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

Rees, Eleanor M.; Nightingale, Emily; Jafari, Yalda; Waterlow, Naomi R.; Clifford, Samuel; Pearson, Carl A. B.; Jombert, Thibaut; Procter, Simon R.; Knight, Gwenan M.

doi:10.1101/2020.04.30.20084780

Cited by 63 publications

(69 citation statements)

References 74 publications

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“…We found a pooled mean ICU LoS of 7.8 (7 to 8.5) days comparable to results from a review reporting a median LoS of 8 (5 to 13) days for patients from China and 7 (4 to 11) days from outside China [44]. As for IMV duration, we found a pooled mean duration of 10 days (95% CI 7 to 13), which is shorter than earlier reports from Wuhan and Seattle of 10 to 17 days [41].…”

Section: Discussionsupporting

confidence: 84%

COVID-19 ICU and Mechanical Ventilation Patient Characteristics and Outcomes - A Systematic Review and Meta-analysis

Chang

Elhusseiny

Yeh

et al. 2020

Preprint

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Background To characterize COVID-19 ICU admissions, their outcome and associated features, as well as identify their regional discrepancies. Methods Scopus, Embase, preprint servers bioRvix and medRvix and the Intensive Care National Audit and Research Center (ICNARC) website was searched for reports through May 1st 2020 on COVID-19 ICU admissions and outcomes using pre-defined search terms and eligibility criteria.Relevant data was extracted and pooled using fixed or random effects meta-analysis depending on heterogeneity. Study quality was assessed by the NIH tool and heterogeneity was assessed by I2 and Q tests. Baseline patient characteristics, ICU and IMV outcomes were pooled and meta-analyzed. Pooled odds ratios (pOR) were calculated for clinical features against ICU, MV mortality. Subgroup analysis was carried out based on patient regions.Results Twenty-eight studies comprising 12,437 COVID-19 ICU admissions from seven countries were meta-analyzed. Pooled ICU admission rate was 21%[95% CI 0.12 to 0.34] and 69% of cases needed IMV[95% CI 0.61-0.75]. ICU and IMV mortality were 28.3%[95% CI 0.25 to 0.32], 43%[95% CI 0.29 to 0.58] and ICU, IMV duration was 7.78[95% CI 6.99 to 8.63] and 10.12[95% CI 7.08 to 13.16] days respectively. Besides confirming the significance of comorbidities and clinical findings of COVID-19, major correlates with ICU mortality were found to be IMV [pOR 16.46, 95% CI 4.37 to 61.96], acute kidney injury (AKI) [pOR 12.47, 95% CI 1.52 to 102.7], and acute respiratory distress syndrome (ARDS) [pOR 6.52, 95% CI 2.66 to 16.01]. Subgroup analyses confirm significant regional discrepancies in outcomes.Conclusions This is the most comprehensive systematic review and meta-analysis of COVID-19 ICU and IMV cases and associated outcomes to date and the only analysis to analyze and associate IMV with COVID-19 ICU mortality. The significant association of AKI, ARDS and IMV with mortality has implications for ICU resource planning for AKI and ARDS as well as research into optimal ventilation strategies for patients. Regional differences in outcome implies a need to develop region specific protocols for ventilatory support as well as overall treatment.Study Registration PROSPERO registration number CRD42020182482.

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Section: Discussionsupporting

confidence: 84%

COVID-19 ICU and Mechanical Ventilation Patient Characteristics and Outcomes - A Systematic Review and Meta-analysis

Chang

Elhusseiny

Yeh

et al. 2020

Preprint

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“…The median length of stay of 111 patients with COVID-19 in hospital in this study was 19 days, which is within the range outside of China (4-21 days), but comparatively lower than that from China (4-53 days) [27]. In general, differences in the length of hospital stay may be attributable to variations in criteria for admission and discharge across different countries as well as timing within the pandemic [27]. Early diagnosis is fundamental for effective management of COVID-19 cases; thus, a median turnaround time of 2 (1-4) days for laboratory diagnosis as noted in the current study seems impressive, and possibly an indication of ongoing measures being championed by the NCDC to strengthen molecular diagnostic capacity in Nigeria.…”

Section: Interpretation Of Key Findingsmentioning

confidence: 46%

“…This is because women are increasingly partaking in the workforce in Nigeria, such that the traditional trends of 'male breadwinner and female family support' are fast eroding [26]. The median length of stay of 111 patients with COVID-19 in hospital in this study was 19 days, which is within the range outside of China (4-21 days), but comparatively lower than that from China (4-53 days) [27]. In general, differences in the length of hospital stay may be attributable to variations in criteria for admission and discharge across different countries as well as timing within the pandemic [27].…”

