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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.
Agarwal, Neeraj; Biswas, Bijit; Singh, Chandramani; Nair, Rathish; Mounica, Gera; H, Haripriya; Jha, Amit Ranjan; Das, Kumar M.
Afiliación
  • Agarwal N; All India Institute of Medical Sciences, Bibinagar, Telangana, India.
  • Biswas B; All India Institute of Medical Sciences, Patna, Bihar, India.
  • Singh C; All India Institute of Medical Sciences, Patna, Bihar, India.
  • Nair R; All India Institute of Medical Sciences, Patna, Bihar, India.
  • Mounica G; All India Institute of Medical Sciences, Patna, Bihar, India.
  • H H; All India Institute of Medical Sciences, Patna, Bihar, India.
  • Jha AR; All India Institute of Medical Sciences, Patna, Bihar, India.
  • Das KM; All India Institute of Medical Sciences, Patna, Bihar, India.
J Prim Care Community Health ; 12: 21501327211054281, 2021.
Article en En | MEDLINE | ID: mdl-34704488
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Prim Care Community Health Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Prim Care Community Health Año: 2021 Tipo del documento: Article País de afiliación: India Pais de publicación: Estados Unidos