Aortic stenosis post-COVID-19: A mathematical model on waiting lists and mortality

Mamas

Abstract

<h4>Objectives</h4> To provide estimates for how different treatment pathways for the management of severe aortic stenosis (AS) may affect NHS England waiting list duration and associated mortality. <h4>Design</h4> We constructed a mathematical model of the excess waiting list and found the closed-form analytic solution to that model. From published data, we calculated estimates for how the following strategies may affect the time to clear the backlog of patients waiting for treatment and the associated waiting list mortality. <h4>Interventions</h4> 1) increasing the capacity for the treatment of severe AS, 2) converting proportions of cases from surgery to transcatheter aortic valve implantation, and 3) a combination of these two. <h4>Results</h4> In a capacitated system, clearing the backlog by returning to pre-COVID-19 capacity is not possible. A conversion rate of 50% would clear the backlog within 666 (95% CI, 533–848) days with 1419 (95% CI, 597–2189) deaths whilst waiting during this time. A 20% capacity increase would require 535 (95% CI, 434–666) days, with an associated mortality of 1172 (95% CI, 466–1859). A combination of converting 40% cases and increasing capacity by 20% would clear the backlog within a year (343 (95% CI, 281–410) days) with 784 (95% CI, 292–1324) deaths whilst awaiting treatment. <h4>Conclusion</h4> A strategy change to the management of severe AS is required to reduce the NHS backlog and waiting list deaths during the post-COVID-19 ‘recovery’ period. However, plausible adaptations will still incur a substantial wait and many hundreds dying without treatment.

Citation

Mamas. (2021). Aortic stenosis post-COVID-19: A mathematical model on waiting lists and mortality. MedRxiv, https://doi.org/10.1101/2021.11.11.21266212

• Acceptance Date: Nov 14, 2021
• Publication Date: Nov 14, 2021
• Journal: medRxiv
• Publisher: Cold Spring Harbor Laboratory Press
• DOI: https://doi.org/10.1101/2021.11.11.21266212
• Public URL: https://keele-repository.worktribe.com/output/422121
• Publisher URL: https://www.medrxiv.org/content/10.1101/2021.11.11.21266212v1