P1584FRAILTY IN MAINTENANCE HEMODIALYSIS PATIENTS
Bibliographic record
Abstract
Abstract Background and Aims The population in Kazakhstan is rapidly aging, as a result the number of geriatric patients on maintenance hemodialysis (MHD) has been increasing. Frailty is prevalent in dialysis patients and is one of the common factors that can lead to increased morbidity and mortality. The primary objectives of this study were to evaluate the prevalence of frailty in elderly patients on MHD by using Edmonton Frailty Scale and assess their association with clinical and laboratory measurements. A secondary objective was to investigate the relationship between nutritional status and frailty. Method From July to September 2018, a total of 65 elderly patients undergoing HD in 7 dialysis facilities in Almaty, Kazakhstan were enrolled in this cross-sectional study. All participants were evaluated for the cognitive status through Mini-Mental State Examination (MMSE), nutritional status by using Mini Nutritional Assessment (MNA), Malnutrition-Inflammation Score (MIS), and anthropometric measurements (body mass index (BMI), triceps skinfold (TSF), mid-arm muscle circumference (MAMC)), functionality (Handgrip strength), as well biochemical data were collected from medical records. Frailty was defined in accordance with the Edmonton Frail scale (EFS). Results The study participants’ median age was 69 (range: 65–88) years old, and median dialysis vintage was 36 (IQR 15–60) months, 53.8% were female. The main comorbidities were hypertension (69.2%) and diabetes (35.4%). The prevalence of frailty assessed by the EFS was 23.1% (men: 13.3%; women: 86.7), 43.1% patients were non-frail (men: 64.3%; women: 35.7%), 33.8% patients were vulnerable (men: 45.5%; women: 54.5%). Based on MIS the prevalence of PEW was 73.8% and, according to MNA, the risk of malnutrition was detected in 47.7%, and 9.2% had malnutrition. No significant difference was observed between genders in the frequency of PEW. Mean body weight was 69.1±11.3kg, the mean BMI was slightly overweight 25.6±4.29kg/m2, while hand-grip strength was 21.33±3.36 in men and 15.5±5.51 in women, p=0.008, and it is lower than the normal population standard values. The frail patients group had a higher proportion of women 86.7% (p=0.001), worse nutritional status (93.3% and 86,7% had PEW evaluated by MIS (p=0.018) and MNA (p=0.035), respectively), more frequency of falls (p=0.01), anemia (p=0.038) when compared to group of non-frail and vulnerable patients. 66.7% of frail patients were widowed (p=0.005). The mean MMSE in this group of patients was 26.7±1.9. Conclusion The prevalence of frailty among elderly hemodialysis patients in this study was 23.1%, and we detected that 86.7% of them were female, as well PEW increased in frail patients. Also the study showed that protein-energy wasting is common among elderly hemodialysis patients. Its prevalence varies between 73.8% and 56.9% depending on the measurement tool used to evaluate the nutritional status. In our country with limited resources, EFS, MIS and MNA could help to follow elderly hemodialysis patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.005 | 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".