Evaluation of frailty in community dwelling older adults with heart failure: a comparative analysis of four frailty assessment methods
Bibliographic record
Abstract
Contexte: La fragilit est un tat de diminution des rserves physiologiques et de vulnrabilit qui prdisposent les patients des rsultats dfavorables tels que la perte d'autonomie et la mortalit.Les taux de fragilit les plus levs, ont t identifier chez les patients souffrant d'insuffisance cardiaque (IC).Pour renforcer les estimations des risques et amliorer les rsultats, des mesures de fragilit doivent tre envisages dans la gestion de l'insuffisance cardiaque.Malgr les progrs rcents, une mthode pour valuer la fragilit dans cette population haut risque qui est ralisable et pronostique fait encore dfaut. Mthodes: Une tude de cohorte prospective a t initier 3 centres hospitaliers afin d'tudier la valeur prdictive de 4 mthodes d'valuation de la fragilit; l'chelle de Fried, Clinical Frailty Scale (CFS), Short Physical Performance Battery (SPPB), et Essential Frailty Toolset (EFT).Des personnes ges 60 ans avec un diagnostic clinique d'IC ont t inscrites.L'valuation de base comprenait un questionnaire et des tests physiques (test d'quilibre, une vitesse de marche sur 5 mtres, une preuve de lever de chaise chronomtr, force de prehension).Le rsultat principale tait un composite de mortalit et l'aggravation d'incapacit 3 mois.Rsultats: Parmi 104 personnes ges, avec un ge moyen de 77.4 8.0 la prvalence de la fragilit a vari considrablement selon la mthode de mesure; Fried 24%, CFS 20%, SPPB 23% and EFT 29%.La fragilit, telle que mesure avec le score SPPB, tait le prdicteur le plus fiable de mortalit ou d'aggravation de l'incapacit 3 mois (odds ratio ajust [OR]: 0,41; intervalle de
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".