Prevalence of mild cognitive impairment in automated peritoneal dialysis patients
Bibliographic record
Abstract
BACKGROUND: Cognitive deterioration decreases quality of life, self-care and adherence to treatment, increasing mortality risk. There is scarce information of cognitive impairment in peritoneal dialysis (PD) and data are controversial. Our aim was to determine the frequency and associated factors of cognitive impairment in patients on automated PD (APD). METHODS: In this cross-sectional study, 71 patients on APD underwent clinical, biochemical and cognitive function evaluation by means of the Mini Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Cognitive function was also evaluated in healthy controls. RESULTS: Participants mean age was 42 ± 16 years, 79% were men and dialysis vintage was 17 months ( interquartile range 7-32). In APD patients, cognitive impairment was present in 7% (mild deterioration) and 68% according to the MMSE and MoCA, respectively, and 4 and 37% in the healthy controls. Patients with cognitive impairment (according to MoCA) were older, with less education, had diabetes more frequently and higher serum glucose as well as lower serum creatinine, phosphorus and sodium concentrations than patients with normal cognitive function. In multiple linear regression analysis, predictors for the MoCA score (R2 = 0.63, P = 0.002) were education {B = 0.54 [95% confidence interval (CI) 0.20-0.89]; P = 0.003}, age [B = -0.11 (95% CI -0.21 to -0.01); P = 0.04], serum sodium [B = 0.58 (95% CI 0.05-1.11); P = 0.03] and creatinine concentration [B = 3.9 (95% CI 0.03-0.83); P = 0.03]. CONCLUSIONS: In this sample of APD patients, the prevalence of cognitive impairment by the MoCA was 65% and was associated with older age, lower education level and lower serum concentrations of sodium and creatinine.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".