Prevalence and Prognosis of Coexisting Frailty and Cognitive Impairment in Patients on Continuous Ambulatory Peritoneal Dialysis
Bibliographic record
Abstract
The aim of this study was to investigate the prevalence of coexisting frailty and cognitive impairment and its association with clinical outcomes in patients on continuous ambulatory peritoneal dialysis (CAPD). Patients on CAPD started to enroll from 2014 to 2016 and ended follow-up by 2017. Frailty was assessed by clinical frailty scale (CFS), and cognitive function was assessed by Montreal Cognitive Assessment (MoCA). Totally 784 CAPD patients were recruited, with median duration of PD 30.7 (8.9~54.3) months. The mean age was 48.8 ± 14.6 years, 320 (40.8%) patients were female and 130 (16.6%) had diabetic nephropathy. Patients with cognitive impairment were more than those with frailty (55.5% vs. 27.6%). Coexisting frailty and cognitive impairment was present in 23.9% patients. Pathway analysis showed that CFS score was negatively associated with MoCA score (β = -0.69, P < 0.001). Coexisting frailty and cognitive impairment was associated with decreased patient survival rate (Log-rank = 84.33, P < 0.001) and increased peritonitis rate (0.22 vs. 0.11, 0.15 and 0.12 episodes per patient year, respectively; all P < 0.001). It was concluded that there was a relatively high prevalence of coexisting frailty and cognitive impairment among patients on CAPD. Frailty was positively associated with cognitive impairment. Coexisting frailty and cognitive impairment increased the risk of adverse outcomes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".