Sensitivity and specificity of the Brazilian version of the Montreal Cognitive Assessment – Basic (MoCA-B) in chronic kidney disease
Bibliographic record
Abstract
Abstract Introduction Cognitive impairment in chronic kidney disease (CKD) is commonly associated with neuropsychiatric disorders. As a complex pathology, at all stages of CKD patients need to have a good understanding of the need for drug and nutritional adherence. Cognitive screening is the starting point for detection of cognitive impairments. Objective To determine the specificity and sensitivity of the Brazilian Portuguese version of the Montreal Cognitive Assessment – Basic (MoCA-B) for identification of cognitive impairment in the CKD population. Methods This was a cross-sectional study with 163 CKD patients undergoing hemodialysis treatment. The Mini-Mental State Examination (MMSE) and MoCA-B were administered. Results The MoCA-B has reliable internal consistency (Cronbach’s alpha = 0.74). A cutoff point of ≤ 21 points provides the best sensitivity and specificity for detection of cognitive impairment. The education variable had less impact on the total MoCA-B score than on the total MMSE score. Conclusions The MoCA-B is a suitable screening instrument for evaluating the global cognition of hemodialysis patients. The results can help health professionals to conduct evaluations and plan clinical management.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".