Evidence map›Paper›PMID 39030068›Full record

ArticleEuropean heart journal. Quality of care & clinical outcomes2025

Wait-times benchmarks for risk-based prioritization in transcatheter aortic valve implantation: a simulation study.

Rafael N Miranda, Peter C Austin, Stephen E Fremes, Mamas A Mamas, Maneesh K Sud, David M J Naimark, Harindra C Wijeysundera

Abstract read
In one paragraph

Article in European heart journal. Quality of care & clinical outcomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Fighting time: the critical importance of pre-TAVR mortality risk prediction.Clinical research in cardiology : official journal of the German Cardiac Society · 2025
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rafael N MirandaInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.ORCID 0000-0003-2173-0021
Peter C AustinInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.ORCID 0000-0003-3337-233X
Stephen E FremesInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.ORCID 0000-0003-1723-3049
Mamas A MamasKeele Cardiovascular Research Group, School of Medicine, Keele University, Stoke-on-Trent ST5 5BG, UK.ORCID 0000-0001-9241-8890
Maneesh K SudICES, Toronto M4N 3M5, Canada.ORCID 0000-0003-1936-5133
David M J NaimarkInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.ORCID 0000-0002-0621-0637
Harindra C WijeysunderaInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto M5T 3M6, Canada.ORCID 0000-0001-8464-1080

Funding

CIHRICESOntario Ministry of Health and Long-Term Care
6 · The paper itself

Abstract

backgroundDemand for transcatheter aortic valve implantation (TAVI) has increased in the last decade, resulting in prolonged wait-times and undesirable health outcomes in many health systems. Risk-based prioritization and wait-times benchmarks can improve equitable access to patients. METHODS AND

resultsWe used simulation models to follow-up a synthetic population of 50 000 individuals from referral to completion of TAVI. Based on their risk of adverse events, patients could be classified as 'low-', 'medium-', and 'high-risk', and shorter wait-times were assigned for the higher risk groups. We assessed the impacts of the size and wait-times for each risk group on waitlist mortality, hospitalization, and urgent TAVIs. All scenarios had the same resource constraints, allowing us to explore the trade-offs between faster access for prioritized patients and deferred access for non-prioritized groups. Increasing the proportion of patients categorized as high-risk, and providing more rapid access to the higher-risk groups achieved the greatest reductions in mortality, hospitalizations and urgent TAVIs (relative reductions of up to 29%, 23%, and 38%, respectively). However, this occurs at the expense of excessive wait-times in the non-prioritized low-risk group (up to 25 weeks). We propose wait-times of up to 3 weeks for high-risk patients and 7 weeks for medium-risk patients.

conclusionPrioritizing higher-risk patients with faster access leads to better health outcomes, however this also results in unacceptably long wait-times for the non-prioritized groups in settings with limited capacity. Decision-makers must be aware of these implications when developing and implementing waitlist prioritization strategies.

Indexed as

Aortic Valve StenosisBenchmarkingTranscatheter Aortic Valve ReplacementWaiting ListsAgedComputer SimulationFemaleHumansMaleRisk AssessmentTime FactorsHealth policyTAVITranscatheter aortic valve implantationWaitlistWait-times

Identifiers

PMID39030068
PMCPMC11736150

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.