Evidence map›Paper›PMID 41940086›Full record

ArticleFrontiers in cardiovascular medicine2026

Geriatric nutritional risk index improves risk scoring for mortality after TAVR compared to established scores.

Johannes Boehm, Andrea Amabile, Hendrik Ruge, Martin Bichler, Stefan Holdenrieder, Melchior Burri, Markus Krane

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Johannes BoehmDepartment of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.
Andrea AmabileDepartment of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.
Hendrik RugeDepartment of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.
Martin BichlerDepartment of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.
Stefan HoldenriederInstitute for Laboratory Medicine, German Heart Center, Technical University of Munich, Munich, Germany.
Melchior Burri *Department of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.
Markus Krane *Department of Cardiovascular Surgery, Institute Insure, TUM University Hospital - German Heart Center, TUM School of Medicine & Health, Technical University of Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Risk scoring prior TAVR is based on the EuroSCORE II (European System for Cardiac Operative Risk Evaluation) and the STS-score (Society of Thoracic Surgeons) which are complex, and partly prone to investigator bias. The geriatric nutritional risk index (GNRI) can be calculated by five parameters via publicly available formula (age, height, weight, sex, serum albumin), whereas EuroSCORE II and the STS-score require 21 and 69 variables, respectively. The study compares the efficiency of GNRI in predicting 30-day mortality compared to the EuroSCORE II and the STS-score. Furthermore, GNRI risk classes were analysed in the long-term. Methods: 3.470 consecutive patients who underwent TAVR between 2010 and 2023 at our institution were analysed. GNRI calculation produces a linear parameter that can be divided in four risk groups. Results: ROC (receiver operating characteristic) curve analysis demonstrated no difference in predicting 30-day mortality between GNRI vs. EuroSCORE II (AUC = 0.72 vs. 0.69, Conclusions: The GNRI is an objective publicly available score that simplifies risk assessment prior TAVR without any loss of precision compared to the EuroSCORE II and the STS-score.

Indexed as

30-day mortalitygeriatricsGNRInutritional scoresoutcome analysisrisk scoringTAVR

Identifiers

PMID41940086
PMCPMC13044081

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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.