Prevalence and Influence Factors of Cognitive Frailty in the Older Adult Patients Undergoing Maintenance Haemodialysis: A Multi‐Centre Cross‐Sectional Study
Bibliographic record
Abstract
AIMS: To examine the prevalence of factors of cognitive frailty in patients undergoing maintenance haemodialysis (MHD). DESIGN: A cross-sectional study. METHODS: From September 2023 to January 2024, 1023 patients undergoing MHD were recruited from 11 hospitals in Chengdu, China, using convenience sampling. The participants' sociodemographic and lifestyle factors, health information and laboratory indicators were assessed using a general information questionnaire. Cognitive frailty was assessed using the Fried Frailty Phenotype and Montreal Cognitive Assessment Scales. Multivariate logistic regression was used to examine the associations between cognitive frailty and sociodemographic and clinical characteristics. Independent variables for the multivariate logistic regression model encompassing age, sex, educational level, marital status, visual impairment, hearing impairment, falls within a year, depression, weight, height, Malnutrition-inflammation score and serum albumin, sodium, phosphorus, total cholesterol and creatinine levels. RESULTS: Among 1023 participants with a mean age of 69.52 years, 300 (29.3%) had cognitive frailty, with a predominance of older patients. Regression analysis showed that advanced age, low literacy and low serum creatinine, sodium and total cholesterol levels were positively correlated with cognitive frailty. Furthermore, 17.1% of the participants experienced depression, a risk factor for cognitive frailty, and malnutrition was an independent risk factor for cognitive frailty. CONCLUSION: Older adult patients undergoing (MHD) are at an increased risk of developing cognitive frailty. The aetiology of cognitive frailty in this cohort was multifactorial. Targeted interventions should be designed and implemented based on these factors, prioritising nutritional guidance and mood management to prevent or reverse cognitive frailty. REPORTING METHOD: The study adhered to the STROBE checklist. IMPACT: Older adult patients undergoing MHD are at increased risk of developing cognitive frailty. Cognitive frailty screening must be incorporated into the routine assessment of older patients undergoing MHD. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".