COVID-19 length of hospital stay: a systematic review and data synthesis

Abstract

Background: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care. Methods: We performed a systematic review of early evidence on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach, we provide distributions for total hospital and ICU LoS from studies in China and elsewhere, for use by the community. Results: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies-four each within and outside China-with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR 10-19) days for China, compared with 5 (IQR 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date. Conclusion: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.

Correlation between Chest CT Severity Scores and the Clinical Parameters of Adult Patients with COVID-19 Pneumonia

“…Concerning the length of hospital stay for patients with COVID-19 disease, a systematic review done by Rees et al has suggested that LOS varies depending on multiple factors such as admission and discharge criteria, bed demand and availability, and different timing within the pandemic [ 34 ]. Death rate in our cohort was significantly increased among patients with severe CT findings, as noted in other studies [ 35 ].…”

A systematic review and meta-analysis on chloroquine and hydroxychloroquine as monotherapy or combined with azithromycin in COVID-19 treatment

“…It is important to note that, a recently published systematic review of 52 studies concluded that duration of hospital stay and intensive care admission were also affected by other factors like time of epidemic and country of citizenship regardless the treatment protocol. Patients living in China had longer duration of hospital stay than other countries 69 .…”

Estimation of economic burden of COVID-19 using Disability-Adjusted Life Years (DALYs) and Productivity Losses in Kerala state, India

“…where S = average salary per day considering the number of paid working days per week as six; Lj = average recovery time; N = Number of incident cases; P = proportion of working population, in cohort 'j'. For computation of productivity losses, the proportion of working population was considered along with an extended disability period for severe cases to account for the ICU stay [20,21].…”