ASSESSMENT OF COGNITIVE FUNCTION IN PATIENTS WITH CHRONIC KIDNEY DISEASE
Bibliographic record
Abstract
Objectives: The objectives of this study were to evaluate cognitive profile in patients with chronic kidney disease (CKD) pre-dialysis and post-dialysis, to assess the severity of cognitive impairment in patients with kidney disease before and after dialysis, and to determine the association of cognitive impairment in relation to dialysis.Methods: A total of 59 patients were recruited with CKD Stage V on dialysis for >6 months. Cognitive function of the patient was assessed by Montreal Cognitive Assessment test scale method for three intervals (before dialysis and two intervals post-dialysis), and the incidence of impairment was analyzed using one-way ANOVA variance test.Results: Among the 59 patients, there were 13 patients with the age of 18–33 years (22.033%), 11 patients with from age 34 to 49 years (18.64%), 21 patients at the age of 50–65 years (35.59%), and 15 patients around 66–80 years (25.42%). From the above categories, population with the age of 50–65 years is at maximum affected by CKD. Among the 59 patients, 24 patients (40.677%) are male and 35 patients (59.33%) are female. There was a mild significant difference seen in cognitive functioning between pre-dialysis and post-dialysis (p≤0.02).Conclusion: It was found that patients with CKD had mild-to-moderate cognitive dysfunction due to morbidities associated with CKD. Inthis study, significant differences of cognitive function result in CKD patients and the severity of cognitive impairment was associatedwith the severity of the kidney disease, which improved with dialysis. Finally, our study suggests that cognitive performance wasimproved after initiation of dialysis and that further management through medications could provide a better outcome in cognitiveperformance.
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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 | 0.002 |
| 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 | 0.000 | 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".