Comparison of frailty in oldest-old people using the Clinical-Functional Vulnerability Index-20 (IVCF-20) and Edmonton Frail Scale (EFS)
Bibliographic record
Abstract
Abstract Objective To compare Clinical-Functional Vulnerability Index-20 (IVCF-20) and Edmonton Frail Scale (EFS) scores among community-dwelling older people aged ≥80 years for prevalence and degree of agreement. Method A cross-sectional study nested within a population-based cohort, was conducted. Baseline sampling was probabilistic by two-stage clustering. In the first stage, the census tract was used as the sampling unit. In the second stage, the number of households was defined according to the population density of individuals aged ≥60 years. Sensitivity, specificity and predictive values were determined and Kappa statistics expressed degree of agreement between the instruments. Results 92 oldest-old people were evaluated. The prevalence of high risk of clinical and functional vulnerability on the IVCF, indicating frailty, was 45,7%, whereas the prevalence of frailty using the EFS was 44,6%. Sensitivity, specificity, positive predictive value and negative predictive values were 88,23%, 87,80%, 90,0% and 85,71%, respectively. Accuracy was 88,04% and the Kappa statistic 0.759 (p<0.001). Conclusion The IVCF-20 and EFS instruments showed good accuracy and strong agreement when applied to community-dwelling oldest-old people. The identification of frailty was superior using the IVCF-20. These results show that the instruments detected similar frailty prevalence in community-dwelling oldest-old people.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".