#3054 A single-centre, cross-sectional study of frailty prevalence and its related risk factors of Indonesian hemodialysis outpatients
Bibliographic record
Abstract
Abstract Background and Aims Frailty is a major problem among maintenance hemodialysis patients, with reported rates up to 82%. The coexistence of frailty and hemodialysis is highly related to morbidity and mortality. The data related to frailty in hemodialysis patients are essential for the development of other healthcare services that should be available in Indonesia. However, the updated epidemiological data in Indonesia are lacking. This study aimed to find the current prevalence of frailty and its related factors among Indonesian hemodialysis outpatients. Method All outpatients aged 18 years and older with regular dialysis for more than three months (two times a week), without acute illness presenting to the Hemodialysis Unit of Universitas Sumatera Utara Hospital, located in Medan, North Sumatera, from September 25th to October 25th, 2024 were enrolled in a cross-sectional study. Frailty status was measured using a FRAIL scale and Edmonton Frail Scale questionnaire. Descriptive, bivariate, and multivariate analyses were conducted. P-value <0.05 was considered statistically significant. Results Among fifty-four participants were enrolled, 50.0% were male. The range age was 28–80 years and 31.4% were ≥60 years; 59.2% were overweight-obese. The main comorbidities associated with end-stage renal disease were hypertension in 37 patients (68.5%) and diabetes in 17 patients (31.5%). 44.5% were already in hemodialysis ≥36 months when the study started. According to the FRAIL scale, 6 (11.1%) were non-frail, 36 (66.7%) were pre-frail and 12 (22.92%) were frail, and according to the Edmonton Frail Scale, 42.6% were robust, 31.5% were pre-frail, and 25.9% were frail. Body mass index (BMI) was associated with frailty (OR 4.0, 95% CI 1.02–15.59). Based on the p-value of the results of bivariate analysis, BMI, age, dialysis vintage, and comorbidity (diabetes) were included in the multivariate analysis. The results of multivariate analysis showed that age and dialysis vintage were associated with frailty among Indonesian hemodialysis outpatients (OR 4.72, 95% CI 0.98–22.59 and OR 6.96, 95% CI 1.23–39.34, respectively.) Conclusion Approximately one in five hemodialysis outpatients in Indonesia is in a frail condition, highlighting a critical issue that demands urgent attention. Frailty is associated with older patients and shorter dialysis vintage. Our findings, despite being limited by a small sample size, a single center design, and a singular frailty assessment, indicate a high prevalence of frailty among hemodialysis outpatients in Indonesia. Therefore, it is imperative that the government, private sector, healthcare professionals, and the community collaboratively develop effective strategies and policies to address this issue.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".