Impact of mild cognitive impairment on unplanned readmission in patients with coronary artery disease
Bibliographic record
Abstract
AIMS: To investigate the effect of mild cognitive impairment (MCI) on unplanned readmission in patients with coronary artery disease (CAD). METHODS AND RESULTS: From 2132 CAD patients, MCI was estimated with the Japanese version of the Montreal Cognitive Assessment (MoCA-J) in 243 non-dementia patients who met the study criteria. The primary outcome was unplanned hospital readmission after discharge. The incidence of MCI in this cohort was 33.3%, and 51 patients (21.0%) had unplanned readmission during a mean follow-up period of 418.6 ± 203.5 days. After adjusting for the covariates, MCI (hazard ratio, 2.28; 95% confidence interval: 1.09-4.76; P = 0.03) was independently associated with unplanned readmission in the multivariable Cox proportional hazard regression analysis. In the Kaplan-Meier analysis, the cumulative incidence of unplanned readmission for the MCI group was significantly higher than that for the non-MCI group (log-rank test, P < 0.001). Even after exclusion of the patients readmitted within 30 days of discharge, the main results did not change (log-rank test, P < 0.001). CONCLUSION: Mild cognitive impairment was independently associated with unplanned readmission after adjustment for many independent variables in CAD patients. In addition to its short-term effects, the adverse effects of MCI had a persistent, long-term impact on CAD patients. Assessment of cognitive function should be conducted by health professionals prior to hospital discharge and during follow-up. To prevent readmission of CAD patients, it will be necessary to support solutions to the problems that inhibit secondary prevention behaviours based on the assessment of the patients' cognitive function.
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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 | 0.001 |
| 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".