Abstract 11825: The Association Between Frailty and Vascular Endothelial Growth Factor Families in Patients With Heart Failure: The PREHOSP-CHF Study
Bibliographic record
Abstract
Background: Frailty is a complex clinical syndrome associated with ageing and chronic illness, and is common in heart failure (HF). Vascular endothelial dysfunction including maladaptive angiogenesis and lymphangiogenesis is involved in the pathogenesis of HF, and is also considered to be the causes of frailty. We investigated the association of vascular endothelial growth factor (VEGF) families, central regulators of angiogenesis and lymphangiogenesis, with frailty, and prognostic role of these cytokines in frail HF patients. Methods: We performed a multicenter prospective cohort study to determine the predictive value of VEGF families for prognosis among patients with HF. A total of 1,024 patients (mean age, 75.5 years, 58.7% male) were included in the analyses. Serum levels of VEGF, VEGF-C, VEGF-D, and soluble VEGF receptor-2 (sVEGFR-2) were measured. Frailty was assessed by Canadian Study of Health and Aging Clinical Frailty Scale (CFS). Results: A total of 256 (25.1%) patients had frailty (CFS≥5) at baseline. Frail patients were older, more likely female, and had lower body mass index, higher NYHA class, and higher rates of prior hospitalization for HF, HF with preserved ejection fraction, anemia, cerebrovascular disease, and dementia. N-terminal pro brain natriuretic peptide, high sensitivity troponin I, and high sensitivity C-reactive protein levels were higher in frail patients. During the 2-year follow-up, 211 all cause death occurred. In Kaplan-Maier analysis, frail patients showed significantly higher incidence of all-cause (hazard ratio [HR], 4.12; 95% confidence interval [CI], 3.14-5.42). Regarding VEGF families, frail patients had significantly lower levels of sVEGFR-2 and VEGF-C, and higher levels of VEGF-D. Multiple regression analysis revealed that VEGF-C had inverse correlation with CFS (P, 0.03). After adjusting for clinical confounders, a low VEGF-C level was independently associated with all-cause death in frail patients (HR, 0.74; 95%CI, 0.58-0.94 for 1-SD increase), but was not in non-frail patients (HR, 0.87; 95%CI, 0.64-1.14 for 1-SD increase) (P for interaction, 0.09). Conclusions: In HF patients, a low VEGF-C value was associated with frailty and was independent risk for all-cause death in frail patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".