SARC-F predicts poor motor function, quality of life, and prognosis in older patients with cardiovascular disease and cognitive impairment
Bibliographic record
Abstract
OBJECTIVES: We investigated whether SARC-F scores were associated with motor function, quality of life (QOL) related to physical function, and prognosis in older patients with cardiovascular disease (CVD) and cognitive impairment. METHODS: This was a retrospective cross-sectional cohort study. The study population consisted of 408 patients with CVD (≥60 years old) who completed the SARC-F questionnaire and Mini-Cog, a cognitive function test, at discharge. Sarcopenia was defined as a total SARC-F score ≥ 4 points. Patients who were cognitively-preserved (Mini-Cog score ≥ 3 points) were excluded. Patients completed the handgrip strength, leg strength, usual gait speed, 6-minute walking distance, short physical performance battery score, and 36-item Short-Form Health Survey Physical Functioning (SF-36PF) tests before discharge. Associations of SARC-F with physical function, QOL, and prognoses (i.e., composite of all-cause death and emergency CVD rehospitalization and the number of CVD rehospitalizations) were investigated. RESULTS: Sarcopenia (SARC-F score ≥ 4 points) was associated with poorer motor function test outcomes and SF-36PF scores (all P < 0.001). The correlations remained significant after adjusting for comorbidities (e.g., anemia, prior heart failure, and renal dysfunction). Sarcopenia was also associated with a poorer prognosis (hazard ratio: 1.574; 95 % confidence interval [CI], 1.011-2.445) and an increased risk of CVD rehospitalization (incidence rate ratio: 1.911; 95 % CI, 1.312-2.782) after adjusting for comorbidities. CONCLUSIONS AND IMPLICATIONS: In older patients with CVD and cognitive impairment, the SARC-F questionnaire may be a simple and inexpensive tool for identifying patients with decreased motor function and a poor prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".