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Table 1 A list of variables and their corresponding category utilized in predicting COVID-19 readmission risk

From: Predictive modeling for COVID-19 readmission risk using machine learning algorithms

Type Category Variables
Inputs Demographic characteristics Age, sex, height, weight, blood group, hospitalization length of stay (LOS)
Clinical manifestation Dry cough, nausea, headache, gastrointestinal (GI) manifestation, Chill, loss of taste and smell, rhinorrhea, sore throat, contusion, high body temperature, muscular pain, vomiting, dyspnea
Past medical history and comorbidities Cardiac disease, smoking, pneumonia, hypertension (diastolic/ systolic), alcohol addiction, diabetes, and other underline diseases
Laboratory results Red-cell count, hematocrit, hemoglobin, absolute lymphocyte count, blood calcium, blood potassium, absolute neutrophil count, alanine aminotransferase (ALT), magnesium, prothrombin time, alkaline phosphatase, platelet count, hypersensitive troponin creatinine, white cell count, aspartate aminotransferase (ASP), blood glucose, total bilirubin, erythrocyte sedimentation rate (ESR), C-reactive protein(CRP), albumin, thromboplastin time, lactate dehydrogenase (LDH), D-dimer, blood phosphorus, blood sodium, and blood urea nitrogen (BUN), oxygen saturation
Radiological factors Pleural fluid, consolidation
Treatment Oxygen therapy
Output Readmission: yes (1), no (0)