Evidence map›Paper›PMID 40622621›Full record

ArticleClinical research in cardiology : official journal of the German Cardiac Society2025

Patient risk evaluation for transcatheter aortic valve replacement (PRE-TAVR) - identification of real-time predictors of short- and long-term mortality.

Julian Kreutz, Philipp Lauten, Georgios Chatzis, Marie Nabrotzki, Nikolaos Patsalis, Styliani Syntila, Harald Lapp, Bernhard Schieffer, Birgit Markus

Abstract readMulticenter Study
In one paragraph

Article in Clinical research in cardiology : official journal of the German Cardiac Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Julian KreutzDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany. kreutzj@staff.uni-marburg.de.ORCID http://orcid.org/0000-0001-9498-9558
Philipp LautenDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Georgios ChatzisDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Marie NabrotzkiDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Nikolaos PatsalisDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Styliani SyntilaDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Harald LappDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Bernhard SchiefferDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.
Birgit MarkusDepartment of Cardiology, Angiology, and Intensive Care Medicine, Philipps-Universität Marburg, Baldingerstraße, 35043, Marburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe steadily increasing number of transcatheter aortic valve replacement (TAVR) procedures being performed on a heterogeneous patient population highlights the need for robust risk assessment. While EuroSCORE II is well established for surgical risks, it is less effective for TAVR, and the newer STS/ACC TAVR score has so far been validated mainly for in-hospital and 30-day mortality.

aimsThis study aims to improve risk stratification for TAVR patients by identifying real-time predictors of 30-day and 1-year mortality that incorporate comprehensive, procedure-specific factors.

methodsFive-year data from 2256 transfemoral TAVR procedures performed at two German Heart Centers (2017-2022) were retrospectively analyzed. Predictors of 1-year and 30-day mortality were assessed using multivariable logistic and LASSO regression, considering a broad spectrum of patient demographics, comorbidities, and peri-procedural factors.

resultsThe analyses revealed a predictor model (PRE-TAVR predictors) for 1-year mortality (AUC 0.770; 95% CI 0.731-0.809), including age (> 81.5 years), NYHA stage IV, COPD (GOLD ≥ 2), atrial fibrillation, previous stroke or malignancy, elevated C-reactive protein (≥ 9.5 mg/L), aortic valve ΔP mean ≥ 48.5 mmHg, peripheral arterial disease (> stage 2) and low platelet count (≤ 228.5 g/L). The accuracy of the model exceeded the EuroSCORE II (AUC 0.645; 95% CI 0.599-0.691) and the STS/ACC TAVR score (AUC 0.714; 95% CI 0.670-0.758). For 30-day mortality, NYHA class IV was the only significant predictor in the bivariate analyses. However, additional LASSO analyses identified pre-existing renal insufficiency (KDIGO stage ≥ 3) and pre-TAVR sodium levels as further significant predictors. The AUC was 0.699 (95% CI 0.611-0.788) compared to an AUC of 0.680 (95% CI 0.604-0.756) for EuroSCORE II and 0.7129 (95% CI 0.633-0.793) for the STS/ACC TAVR score.

conclusionThe PRE-TAVR study developed a robust model, particularly for predicting 1-year mortality. This model outperformed the EuroSCORE II and STS/ACC TAVR scores, despite requiring fewer variables. It provides a solid basis for future risk scores and enables more precise patient selection.

Indexed as

Aortic Valve StenosisTranscatheter Aortic Valve ReplacementAgedAged, 80 and overFemaleFollow-Up StudiesGermanyHumansMaleRetrospective StudiesRisk AssessmentRisk FactorsSurvival RateTime Factors1-year mortality30-day mortalityLASSO regression analysisPredictors of mortalityTranscatheter aortic valve replacement (TAVR)

Identifiers

PMID40622621
PMCPMC12540637

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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.