Evidence map›Paper›PMID 38390797›Full record

ArticleJournal of the American Heart Association2024

Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T).

Rafael N Miranda, Feng Qiu, Ragavie Manoragavan, Peter C Austin, David M J Naimark, Stephen E Fremes, Dennis T Ko, Mina Madan, Mamas A Mamas, Maneesh K Sud and 2 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Rafael N MirandaInstitute of Health Policy, Management and Evaluation University of Toronto Canada.ORCID 0000-0003-2173-0021
Feng QiuICES Toronto Canada.ORCID 0000-0001-9882-7564
Ragavie ManoragavanSchulich Heart Program, Sunnybrook Health Sciences Centre University of Toronto Canada.
Peter C AustinInstitute of Health Policy, Management and Evaluation University of Toronto Canada.ORCID 0000-0003-3337-233X
David M J NaimarkInstitute of Health Policy, Management and Evaluation University of Toronto Canada.ORCID 0000-0002-0621-0637
Stephen E FremesInstitute of Health Policy, Management and Evaluation University of Toronto Canada.ORCID 0000-0003-1723-3049
Dennis T KoICES Toronto Canada.ORCID 0000-0001-6840-8051
Mina MadanSchulich Heart Program, Sunnybrook Health Sciences Centre University of Toronto Canada.ORCID 0000-0003-0285-6569
Mamas A MamasKeele Cardiovascular Research Group, School of Medicine Keele University Stoke-on-Trent United Kingdom.ORCID 0000-0001-9241-8890
Maneesh K SudICES Toronto Canada.ORCID 0000-0003-1936-5133
Derrick TamSchulich Heart Program, Sunnybrook Health Sciences Centre University of Toronto Canada.
Harindra C WijeysunderaInstitute of Health Policy, Management and Evaluation University of Toronto Canada.ORCID 0000-0001-8464-1080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. METHODS AND

resultsWe included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors.

conclusionsThe Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Indexed as

Aortic Valve StenosisTranscatheter Aortic Valve ReplacementAortic ValveHumansOntarioRisk FactorsTreatment OutcomeTriageWaiting Listsaccess to careobservational studyprediction modelTAVItranscatheter aortic valve implantationtranscatheter aortic valve replacement

Identifiers

PMID38390797
PMCPMC10944064

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.