Evidence map›Paper›PMID 29566805›Full record

ArticleJACC. Cardiovascular interventions2018

Inclusion of Functional Status Measures in the Risk Adjustment of 30-Day Mortality After Transcatheter Aortic Valve Replacement: A Report From the Society of Thoracic Surgeons/American College of Cardiology TVT Registry.

Suzanne V Arnold, Sean M O'Brien, Sreekanth Vemulapalli, David J Cohen, Amanda Stebbins, J Matthew Brennan, David M Shahian, Fred L Grover, David R Holmes, Vinod H Thourani and 3 more

Abstract readValidation Study
In one paragraph

Article in JACC. Cardiovascular interventions, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Calculating Risk for Poor Outcomes After Transcatheter Aortic Valve Replacement.Journal of clinical outcomes management : JCOM · 2019
    Article
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  16. Is it Time to Move Beyond STS and TVT Scores for Predicting TAVR Mortality?Journal of the Society for Cardiovascular Angiography & Interventions
    Article
  17. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Suzanne V ArnoldSaint Luke's Mid America Heart Institute and the University of Missouri-Kansas City, Kansas City, Missouri. Electronic address: suz.v.arnold@gmail.com.
Sean M O'BrienDuke University, Durham, North Carolina.
Sreekanth VemulapalliDuke University, Durham, North Carolina.
David J CohenSaint Luke's Mid America Heart Institute and the University of Missouri-Kansas City, Kansas City, Missouri.
Amanda StebbinsDuke University, Durham, North Carolina.
J Matthew BrennanDuke University, Durham, North Carolina.
David M ShahianLahey Hospital and Medical Center and Harvard Clinical Research Institute, Boston, Massachusetts.
Fred L GroverUniversity of Colorado School of Medicine, Aurora, Colorado.
David R HolmesMayo Clinic, Rochester, Minnesota.
Vinod H ThouraniMedstar Washington Hospital Center/Georgetown University, Washington, District of Columbia.
Eric D PetersonDuke University, Durham, North Carolina.
Fred H EdwardsUniversity of Florida College of Medicine-Jacksonville, Jacksonville, Florida.
STS/ACC TVT Registry

Funding

Optimal Decision Making in Aortic Valve ReplacementK23HL116799 · NHLBI · SAINT LUKE'S HOSPITAL · PI ARNOLD, SUZANNE VICTORIA · 2014 to 2018
$635k
NHLBI NIH HHS K23 HL116799
6 · The paper itself

Abstract

objectivesThe aim of this study was to develop and validate a risk adjustment model for 30-day mortality after transcatheter aortic valve replacement (TAVR) that accounted for both standard clinical factors and pre-procedural health status and frailty.

backgroundAssessment of risk for TAVR is important both for patient selection and provider comparisons. Prior efforts for risk adjustment have focused on in-hospital mortality, which is easily obtainable but can be biased because of early discharge of ill patients.

methodsUsing data from patients who underwent TAVR as part of the Society of Thoracic Surgeons/American College of Cardiology TVT (Transcatheter Valve Therapy) Registry (June 2013 to May 2016), a hierarchical logistic regression model to estimate risk for 30-day mortality after TAVR based only on pre-procedural factors and access site was developed and internally validated. The model included factors from the original TVT Registry in-hospital mortality model but added the Kansas City Cardiomyopathy Questionnaire (health status) and gait speed (5-m walk test).

resultsAmong 21,661 TAVR patients at 188 sites, 1,025 (4.7%) died within 30 days. Independent predictors of 30-day death included older age, low body weight, worse renal function, peripheral artery disease, home oxygen, prior myocardial infarction, left main coronary artery disease, tricuspid regurgitation, nonfemoral access, worse baseline health status, and inability to walk. The predicted 30-day mortality risk ranged from 1.1% (lowest decile of risk) to 13.8% (highest decile of risk). The model was able to stratify risk on the basis of patient factors with good discrimination (C = 0.71 [derivation], C = 0.70 [split-sample validation]) and excellent calibration, both overall and in key patient subgroups.

conclusionsA clinical risk model was developed for 30-day death after TAVR that included clinical data as well as health status and frailty. This model will facilitate tracking outcomes over time as TAVR expands to lower risk patients and to less experienced sites and will allow an objective comparison of short-term mortality rates across centers.

Indexed as

Decision Support TechniquesHealth StatusHealth Status IndicatorsAgedAged, 80 and overCardiomyopathiesClinical Decision-MakingFemaleFrailtyHeart Valve DiseasesHospital MortalityHumansMalePhysical FitnessPredictive Value of TestsRegistriesmortalitytranscatheter aortic valve replacementvariation

Identifiers

PMID29566805
PMCPMC5868746

What OpenQuestion holds

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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.