Using Montreal Cognitive Assessment (MOCA) Test to Guide Peritoneal Dialysis Strategy: From Candidate Evaluation to Ongoing Care
Bibliographic record
Abstract
Background: Peritoneal Dialysis (PD) is a home dialysis technique, while patient or patient's assistant are responsible to perform the dialysis. Successful treatment requires appropriate physical and cognitive skills. Patients with CKD are at increased risk for developing cognitive impairment, before and after onset of dialysis. Early detection of cognitive impairment is essential in PD patients, given the technique's reliance on patient autonomy and self-management. Montreal Cognitive Assessment (MoCA) test is a simple and easy-to-apply test, validated for assessment of global cognitive function. Methods: In our PD unit we started to use MoCA test for all elderly (>65 years old) PD candidates and in doubtable and inconclusive cases on PD in June 2023. This is a retrospective analysis of MoCA test results obtained between July 2023 to April 30, 2025, in our PD unit, in conjunction with the corresponding clinical data. Results: MoCA test was performed on 37 patients, 20 were predialysis, and 17 were already treated by PD. Mean age of all patients was 76.9 years. Dialysis mean vintage was 2.2 years. Mean MoCA result was 21.2 (13-29). In predialysis group mean MoCA score was 21 (15-25) vs 21.3 (13-29) in dialysis group. Predialysis patients with score 18 and less were not able to perform PD independently: 3 of them were excluded from PD program, three others perform assisted PD. In prevalent PD patients results were different: only one patient (MoCA score 13) was unable to perform PD independently, one other deteriorated cognitively after started PD and now is treated with assisted PD, all other patients regardless of MoCA score continue to perform PD by themselves. Conclusion: Some grade of impaired cognitive function is common among old and very old CKD patients and patients treated by PD. According to our data, a MoCA score of at least 18 is required to the successful learning of PD performance. However, for continuation PD in prevalent patients who are already familiar with the technique, a MoCA score as low as 15 may be sufficient. Patient with score ranging from 18 to 21 are classified as high-risk and we emphasize more intensive training, individualized according to detailed MoCA assessments and closer follow-up for these patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".