The prevalence of cognitive impairment and its corresponding risk factors in patients with hemodialysis
Bibliographic record
Abstract
Objective To explore the prevalence of cognitive impairment and its corresponding risk factors in patients with hemodialysis. Methods Using a cross-sectional design,we measured cognitive function in 123 hemodialysis patients aged 31 years and above. Cognitive performance was measured with Chinese version of The Montreal Cognitive Assessment (MoCA). The corresponding risk factors were investigated spontaneously. Results Of 123 subjects who completed the investigation,84 cases were classified with cognitive impairment and the prevalence of cognitive impairment reached 68.3%. Multi-factor Logistic regression analysis indicated that eld (OR=1.090; 95% CI:1.034-1.147; P=0.001),male(OR=5.213; 95% CI:1.758-15.455; P=0.003),education time no more than 5 years (OR=0.076; 95% CI:0.014-0.420; P=0.003)and hypertention (OR=6.891; 95% CI:2.042-23.258; P=0.002)were independent risk factors of cognitive impairment in hemodialysis patients. Conclusions Hemodialysis patients are at high risk for cognitive impairment. Eld,male,education time no more than 5 years and hypertension were its independent risk factors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".