Prevalence and patterns of cognitive impairment in adult hemodialysis patients: the COGNITIVE-HD study
Bibliographic record
Abstract
Background: Mounting evidence indicates an increased risk of cognitive impairment in adults with end-stage kidney disease on dialysis, but the extent and pattern of deficits across the spectrum of cognitive domains are uncertain. Methods: We conducted a cross-sectional study of 676 adult hemodialysis patients from 20 centers in Italy, aiming to evaluate the prevalence and patterns of cognitive impairment across five domains of learning and memory, complex attention, executive function, language and perceptual-motor function. We assessed cognitive function using a neuropsychological battery of 10 tests and calculated test and domain z-scores using population norms (age or age/education). We defined cognitive impairment as a z-score ≤ -1.5. Results: Participants' median age was 70.9 years (range 21.6-94.1) and 262 (38.8%) were women. Proportions of impairment on each domain were as follows: perceptual-motor function 31.5% (150/476), language 41.2% (273/662), executive function 41.7% (281/674), learning and memory 42.2% (269/638), complex attention 48.8% (329/674). Among 474 participants with data for all domains, only 28.9% (n = 137) were not impaired on any domain, with 25.9% impaired on a single domain (n = 123), 17.3% on two (n = 82), 13.9% on three (n = 66), 9.1% on four (n = 43) and 4.9% (n = 23) on all five. Across patients, patterns of impairment combinations were diverse. Conclusions: In conclusion, cognitive impairment is extremely common in hemodialysis patients, across numerous domains, and patients often experience multiple deficits simultaneously. Clinical care should be tailored to meet the needs of patients with different types of cognitive impairment and future research should focus on identifying risk factors for cognitive decline.
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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) | 0.000 | 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 | 0.001 |
| 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".