Colorado
| | - Laura R Loehr
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina
| | - Stephanie J London
- National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina
| | - Ana Navas Acien
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York
| | - Anne B Newman
- Department of Epidemiology, Pitt Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - George T O’Connor
- Department of Medicine, School of Medicine, Boston University, Boston, Massachusetts
| | - Joseph E Schwartz
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stony Brook University, Stony Brook, New York
| | | | - Fawn Yeh
- Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Yiyi Zhang
- Division of General Medicine, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Andrew E Moran
- Division of General Medicine, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | | | - Wendy B White
- Jackson Heart Study, Undergraduate Training and Education Center, Tougaloo College, Tougaloo, Mississippi
| | - Sachin Yende
- Division of Pulmonary and Critical Care, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - R Graham Barr
- Division of General Medicine, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
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Sundaresan AS, Schneider G, Reynolds J, Kirchner HL. Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data. Appl Clin Inform 2018; 9:528-540. [PMID: 30040112 PMCID: PMC6051766 DOI: 10.1055/s-0038-1666994] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Background
Asthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.
Objective
We propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.
Methods
We performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.
Results
There were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91–0.94) and 0.94 (0.93–0.96), respectively, for EMR and claims data, with positive predictive value of > 94%. The algorithms are visually presented using nomograms.
Conclusion
We were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.
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Affiliation(s)
- Agnes S Sundaresan
- Department of Epidemiology and Health Services Research, Geisinger Health System, Danville, Pennsylvania, United States.,Medicine Institute, Geisinger Health System, Danville, Pennsylvania, United States
| | - Gargi Schneider
- MedPeds Program, Geisinger Medical Center, Danville, Pennsylvania, United States
| | - Joy Reynolds
- Lewis Katz School of Medicine at Temple University, Temple University, Philadelphia, Pennsylvania, United States
| | - H Lester Kirchner
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, Pennsylvania, United States.,Department of Clinical Sciences, Geisinger Commonwealth School of Medicine, Geisinger Health System, Scranton, Pennsylvania, United States.,Department of Pediatrics, Global and Immigrant Health Section, Baylor College of Medicine, Houston, Texas, United States
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Oelsner EC, Smith BM, Hoffman EA, Kalhan R, Donohue KM, Kaufman JD, Nguyen JN, Manichaikul AW, Rotter JI, Michos ED, Jacobs DR, Burke GL, Folsom AR, Schwartz JE, Watson K, Barr RG. Prognostic Significance of Large Airway Dimensions on Computed Tomography in the General Population. The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study. Ann Am Thorac Soc 2018; 15:718-727. [PMID: 29529382 PMCID: PMC6137677 DOI: 10.1513/annalsats.201710-820oc] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Accepted: 03/12/2018] [Indexed: 12/22/2022] Open
Abstract
RATIONALE Large airway dimensions on computed tomography (CT) have been associated with lung function, symptoms, and exacerbations in chronic obstructive pulmonary disease (COPD), as well as with symptoms in smokers with preserved spirometry. Their prognostic significance in persons without lung disease remains undefined. OBJECTIVES To examine associations between large airway dimensions on CT and respiratory outcomes in a population-based cohort of adults without prevalent lung disease. METHODS The Multi-Ethnic Study of Atherosclerosis recruited participants ages 45-84 years without cardiovascular disease in 2000-2002; we excluded participants with prevalent chronic lower respiratory disease (CLRD). Spirometry was measured in 2004-2006 and 2010-2012. CLRD hospitalizations and deaths were classified by validated criteria through 2014. The average wall thickness for a hypothetical airway of 10-mm lumen perimeter on CT (Pi10) was calculated using measures of airway wall thickness and lumen diameter. Models were adjusted for age, sex, principal components of ancestry, body mass index, smoking, pack-years, scanner, percent emphysema, genetic risk score, and initial forced expiratory volume in 1 second (FEV1) percent predicted. RESULTS Greater Pi10 was associated with 9% faster FEV1 decline (95% confidence interval [CI], 2 to 15%; P = 0.012) and increased incident COPD (odds ratio, 2.22; 95% CI, 1.43-3.45; P = 0.0004) per standard deviation among 1,830 participants. Over 78,147 person-years, higher Pi10 was associated with a 57% higher risk of first CLRD hospitalization or mortality (P = 0.0496) per standard deviation. Of Pi10's component measures, both greater airway wall thickness and narrower lumen predicted incident COPD and CLRD clinical events. CONCLUSIONS In adults without CLRD, large airway dimensions on CT were prospectively associated with accelerated lung function decline and increased risks of COPD and CLRD hospitalization and mortality.
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Affiliation(s)
- Elizabeth C. Oelsner
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Benjamin M. Smith
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Respiratory Division, McGill University, Montreal, Quebec, Canada
| | - Eric A. Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa
| | - Ravi Kalhan
- Division of Pulmonary, Northwestern University, Chicago, Illinois
| | - Kathleen M. Donohue
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Joel D. Kaufman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington
| | - Jennifer N. Nguyen
- Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Ani W. Manichaikul
- Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Jerome I. Rotter
- Division of Genomic Outcomes, University of California, Los Angeles, School of Medicine, Torrance, California
| | - Erin D. Michos
- Department of Cardiology, Johns Hopkins University, Baltimore, Maryland
| | - David R. Jacobs
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Gregory L. Burke
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; and
| | - Aaron R. Folsom
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Joseph E. Schwartz
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Karol Watson
- Division of Cardiology, University of California, Los Angeles, School of Medicine, Los Angeles, California
| | - R. Graham Barr
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
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Clement A, de Blic J, Epaud R, Galeron L, Nathan N, Hadchouel A, Barbato A, Snijders D, Kiper N, Cunningham S, Griese M, Bush A, Schwerk N. Management of children with interstitial lung diseases: the difficult issue of acute exacerbations. Eur Respir J 2016; 48:1559-1563. [DOI: 10.1183/13993003.01900-2016] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 10/16/2016] [Indexed: 11/05/2022]
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