Bibliographic record
Abstract
AIM: This study aimed to evaluate frailty in older individuals and to identify factors related to frailty. METHOD: The descriptive, and cross-sectional study was conducted with 111 elderly patients who received inpatient treatment in a university hospital between January and September 2016. Ethics committee approval, institutional consent, and informed patient consent were obtained for the study. Along with the Edmonton Frail Scale, a data form was used to collect data about the patient’s sociodemographics, disease status, and fall incidents. The data were collected through face-to-face interviews. RESULTS: The prevalence of severe frailty was 19.8%. Significant relationships were found between frailty and advanced age, low education, low income, continuous use of medicines, and a history of falls within the last year. CONCLUSION: Elderly individuals included in the study were categorized as “vulnerable” (Edmonton Frail Scale score of 6.84±3.83) and were at the borderline for “mild frailty” (Edmonton Frail Scale score of 7-8). The factors associated with frailty were advanced age, low education, and income level, continuous use of medicines, and the history of falls within the last year. Yaşlılarda Kırılganlığın Değerlendirilmesi AMAÇ: Yaşlı bireylerde kırılganlığı değerlendirmek ve kırılganlıkla ilişkili faktörleri saptamaktır. YÖNTEM: Tanımlayıcı ve kesitsel çalışma, Ocak 2016-Eylül 2016 tarihleri arasında bir üniversite hastanesinde yatarak tedavi gören 111 yaşlı birey ile yürütülmüştür. Çalışmanın uygulanabilmesi için etik kurul onayı, kurum izni ve bireylerden bilgilendirilmiş gönüllü olur alınmıştır. Verilerin toplanmasında sosyo-demografik özellikler ile hastalık ve düşme ile ilgili veri formu ve Edmonton Kırılganlık Ölçeği kullanılmıştır. Veriler yüz yüze görüşme yöntemiyle toplanmıştır. BULGULAR: Araştırmada şiddetli kırılganlık prevelansı % 19,8’dir. Kırılganlık ile ileri yaş, düşük eğitim düzeyi, düşük gelir düzeyi, sürekli ilaç kullanımı,1 yıl içindeki düşme öyküsü arasında istatistiksel olarak anlamlı bir ilişki saptanmıştır. SONUÇ: Araştırmaya dahil edilen yaşlı bireyler görünürde ‘savunmasız’ (6,84±3,83 puan) olup ‘hafif kırılgan yaşlı’ (7-8 puan) sınırındadır. Araştırma sonucunda kırılganlıkla ilişkili faktörlerin; ileri yaş, düşük eğitim ve gelir düzeyi, sürekli ilaç kullanımı ve düşme öyküsü olduğu belirlenmiştir. Cite this article as: Düzgün, G., Üstündağ, S., & Karadakovan, A. (2021). Assessment of frailty in the elderly. Florence Nightingale J Nurs, 29(1), 2-8.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".