An. Dataset.xlsx (1.79 MB)
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Mortality incidence, sociodemographic and clinical data in COVID-19 patients.

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modified on 12.01.2021, 14:51
This data record contains a single file, An. Dataset.xlsx, in .xlsx file format.

The data file contains information on demographics, comorbidities, admission laboratory values, admission medications, admission supplemental oxygen orders, discharge and mortality. The data were derived from a healthcare surveillance software package (Clinical Looking Glass [CLG]; Streamline Health, Atlanta, Georgia) and review of the primary medical records.
The data relate to COVID-19 patients admitted to a single healthcare system, over a specific period of time, and separated into the 1st 3 weeks of the pandemic and the 2nd 3 weeks of the pandemic.
Some of the variables included in the dataset are: length of hospital stay (LOS), myocardial infraction (MI), peripheral vascular disease (PVD), congestive heart failure (CHF), cardiovascular disease (CVD), dementia (Dement), Chronic obstructive pulmonary disease (COPD), diabetes mellitus simple (DM simple), diabetes mellitus complicated (DM complicated), oxygen saturation (OsSats), mean arterial pressure, in mmHg (MAP), D-dimer, in mg/ml (Ddimer), platelets, in k per mm3 (Plts), international normalized ratio (INR), blood urea nitrogen, in mg/dL (BUN), alanine aminotransferase, in U/liter (AST), while blood cells, in per mm3 (WBC) and interleukin-6, in pg/ml (IL-6).

Study aims and methodology:
COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. In this study, the authors propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality.
4,711 patients with confirmed SARS-CoV-2 infection were included in the study. The authors derived a risk model using the first half of the cohort (n=2,355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2,356 patients. This study was approved by the Montefiore Medical Center/Albert Einstein College of Medicine Institutional Review Board. The Institutional Review Board approved waiver of patient informed consent due to the retrospective design of the study
For more details on the methodology, please read the related article.

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