Section: Interpretation Of Key Findingsmentioning

confidence: 61%

Descriptive epidemiology of coronavirus disease 2019 in Nigeria, 27 February–6 June 2020

et al. 2020

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The objective of this study was to describe the epidemiology of COVID-19 in Nigeria with a view of generating evidence to enhance planning and response strategies. A national surveillance dataset between 27 February and 6 June 2020 was retrospectively analysed, with confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR). The primary outcomes were cumulative incidence (CI) and case fatality (CF). A total of 40 926 persons (67% of total 60 839) had complete records of RT-PCR test across 35 states and the Federal Capital Territory, 12 289 (30.0%) of whom were confirmed COVID-19 cases. Of those confirmed cases, 3467 (28.2%) had complete records of clinical outcome (alive or dead), 342 (9.9%) of which died. The overall CI and CF were 5.6 per 100 000 population and 2.8%, respectively. The highest proportion of COVID-19 cases and deaths were recorded in persons aged 31–40 years (25.5%) and 61–70 years (26.6%), respectively; and males accounted for a higher proportion of confirmed cases (65.8%) and deaths (79.0%). Sixty-six per cent of confirmed COVID-19 cases were asymptomatic at diagnosis. In conclusion, this paper has provided an insight into the early epidemiology of COVID-19 in Nigeria, which could be useful for contextualising public health planning.

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“…Estimating LoS has not been the primary focus of previous modelling; and studies that calculate LoS tend to use ad-hoc approaches [8]. There is currently a lack of statistically principled modelling that accounts for both delays in patient outcomes and complex hospitalisation pathways.…”

Section: Introductionmentioning

confidence: 99%

Hospital Length of Stay For COVID-19 Patients: Data-Driven Methods for Forward Planning

Vekaria¹,

orcid²,

Overton³

et al. 2020

Preprint

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Background: Predicting hospital length of stay (LoS) for patients with COVID-19 infection is essential to ensure that adequate bed capacity can be provided without unnecessarily restricting care for patients with other conditions. Here, we demonstrate the utility of three complementary methods for predicting LoS using UK national- and hospital-level data. Method: On a national scale, relevant patients were identified from the COVID-19 Hospitalisation in England Surveillance System (CHESS) reports. An Accelerated Failure Time (AFT) survival model and a truncation corrected method (TC), both with underlying Weibull distributions, were fitted to the data to estimate LoS from hospital admission date to an outcome (death or discharge) and from hospital admission date to Intensive Care Unit (ICU) admission date. In a second approach we fit a multi-state (MS) survival model to data directly from the Manchester University NHS Foundation Trust (MFT). We develop a planning tool that uses LoS estimates from these models to predict bed occupancy. Results: All methods produced similar overall estimates of LoS for overall hospital stay, given a patient is not admitted to ICU (8.4, 9.1 and 9.3 days for AFT, TC and MS, respectively). Estimates differ more significantly between the local and national level when considering ICU. National estimates for ICU LoS from AFT and TC were 12.4 and 13.4 days, whereas in local data the MS method produced estimates of 22.8 days. Conclusions: Given the complexity and partiality of different data sources and the rapidly evolving nature of the COVID-19 pandemic, it is most appropriate to use multiple analysis methods on multiple datasets. The AFT method accounts for censored cases, but does not allow for simultaneous consideration of different outcomes. The TC method does not include censored cases but does consider these different outcomes. The MS method can model complex pathways to different outcomes whilst accounting for censoring, but cannot handle non-random case missingness. Overall, we conclude that data-driven modelling approaches of LoS using these methods is useful in epidemic planning and management, and should be considered for widespread adoption throughout healthcare systems internationally where similar data resources exist.

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

Cited by 63 publications

References 74 publications

COVID-19 ICU and Mechanical Ventilation Patient Characteristics and Outcomes - A Systematic Review and Meta-analysis

COVID-19 ICU and Mechanical Ventilation Patient Characteristics and Outcomes - A Systematic Review and Meta-analysis

Descriptive epidemiology of coronavirus disease 2019 in Nigeria, 27 February–6 June 2020

Hospital Length of Stay For COVID-19 Patients: Data-Driven Methods for Forward Planning

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