The effect of n-back training during hemodialysis on cognitive function in hemodialysis patients: a non-blind clinical trial
Bibliographic record
Abstract
Abstract Background Traditional vascular risk factors such as hypertension, diabetes mellitus, hyperlipidemia, cigarette smoking, and cardiovascular disease with myocardial infarction and atrial fibrillation have been linked to cognitive impairment in patients with chronic kidney disease. Therefore, interventions for cognitive function that can be performed during hemodialysis are needed. In this regard, n-back training has been demonstrated to be effective in patients with cognitive impairment. Methods In this pre-post study, 12 patients underwent n-back training during hemodialysis. The patients, aged 52–80 years, had mild cognitive impairment and were tested before and after a 3-month training period. This study was carried out in a single dialysis center. The Mini-Mental State Examination, Montreal Cognitive Assessment-Japanese version, Benton Visual Retention Test, Trail Making Test, visual cancelation task, Symbol Digit Modality Test, and Paced Auditory Serial Addition Task were used as outcome measures. Results All patients completed the 3-month training program. Improvements were seen in scores for the Mini-Mental State Examination (P = 0.01), Montreal Cognitive Assessment-Japanese version (P = 0.01), Benton Visual Retention Test (P = 0.02), Trail Making Test-B (P = 0.01), and Paced Auditory Serial Addition Task 1 s (P = 0.01) and 2 s (P = 0.01) from baseline to 3 months. Conclusions Cognitive training during hemodialysis improved cognitive and attention function in patients with mild cognitive impairment. This suggests that the simultaneous provision of n-back training and hemodialysis can be effective for treating chronic kidney disease with cognitive impairment. Trial registration UMIN Clinical Trials Registry ( UMIN000033742 ); retrospectively registered on August 13, 2018.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".