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Record W4416301115 · doi:10.3389/fcvm.2025.1671305

Comparison of sarcopenia prevalence and prognostic features between HFrEF and HFpEF: a systematic review and meta-analysis

2025· review· en· W4416301115 on OpenAlexaboutno aff
Jun Yang, Xinbin Zhou, Siyin Wang, Jin Dai, Xiao Wang

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2025
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSarcopeniaMEDLINEHeart failureDiseaseDiabetes mellitus

Abstract

fetched live from OpenAlex

Background Sarcopenia is closely associated with heart failure (HF); however, no prior meta-analysis has specifically addressed its relation with different ejection fraction phenotypes. This study investigated the prevalence of sarcopenia in patients with HF with reduced ejection fraction (HFrEF) vs. those with preserved ejection fraction (HFpEF), compared their prevalence rates, and explored the prognostic outcomes associated with sarcopenia in these phenotypes. Methods PubMed, Cochrane, and Embase databases were searched from their inception to February 2025. Studies reporting the prevalence or prognosis of sarcopenia in patients with HF and defined ejection fraction phenotypes were included. Two authors independently assessed study quality using the Newcastle–Ottawa Scale and Agency for Healthcare Research and Quality. Meta-analyses were conducted using Stata 17, with random-effects models applied to heterogeneous data. Results Twenty studies were included: 17 on sarcopenia prevalence in HFrEF, four in HFpEF, four comparing the prevalence between phenotypes, and two comparing prognoses. The pooled prevalence rate of sarcopenia was 35% and 28% in patients with HFrEF and HFpEF, respectively. Subgroup analyses revealed regional variations: Asian populations showed a higher prevalence in HFrEF (48%) that that in HFpEF (16%), whereas European populations exhibited a higher prevalence in HFpEF (44%) than that in HFrEF (27%). In America, the prevalence of sarcopenia in patients with HFrEF was 29%. Age-stratified analyses demonstrated a sarcopenia prevalence of 30% in patients with HFrEF aged ≥65 years vs. 36% in those <65 years. Hospitalized patients with HFrEF had a higher prevalence (45%) than that of the outpatient cohort (23%), whereas hospitalized patients with HFpEF showed a 43% prevalence vs. 16% in outpatients. A meta-analysis of studies directly comparing HFrEF and HFpEF found no significant difference in sarcopenia prevalence (fixed-effect model: RR = 1.12, 95% CI: 1.01–1.23; I 2 = 23%, p = 0.273). Prognostic comparisons between patients with sarcopenic HFrEF and HFpEF also showed no significant difference (hazard ratio = 1.57, 95% CI: 0.66–3.77; I 2 = 79%, p = 0.029). Conclusion In epidemiology, the prevalence of sarcopenia was higher in patients with HFrEF than in those with HFpEF. However, Among studies that include a comparison of the prevalence rates of HFrEF and HFpEF with sarcopenia, meta-analyses have indicated that the ejection fraction phenotype is neither associated with the prevalence of sarcopenia in HF nor with poor outcomes in patients with HF and sarcopenia. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420251077599 , PROSPERO CRD420251077599.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0180.036
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.099
GPT teacher head0.416
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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