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Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

Predictive Modeling of Morbidity and Mortality in Patients Hospitalized With COVID-19 and its Clinical Implications: Algorithm Development and Interpretation

A t-distributed stochastic neighbor embedding plot (Figure 3 A) suggests lack of clustering among lab features and overall low correlation (Figure 3 B) in pairwise comparisons (|μ|=0.08; |σ|=0.10). Local pockets of correlation (|r|≥0.83) were identified between hemoglobin, hematocrit, and red blood cell count; absolute neutrophils and white blood cell count; and bilirubin direct and bilirubin total. Each of these sets measures variables that are clinically interdependent and, thus, expected.

Joshua M Wang, Wenke Liu, Xiaoshan Chen, Michael P McRae, John T McDevitt, David Fenyö

J Med Internet Res 2021;23(7):e29514

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Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation

Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation

Normally distributed predictors were compared using an independent t test. Proportions were compared using the chi-squared test [24,25]. Two-sided tests were considered statistically significant for P We externally validated the Tier 1 Outpatient Model using data from a study of 160 hospitalized patients with COVID-19 from Zhongnan Hospital of Wuhan University. Only patients with complete information (age, systolic blood pressure, gender, diabetes, and cardiovascular comorbidities) were included.

Michael P McRae, Isaac P Dapkins, Iman Sharif, Judd Anderman, David Fenyo, Odai Sinokrot, Stella K Kang, Nicolaos J Christodoulides, Deniz Vurmaz, Glennon W Simmons, Timothy M. Alcorn, Marco J Daoura, Stu Gisburne, David Zar, John T McDevitt

J Med Internet Res 2020;22(8):e22033

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Article has an altmetric score of 2