Predict the hospitalization in COVID-19: Magic is in the air

ABSTRACT

Background: Although pathogenesis and pattern of disease are still not completely understood, tactical management of overcrowding of hospitals and rational usage of resources is the need of the hour. Aims and Objectives: The study objectives were as follows Finding of correlation between various attributes of COVID; evaluation of the association of common characteristics with hospital stay; prediction of cooccurrence of different symptoms; calculation of odds ratio of prolonged hospitalization due to various symptoms; and estimation of the rate of prolonged hospitalization due to different symptoms and comorbidities. Materials and Methods: Retrospective data of 6918 COVID-19-positive cases from SCB Medical College and Hospital, India, were obtained from the hospital records from March 2020 to January 2021. The patients’ age, gender, symptoms, and comorbidities were analyzed against their hospital stay using R software (version 4.0.2). Results: Elderly patients (>65 years) had a higher rate (91.22%) of prolonged hospital stay as compared to others (47.61%). Frequently observed symptoms (in decreasing order) were fever (73.93%), cough (67.52%), myalgia (62.11%), dyspnea (49.59%), dizziness (47.38%), and anosmia (44.10%). The risk of prolonged hospitalization was highest with dyspnea [odds ratio 2.29 (95% confidence interval 2.07–2.52)], followed by diarrhea [odds ratio [OR] 1.98 (confidence interval [CI] 1.77–2.21)], fever [OR 1.89 (CI 1.69–2.10)], anosmia [OR 1.86 (CI 1.69–2.05)], and dizziness [OR 1.46 (CI 1.32–1.60)]. The rate of hospitalization for more than 7 days was highest with diabetes (86.80%) followed by respiratory illnesses (71.85%) and hypertension (71.28%). Conclusion: These findings can help manage patients based on their symptoms and comorbidities before admission.