Evidence map›Paper›PMID 38324040›Full record

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

Epicardial adipose tissue as an independent predictor of long-term outcome in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Alexander Schulz, Bo E Beuthner, Zoé M Böttiger, Svante S Gersch, Torben Lange, Judith Gronwald, Ruben Evertz, Sören J Backhaus, Johannes T Kowallick, Gerd Hasenfuß and 1 more

Abstract read
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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

11 authors.

Alexander Schulz *Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.ORCID http://orcid.org/0000-0001-5589-8792
Bo E Beuthner *Department of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Zoé M BöttigerDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Svante S GerschDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Torben LangeDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Judith GronwaldDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Ruben EvertzDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Sören J BackhausDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Johannes T KowallickGerman Center for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany.
Gerd HasenfußDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany.
Andreas SchusterDepartment of Cardiology and Pneumology, University Medical Center Göttingen, Georg-August University, Robert-Koch-Str. 40, 37099, Göttingen, Germany. andreas_schuster@gmx.net.ORCID http://orcid.org/0000-0003-1508-1125

Funding

Deutsche Forschungsgemeinschaft CRC 1002 D1
6 · The paper itself

Abstract

backgroundAccurate risk stratification is important to improve patient selection and outcome of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). As epicardial adipose tissue (EAT) is discussed to be involved in cardiovascular disease, it could be useful as a marker of poor prognosis in patients with severe AS undergoing TAVR.

methodsA total of 416 patients diagnosed with severe AS by transthoracic echocardiography were assigned for TAVR and enrolled for systematic assessment. Patients underwent clinical surveys and 5-year long-term follow-up, with all-cause mortality as the primary endpoint. EAT volume was quantified on pre-TAVR planning CTs. Patients were retrospectively dichotomized at the median of 74 cm

resultsA total number of 341 of 416 patients (median age 80.9 years, 45% female) were included in the final analysis. Patients with high EAT volumes had similar short-term outcome (p = 0.794) but significantly worse long-term prognosis (p = 0.023) compared to patients with low EAT volumes. Increased EAT volumes were associated with worse long-term outcome (HR1.59; p = 0.031) independently from concomitant cardiovascular risk factors, general type of AS, and functional echocardiography parameters of AS severity (HR1.69; p = 0.013).

conclusionIncreased EAT volume is an independent predictor of all-cause mortality in patients with severe AS undergoing TAVR. It can be easily obtained from pre-TAVR planning CTs and may thus qualify as a novel marker to improve prognostication and management of patient with severe AS.

trial registrationDRKS, DRKS00024479.

Indexed as

Adipose TissueAortic ValveAortic Valve StenosisPericardiumTranscatheter Aortic Valve ReplacementAgedAged, 80 and overEchocardiographyEpicardial Adipose TissueFemaleFollow-Up StudiesHumansMalePrognosisRetrospective StudiesRisk AssessmentComputed tomographyEpicardial adipose tissueLong-term outcomeRisk predictionTranscatheter aortic valve replacement

Identifiers

PMID38324040
PMCPMC12540550

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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.