Version 1
: Received: 10 August 2020 / Approved: 11 August 2020 / Online: 11 August 2020 (13:45:43 CEST)
Version 2
: Received: 8 September 2020 / Approved: 9 September 2020 / Online: 9 September 2020 (09:28:49 CEST)
How to cite:
Doidge, J.C.; Mouncey, P.R.; Thomas, K.; Gould, D.W.; Ferrando-Vivas, P.; Shankar-Hari, M.; Harrison, D.A.; Rowan, K.M. Trends in Intensive Care for Patients with COVID-19 in England, Wales and Northern Ireland. Preprints2020, 2020080267. https://doi.org/10.20944/preprints202008.0267.v1
Doidge, J.C.; Mouncey, P.R.; Thomas, K.; Gould, D.W.; Ferrando-Vivas, P.; Shankar-Hari, M.; Harrison, D.A.; Rowan, K.M. Trends in Intensive Care for Patients with COVID-19 in England, Wales and Northern Ireland. Preprints 2020, 2020080267. https://doi.org/10.20944/preprints202008.0267.v1
Doidge, J.C.; Mouncey, P.R.; Thomas, K.; Gould, D.W.; Ferrando-Vivas, P.; Shankar-Hari, M.; Harrison, D.A.; Rowan, K.M. Trends in Intensive Care for Patients with COVID-19 in England, Wales and Northern Ireland. Preprints2020, 2020080267. https://doi.org/10.20944/preprints202008.0267.v1
APA Style
Doidge, J.C., Mouncey, P.R., Thomas, K., Gould, D.W., Ferrando-Vivas, P., Shankar-Hari, M., Harrison, D.A., & Rowan, K.M. (2020). Trends in Intensive Care for Patients with COVID-19 in England, Wales and Northern Ireland. Preprints. https://doi.org/10.20944/preprints202008.0267.v1
Chicago/Turabian Style
Doidge, J.C., David A Harrison and Kathryn M Rowan. 2020 "Trends in Intensive Care for Patients with COVID-19 in England, Wales and Northern Ireland" Preprints. https://doi.org/10.20944/preprints202008.0267.v1
Abstract
Aim: To report changes in admission rates, patient characteristics, processes of care and outcomes for all patients with COVID-19 admitted to intensive care units (ICUs) in England, Wales and Northern Ireland. Methods: Population cohort of all 10,287 patients with COVID-19 appearing in the Case Mix Programme national clinical audit from 1 February to 2 July, 2020. Analyses were stratified by time period (pre-peak, peak, post-peak) and geographical region, and multivariable regressions were used to estimate differences in 28-day mortality, adjusting for variation in patient characteristics over time. Results: Admissions to ICU peaked on 1 April, nine days after commencement of “lockdown”, and occurred simultaneously across regions. The number of patients in ICU peaked ten days later. Compared with patients admitted during the pre- and post-peak periods, patients admitted during the peak were younger and had lower levels of prior dependency but more severe respiratory and renal dysfunction. Use of invasive ventilation and renal replacement reduced over time. Twenty-eight-day mortality reduced from 43.5% (95% CI 41.6% to 45.5%) pre-peak to 34.3% (95% CI 32.3% to 36.2%) post-peak; a difference of −8.8% (95% CI: −5.2%, −12.3%) after adjusting for patient characteristics. London experienced the highest admission rate and had higher mortality during the peak period but a greater reduction in post-peak mortality. Conclusion: Observed trends suggest opposing effects of ICU strain and clinical learning. Further investigation is needed to identify modifiable system factors that could alleviate strain in future epidemics and changes in clinical practice that contributed to improved patient outcomes.
Keywords
COVID-19; intensive care; trends; United Kingdom; mortality; mechanical ventilation
Subject
Medicine and Pharmacology, Pulmonary and Respiratory Medicine
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
3 November 2020
Commenter:
Boris Hayete
The commenter has declared there is no conflict of interests.
Comment:
How was the adjustment for age made, to focus on one question? Age doesn't seem to have binned, that is, the adjustment likely wasn't based on factor levels, and dependence of mortality on age is roughly exponential. Without an appropriate transform, linear adjustment or residual modeling would have likely failed to account for at least some of age dependence of IFR.
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Commenter: Boris Hayete
The commenter has declared there is no conflict of interests.