Association between dialysis treatment and cognitive decline: A study from the Project in Sado for Total Health (PROST), Japan
Bibliographic record
Abstract
AIM: Evidence for the association between dialysis treatment and cognitive decline is limited. The present study aimed to determine whether dialysis treatment is associated with cognitive decline in adult outpatients of a general hospital in Japan. METHODS: This was a cross-sectional substudy of the Project in Sado for Total Health (PROST). Total Health PROST targeted adult outpatients of a general hospital in Sado City, Niigata, Japan. Among 753 patients (mean age 68.1 ± 11.6 years) analyzed, 66 received dialysis. Cognitive state was evaluated using the Mini-Mental State Examination, and those with a Mini-Mental State Examination score <24 were considered "cognitively declined." The prevalence of cognitive decline was compared by odds ratios calculated with multiple logistic regression analysis. Variables included in the analyses were dialysis, age, sex and self-reported histories of hypertension, diabetes, stroke and ischemic heart disease. RESULTS: Of the 66 dialysis patients, 24 (36.4%) showed cognitive decline, whereas 172 (25.0%) of 687 non-dialysis patients showed cognitive decline. The age and sex-adjusted odds ratio for cognitive decline in dialysis patients was 2.57 (95% confidence interval 1.43-4.61), relative to non-dialysis patients. The odds ratio remained significant (odds ratio 2.69, 95% confidence interval 1.49-4.88) even after adjusting for all covariates. CONCLUSION: The prevalence of cognitive decline was high in dialysis patients relative to non-dialysis patients among outpatients of a general hospital in Japan. Geriatr Gerontol Int 2017; 17: 1584-1587.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".