Early Determinants of Length of Hospital Stay: A Case Control Survival Analysis among COVID-19 Patients admitted in a Tertiary Healthcare Facility of East India

• 主要な著者: Neeraj Agarwal (著者), Bijit Biswas (著者), Chandramani Singh (著者), Rathish Nair (著者), Gera Mounica (著者), Haripriya H (著者), Amit Ranjan Jha (著者), Kumar M. Das (著者)
• フォーマット: 図書
• 出版事項: SAGE Publishing, 2021-10-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.
• Notes: 2150-1327; 10.1177/21501327211054281
• Keywords: Computer applications to medicine. Medical informatics; R858-859.7; Public aspects of medicine; RA1-1270
• Source: Journal of Primary Care & Community Health, Vol 12 (2021)

Background: Length of hospital stay (LOS) for a disease is a vital estimate for healthcare logistics planning. The study aimed to illustrate the effect of factors elicited on arrival on LOS of the COVID-19 patients. Materials and Methods: It was a retrospective, record based, unmatched, case control study using hospital records of 334 COVID-19 patients admitted in an East Indian tertiary healthcare facility during May to October 2020. Discharge from the hospital (cases/survivors) was considered as an event while death (control/non-survivors) as right censoring in the case-control survival analysis using cox proportional hazard model. Results: Overall, we found the median LOS for the survivors to be 8 days [interquartile range (IQR): 7-10 days] while the same for the non-survivors was 6 days [IQR: 2-11 days]. In the multivariable cox-proportional hazard model; travel distance (>16 km) [adjusted hazard ratio (aHR): 0.69, 95% CI: (0.50-0.95)], mode of transport to the hospital (ambulance) [aHR: 0.62, 95% CI: (0.45-0.85)], breathlessness (yes) [aHR: 0.56, 95% CI: (0.40-0.77)], number of co-morbidities (1-2) [aHR: 0.66, 95% CI: (0.47-0.93)] (≥3) [aHR: 0.16, 95% CI: (0.04-0.65)], COPD/asthma (yes) [ [aHR: 0.11, 95% CI: (0.01-0.79)], DBP (<60/≥90) [aHR: 0.55, 95% CI: (0.35-0.86)] and qSOFA score (≥2) [aHR: 0.33, 95% CI: (0.12-0.92)] were the significant attributes affecting LOS of the COVID-19 patients. Conclusion: Factors elicited on arrival were found to be significantly associated with LOS. A scoring system inculcating these factors may be developed to predict LOS of the COVID-19 patients.