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      Comorbidities associated with mortality in 31,461 adults with COVID-19 in the United States: A federated electronic medical record analysis

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          Abstract

          Background

          At the beginning of June 2020, there were nearly 7 million reported cases of coronavirus disease 2019 (COVID-19) worldwide and over 400,000 deaths in people with COVID-19. The objective of this study was to determine associations between comorbidities listed in the Charlson comorbidity index and mortality among patients in the United States with COVID-19.

          Methods and findings

          A retrospective cohort study of adults with COVID-19 from 24 healthcare organizations in the US was conducted. The study included adults aged 18–90 years with COVID-19 coded in their electronic medical records between January 20, 2020, and May 26, 2020. Results were also stratified by age groups (<50 years, 50–69 years, or 70–90 years). A total of 31,461 patients were included. Median age was 50 years (interquartile range [IQR], 35–63) and 54.5% ( n = 17,155) were female. The most common comorbidities listed in the Charlson comorbidity index were chronic pulmonary disease (17.5%, n = 5,513) and diabetes mellitus (15.0%, n = 4,710). Multivariate logistic regression analyses showed older age (odds ratio [OR] per year 1.06; 95% confidence interval [CI] 1.06–1.07; p < 0.001), male sex (OR 1.75; 95% CI 1.55–1.98; p < 0.001), being black or African American compared to white (OR 1.50; 95% CI 1.31–1.71; p < 0.001), myocardial infarction (OR 1.97; 95% CI 1.64–2.35; p < 0.001), congestive heart failure (OR 1.42; 95% CI 1.21–1.67; p < 0.001), dementia (OR 1.29; 95% CI 1.07–1.56; p = 0.008), chronic pulmonary disease (OR 1.24; 95% CI 1.08–1.43; p = 0.003), mild liver disease (OR 1.26; 95% CI 1.00–1.59; p = 0.046), moderate/severe liver disease (OR 2.62; 95% CI 1.53–4.47; p < 0.001), renal disease (OR 2.13; 95% CI 1.84–2.46; p < 0.001), and metastatic solid tumor (OR 1.70; 95% CI 1.19–2.43; p = 0.004) were associated with higher odds of mortality with COVID-19. Older age, male sex, and being black or African American (compared to being white) remained significantly associated with higher odds of death in age-stratified analyses. There were differences in which comorbidities were significantly associated with mortality between age groups. Limitations include that the data were collected from the healthcare organization electronic medical record databases and some comorbidities may be underreported and ethnicity was unknown for 24% of participants. Deaths during an inpatient or outpatient visit at the participating healthcare organizations were recorded; however, deaths occurring outside of the hospital setting are not well captured.

          Conclusions

          Identifying patient characteristics and conditions associated with mortality with COVID-19 is important for hypothesis generating for clinical trials and to develop targeted intervention strategies.

          Abstract

          In this analysis of electronic health records, Stephanie Harrison and colleagues investigate comorbidities and mortality in COVID-19 patients.

          Author summary

          Why was this study done?
          • Coronavirus disease 2019 (COVID-19) has led to a public health emergency internationally.

          • As of June 2020, there were over 400,000 deaths reported with COVID-19 globally and over 110,000 deaths were in the US, but many people have also recovered.

          • Because of the unprecedented outbreak of COVID-19 worldwide, little is known about which underlying health conditions may impact a person’s likelihood of dying with COVID-19.

          • Some previous studies have suggested being older; being from a black, Asian, or minority ethnic (BAME) background; and having certain health conditions may increase risk of death with COVID-19, but further evidence is needed to understand factors which influence this.

          What did the researchers do and find?
          • The research utilized a network of 24 healthcare organizations in the US, which provided deidentified data from electronic medical records of patients.

          • A total of 31,461 adults with COVID-19 coded in their electronic medical records were included in the study after a search of the network between January 20, 2020, and May 26, 2020.

          • We determined associations between age, sex, ethnicity, comorbidities, and death with COVID-19 during the study period.

          • After accounting for the other included factors in the study, being older, being male, being black or African American, and having a history of myocardial infarction, congestive heart failure, dementia, chronic pulmonary disease, mild liver disease, moderate/severe liver disease, renal disease, or metastatic solid tumor were all associated with higher odds of death with COVID-19.

          • There were differences in which comorbidities were associated with death when we stratified the results by age group.

          What do these findings mean?
          • Identifying factors associated with death with COVID-19 could help with hypothesis generating for clinical trials and identify patients who may need to be targeted for early intervention or monitoring.

          • The study has limitations; for example, some health conditions may be underreported or incorrectly coded in electronic medical records at the time of data entry, and all deaths of participants may not have been captured.

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          Most cited references14

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          Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

          Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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            • Article: not found

            A Novel Coronavirus from Patients with Pneumonia in China, 2019

            Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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              • Abstract: found
              • Article: not found

              Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

              Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                10 September 2020
                September 2020
                : 17
                : 9
                : e1003321
                Affiliations
                [1 ] Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
                [2 ] TriNetX, Inc., Cambridge, Massachusetts, United States of America
                [3 ] Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
                [4 ] TriNetX, Inc., London, United Kingdom
                Universitair Medisch Centrum Utrecht, NETHERLANDS
                Author notes

                I have read the journal's policy and the authors of this manuscript have the following competing interests. GYHL is a Consultant for Bayer/Janssen, BMS/Pfizer, Medtronic, Boehringer Ingelheim, Novartis, Verseon, and Daiichi-Sankyo and a Speaker for Bayer, BMS/Pfizer, Medtronic, Boehringer Ingelheim, and Daiichi-Sankyo. No fees are directly received personally. DAL has received investigator-initiated educational grants from Bristol-Myers Squibb (BMS) and Boehringer Ingelheim; has been a speaker for Boehringer Ingelheim and BMS/Pfizer; and has consulted for BMS, Boehringer Ingelheim, and Daiichi-Sankyo. EF-E and PU are employees of TriNetX. SLH has declared no competing interests.

                Author information
                http://orcid.org/0000-0002-8846-0946
                http://orcid.org/0000-0002-0594-0275
                http://orcid.org/0000-0002-5604-9378
                http://orcid.org/0000-0002-7566-1626
                Article
                PMEDICINE-D-20-02012
                10.1371/journal.pmed.1003321
                7482833
                32911500
                c2f5be71-2aff-4475-bd87-219fdb04cf38
                © 2020 Harrison et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 May 2020
                : 7 August 2020
                Page count
                Figures: 0, Tables: 2, Pages: 11
                Funding
                The authors received no specific funding for this work. TriNetX funded the acquisition of the data used.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Medicine and Health Sciences
                Health Care
                Health Information Technology
                Electronic Medical Records
                Computer and Information Sciences
                Information Technology
                Health Information Technology
                Electronic Medical Records
                Medicine and Health Sciences
                Gastroenterology and Hepatology
                Liver Diseases
                People and places
                Population groupings
                Ethnicities
                African American people
                People and Places
                Population Groupings
                Age Groups
                Medicine and Health Sciences
                Cardiology
                Myocardial Infarction
                Medicine and Health Sciences
                Cardiology
                Heart Failure
                Medicine and Health Sciences
                Epidemiology
                Ethnic Epidemiology
                Custom metadata
                The conditions under which the data were provided do not allow for the data to be made publicly available. The data we used for this paper were acquired from TriNetX ( https://www.trinetx.com/). Release and/or sharing of these data are not covered under our data use agreement with TriNetX. To gain access to the data, a request can be made to TriNetX ( join@ 123456trinetx.com ), but costs may be incurred, and a data sharing agreement would be necessary.
                COVID-19

                Medicine
                Medicine

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