A cross‐sectional study exploring cognitive impairment in kidney failure
Bibliographic record
Abstract
BACKGROUND: Little is known of the prevalence or associated factors of cognitive impairment in people with kidney failure. Assessment of cognition is necessary to inform comprehension of healthcare information, aptitude for dialysis modality and informed decision making. OBJECTIVES: This study sought to determine the prevalence and factors associated with cognitive impairment in people with kidney failure. DESIGN: Prospective cross-sectional. PARTICIPANTS: Participants (n = 222) with chronic kidney disease grade 5 (CKD G5) including those not treated with dialysis, those undertaking dialysis independently or in a facility (CKD 5D), and those with a kidney transplant (CKD 5T). MEASUREMENTS: Data were collected using the Montreal Cognitive Assessment tool, the Hospital Anxiety and Depression Scale (only the depression subscale), and a demographic questionnaire. Type of kidney disease and comorbidities were extracted from participants' hospital records. RESULTS: Participants were 61 ± 13.63 years old; most were male (61.26%), and diabetes was the primary cause of kidney disease (34%). Prevalence of cognitive impairment was 34% although it was significantly higher for those in CKD G5 compared with other groups. A number of factors were found to be associated with cognitive impairment including, age, diabetes, hypertension, education, haemoglobin, albumin, parathyroid hormone, CKD G5, and length of time on treatment. CONCLUSIONS: Cognitive impairment in kidney failure is common and it has significant implications for informed decision making and treatment choices. Routine assessment of cognitive function is an important part of clinical practice.
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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".