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Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records.
BMJ Open. 2020 10 26; 10(10):e040441.BO

Abstract

OBJECTIVE

To assess association of clinical features on COVID-19 patient outcomes.

DESIGN

Retrospective observational study using electronic medical record data.

SETTING

Five member hospitals from the Mount Sinai Health System in New York City (NYC).

PARTICIPANTS

28 336 patients tested for SARS-CoV-2 from 24 February 2020 to 15 April 2020, including 6158 laboratory-confirmed COVID-19 cases.

MAIN OUTCOMES AND MEASURES

Positive test rates and in-hospital mortality were assessed for different racial groups. Among positive cases admitted to the hospital (N=3273), we estimated HR for both discharge and death across various explanatory variables, including patient demographics, hospital site and unit, smoking status, vital signs, lab results and comorbidities.

RESULTS

Hispanics (29%) and African Americans (25%) had disproportionately high positive case rates relative to their representation in the overall NYC population (p<0.05); however, no differences in mortality rates were observed in hospitalised patients based on race. Outcomes differed significantly between hospitals (Gray's T=248.9; p<0.05), reflecting differences in average baseline age and underlying comorbidities. Significant risk factors for mortality included age (HR 1.05, 95% CI 1.04 to 1.06; p=1.15e-32), oxygen saturation (HR 0.985, 95% CI 0.982 to 0.988; p=1.57e-17), care in intensive care unit areas (HR 1.58, 95% CI 1.29 to 1.92; p=7.81e-6) and elevated creatinine (HR 1.75, 95% CI 1.47 to 2.10; p=7.48e-10), white cell count (HR 1.02, 95% CI 1.01 to 1.04; p=8.4e-3) and body mass index (BMI) (HR 1.02, 95% CI 1.00 to 1.03; p=1.09e-2). Deceased patients were more likely to have elevated markers of inflammation.

CONCLUSIONS

While race was associated with higher risk of infection, we did not find racial disparities in inpatient mortality suggesting that outcomes in a single tertiary care health system are comparable across races. In addition, we identified key clinical features associated with reduced mortality and discharge. These findings could help to identify which COVID-19 patients are at greatest risk of a severe infection response and predict survival.

Authors+Show Affiliations

Sema4, Stamford, Connecticut, USA.Sema4, Stamford, Connecticut, USA.Sema4, Stamford, Connecticut, USA.Sema4, Stamford, Connecticut, USA.Sema4, Stamford, Connecticut, USA. Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Mount Sinai Data Warehouse, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Mount Sinai Data Warehouse, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York, USA. The Hasso Plattner Institute for Digital Health at the Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA.The Office of the Dean, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Tisch Cancer Institute and Division of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Sema4, Stamford, Connecticut, USA. Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Sema4, Stamford, Connecticut, USA. Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.Sema4, Stamford, Connecticut, USA li.li@mssm.edu. Department of Genetics and Genomic Sciences, The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Pub Type(s)

