Bibliographic record
Abstract
Introduction The Clinical Frailty Scale (CFS) is a clinical judgement-based frailty tool developed from the Canadian Study of Health and Aging. Many studies on the measurement of frailty and its effect on clinical outcomes have been conducted on patients hospitalized, especially in intensive care units. The purpose of this study is to examine the relationship between polypharmacy and frailty on outpatient older adult patients in primary care. Materials and Method This cross-sectional study included 298 patients who were aged ≥65 years and admitted to Yenimahalle Family Health Center between May-2022 and July-2022. Frailty was evaluated by using CFS. Polypharmacy was defined as five medications or more and “excessive polypharmacy” as 10 medications or more. The medications below five are grouped as “no polypharmacy”. Results There was a statistically significance between age groups, gender, smoking status, marital status, polypharmacy status, and FS ( p = .003 and η 2 : .20; p < .001 and Cohen d: .80; p = .018 and Cohen d: .35; p < .001 and Cohen d: 1.10 and p < .001 and η 2 : 1.45 respectively). A strong, positive correlation was found between polypharmacy and the frailty score. Conclusion Polypharmacy, especially excessive polypharmacy, may be a promising adjunct to frailty in identifying older patients whose health is more likely to worsen. Providers in primary care should also consider frailty when prescribing drugs.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".