Prevalence of Cognitive Impairment among Peritoneal Dialysis Patients, Impact on Peritonitis and Role of Assisted Dialysis
Bibliographic record
Abstract
UNLABELLED: ♦ BACKGROUND: Chronic renal failure and aging are suggested as risk factors for cognitive impairment (CI). We studied the prevalence of CI among peritoneal dialysis (PD) patients using Montreal Cognitive Assessment (MoCA), its impact on PD-related peritonitis in the first year, and the potential role of assisted PD. ♦ METHODS: One hundred fourteen patients were newly started on PD between February 2011 and July 2013. Montreal Cognitive Assessment was performed in the absence of acute illness. Data on patient characteristics including demographics, comorbidities, blood parameters, dialysis adequacy, presence of helpers, medications, and the number PD-related infections were collected. ♦ RESULTS: The age of studied patients was 59±15.0 years, and 47% were female. The prevalence of CI was 28.9%. Patients older than 65 years old (odds ratio [OR] 4.88, confidence interval [CI] 1.79 - 13.28 p = 0.002) and with an education of primary level or below (OR 4.08, CI 1.30 - 12.81, p = 0.016) were independent risk factors for CI in multivariate analysis. Patients with PD-related peritonitis were significantly older (p < 0.001) and more likely to have CI as defined by MoCA (p = 0.035). After adjustment for age, however, CI was not a significant independent risk factor for PD-related peritonitis among self-care PD patients (OR 2.20, CI 0.65 - 7.44, p = 0.20). When we compared patients with MoCA-defined CI receiving self-care and assisted PD, there were no statistically significant differences between the 2 groups in terms of age, MoCA scores, or comorbidities. There were also no statistically significant differences in 1-year outcome of PD-related peritonitis rates or exit-site infections. ♦ CONCLUSION: Cognitive impairment is common among local PD patients. Even with CI, peritonitis rate in self-care PD with adequate training is similar to CI patients on assisted PD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".