Journal Article
Observational Study

Language

eng

PubMed ID

33109676

Citation

Wang, Zichen, et al. "Hospitalised COVID-19 Patients of the Mount Sinai Health System: a Retrospective Observational Study Using the Electronic Medical Records." BMJ Open, vol. 10, no. 10, 2020, pp. e040441.
Wang Z, Zheutlin A, Kao YH, et al. Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records. BMJ Open. 2020;10(10):e040441.
Wang, Z., Zheutlin, A., Kao, Y. H., Ayers, K., Gross, S., Kovatch, P., Nirenberg, S., Charney, A., Nadkarni, G., De Freitas, J. K., O'Reilly, P., Just, A., Horowitz, C., Martin, G., Branch, A., Glicksberg, B. S., Charney, D., Reich, D., Oh, W. K., ... Li, L. (2020). Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records. BMJ Open, 10(10), e040441. https://doi.org/10.1136/bmjopen-2020-040441
Wang Z, et al. Hospitalised COVID-19 Patients of the Mount Sinai Health System: a Retrospective Observational Study Using the Electronic Medical Records. BMJ Open. 2020 10 26;10(10):e040441. PubMed PMID: 33109676.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Hospitalised COVID-19 patients of the Mount Sinai Health System: a retrospective observational study using the electronic medical records. AU - Wang,Zichen, AU - Zheutlin,Amanda, AU - Kao,Yu-Han, AU - Ayers,Kristin, AU - Gross,Susan, AU - Kovatch,Patricia, AU - Nirenberg,Sharon, AU - Charney,Alexander, AU - Nadkarni,Girish, AU - De Freitas,Jessica K, AU - O'Reilly,Paul, AU - Just,Allan, AU - Horowitz,Carol, AU - Martin,Glenn, AU - Branch,Andrea, AU - Glicksberg,Benjamin S, AU - Charney,Dennis, AU - Reich,David, AU - Oh,William K, AU - Schadt,Eric, AU - Chen,Rong, AU - Li,Li, Y1 - 2020/10/26/ PY - 2020/10/28/entrez PY - 2020/10/29/pubmed PY - 2020/11/5/medline KW - COVID-19 KW - epidemiology KW - health informatics KW - infectious diseases SP - e040441 EP - e040441 JF - BMJ open JO - BMJ Open VL - 10 IS - 10 N2 - OBJECTIVE: To assess association of clinical features on COVID-19 patient outcomes. DESIGN: Retrospective observational study using electronic medical record data. SETTING: Five member hospitals from the Mount Sinai Health System in New York City (NYC). PARTICIPANTS: 28 336 patients tested for SARS-CoV-2 from 24 February 2020 to 15 April 2020, including 6158 laboratory-confirmed COVID-19 cases. MAIN OUTCOMES AND MEASURES: Positive test rates and in-hospital mortality were assessed for different racial groups. Among positive cases admitted to the hospital (N=3273), we estimated HR for both discharge and death across various explanatory variables, including patient demographics, hospital site and unit, smoking status, vital signs, lab results and comorbidities. RESULTS: Hispanics (29%) and African Americans (25%) had disproportionately high positive case rates relative to their representation in the overall NYC population (p<0.05); however, no differences in mortality rates were observed in hospitalised patients based on race. Outcomes differed significantly between hospitals (Gray's T=248.9; p<0.05), reflecting differences in average baseline age and underlying comorbidities. Significant risk factors for mortality included age (HR 1.05, 95% CI 1.04 to 1.06; p=1.15e-32), oxygen saturation (HR 0.985, 95% CI 0.982 to 0.988; p=1.57e-17), care in intensive care unit areas (HR 1.58, 95% CI 1.29 to 1.92; p=7.81e-6) and elevated creatinine (HR 1.75, 95% CI 1.47 to 2.10; p=7.48e-10), white cell count (HR 1.02, 95% CI 1.01 to 1.04; p=8.4e-3) and body mass index (BMI) (HR 1.02, 95% CI 1.00 to 1.03; p=1.09e-2). Deceased patients were more likely to have elevated markers of inflammation. CONCLUSIONS: While race was associated with higher risk of infection, we did not find racial disparities in inpatient mortality suggesting that outcomes in a single tertiary care health system are comparable across races. In addition, we identified key clinical features associated with reduced mortality and discharge. These findings could help to identify which COVID-19 patients are at greatest risk of a severe infection response and predict survival. SN - 2044-6055 UR - https://www.unboundmedicine.com/medline/citation/33109676/Hospitalised_COVID_19_patients_of_the_Mount_Sinai_Health_System:_a_retrospective_observational_study_using_the_electronic_medical_records_ L2 - https://bmjopen.bmj.com/lookup/pmidlookup?view=long&amp;pmid=33109676 DB - PRIME DP - Unbound Medicine ER -