Author: Wang, Z.; Zheutlin, A. B.; Kao, Y.-H.; Ayers, K. L.; Gross, S. J.; Kovatch, P.; Nirenberg, S.; Charney, A. W.; Nadkarni, G. N.; O'Reilly, P. F.; Just, A. C.; Horowitz, C. R.; Martin, G.; Branch, A. D.; Glicksberg, B. S.; Charney, D. S.; Reich, D. L.; Oh, W. K.; Schadt, E. E.; Chen, R.; Li, L.
Title: Analysis of hospitalized COVID-19 patients in the Mount Sinai Health System using electronic medical records (EMR) reveals important prognostic factors for improved clinical outcomes Cord-id: 9pn30z0k Document date: 2020_5_4
ID: 9pn30z0k
Snippet: COVID-19 is a novel threat to human health worldwide. There is an urgent need to understand patient characteristics of having COVID-19 disease and evaluate markers of critical illness and mortality. Objective: To assess association of clinical features on patient outcomes. Design, Setting, and Participants: In this observational case series, patient-level data were extracted from electronic medical records for 28,336 patients tested for SARS-CoV-2 at the Mount Sinai Health System from 2/24/ to 4
Document: COVID-19 is a novel threat to human health worldwide. There is an urgent need to understand patient characteristics of having COVID-19 disease and evaluate markers of critical illness and mortality. Objective: To assess association of clinical features on patient outcomes. Design, Setting, and Participants: In this observational case series, patient-level data were extracted from electronic medical records for 28,336 patients tested for SARS-CoV-2 at the Mount Sinai Health System from 2/24/ to 4/15/2020, including 6,158 laboratory-confirmed cases. Exposures: Confirmed COVID-19 diagnosis by RT-PCR assay from nasal swabs. Main Outcomes and Measures: Effects of race on positive test rates and mortality were assessed. Among positive cases admitted to the hospital (N = 3,273), effects of patient demographics, hospital site and unit, social behavior, vital signs, lab results, and disease comorbidities on discharge and death were estimated. Results: Hispanics (29%) and African Americans (25%) had disproportionately high positive case rates relative to population base rates (p<2e-16); however, no differences in mortality rates were observed in the hospital. Outcome differed significantly between hospitals (Gray's T=248.9; p<2e-16), reflecting differences in average baseline age and underlying comorbidities. Significant risk factors for mortality included age (HR=1.05 [95% CI, 1.04-1.06]; p=1.15e-32), oxygen saturation (HR=0.985 [95% CI, 0.982-0.988]; p=1.57e-17), care in ICU areas (HR=1.58 [95% CI, 1.29-1.92]; p=7.81e-6), and elevated creatinine (HR=1.75 [95% CI, 1.47-2.10]; p=7.48e-10), alanine aminotransferase (ALT) (HR=1.002, [95% CI 1.001-1.003]; p=8.86e-5) and body-mass index (BMI) (HR=1.02, [95% CI 1.00-1.03]; p=1.09e-2). Asthma (HR=0.78 [95% CI, 0.62-0.98]; p=0.031) was significantly associated with increased length of hospital stay, but not mortality. Deceased patients were more likely to have elevated markers of inflammation. Baseline age, BMI, oxygen saturation, respiratory rate, white blood cell (WBC) count, creatinine, and ALT were significant prognostic indicators of mortality. Conclusions and Relevance: While race was associated with higher risk of infection, we did not find a racial disparity in inpatient mortality suggesting that outcomes in a single tertiary care health system are comparable across races. We identified clinical features associated with reduced mortality and discharge. These findings could help to identify which COVID-19 patients are at greatest risk and evaluate the impact on survival.
Search related documents:
Co phrase search for related documents- absence presence and local state: 1
- absence presence and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- absence presence and logistic regression model: 1, 2, 3, 4, 5, 6, 7
- absence presence and low mortality rate: 1
- additional information and local outbreak: 1
- additional information and local state: 1, 2, 3, 4
- additional information and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
- additional information and logistic regression model: 1, 2, 3
- additional information and low oxygen saturation: 1, 2
- additional strain and logistic regression: 1, 2
- local outbreak and logarithmic scale: 1
- local outbreak and logistic regression: 1, 2, 3, 4, 5
- local state and logistic regression: 1, 2, 3, 4, 5
- local state and logistic regression model: 1, 2, 3
- local state government and logistic regression: 1
- logistic regression and low mortality rate: 1, 2, 3, 4, 5, 6, 7, 8, 9
- logistic regression and low oxygen saturation: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
- logistic regression model and low mortality rate: 1, 2, 3
- logistic regression model and low oxygen saturation: 1
Co phrase search for related documents, hyperlinks ordered by date