A Mixed Methods Study of Risk Factors for Frailty in Peritoneal Dialysis Patients
Bibliographic record
Abstract
OBJECTIVES: This study uses a convergent mixed methods approach to investigate the frailty phenotypes and risk factors in peritoneal dialysis (PD) patients. DESIGN: A cross-sectional mixed methods research study was employed. METHODS: This study follows the MMR-RHS reporting guidelines. From November 2023 to August 2024, 213 patients were recruited from the PD centre of a tertiary hospital in Chongqing, China. Quantitative data were collected using a general information questionnaire and standardised scales, including Fried Frailty Phenotype (FFP), Charlson Comorbidity Index (CCI), Mini Nutritional Assessment-Short Form (MNA-SF), Montreal Cognitive Assessment (MoCA) and Hospital Anxiety and Depression Scale (HADS). Concurrently, 19 PD patients in pre-frail or frail states participated in semi-structured interviews. The quantitative and qualitative findings were then integrated for analysis. RESULTS: Amongst the 213 PD patients, 46.5% were non-frail, 41.3% were pre-frail and 12.2% were frail. Integrated analysis indicated that fatigue and low muscle strength were the primary frailty phenotypes amongst the patients. Age, sedentary behaviour, comorbidities, nutritional status, cognitive function, polypharmacy, psychological state and social connections were identified as risk factors for frailty in this patient population. CONCLUSION: Many factors influence the frailty of PD patients. Future research should further explore the complex interactions amongst these factors and effective modulation strategies to mitigate the frailty progression. Incorporating the patients' perspectives in designing comprehensive intervention programmes will help identify key challenges and focal points for intervention. IMPACT: This study identifies risk factors for frailty in PD patients, offering healthcare professionals a basis for designing targeted interventions. These factors encompass multiple dimensions, indicating the need for multidisciplinary collaboration in managing frailty. PATIENT CONTRIBUTION: The PD patients in this study provided valuable quantitative data and shared their frailty experiences, enhancing the research conclusions' practical value.
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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 | 0.027 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".