Examination of the proportion and characteristics of cognitive function changes during hospitalization in patients with cardiovascular diseases
Bibliographic record
Abstract
OBJECTIVE: Cognitive function decline is influenced by cardiovascular diseases and associated risk factors. However, changes in the cognitive function of patients with cardiovascular diseases during hospitalization and the factors influencing these changes remain unclear. This study elucidated the proportion and characteristics of changes in cognitive function during hospitalization in patients with cardiovascular diseases. METHODS: We conducted cognitive function assessments at admission and discharge for patients with cardiovascular diseases. Using the Mini-Mental State Examination (MMSE) and the Japanese version of the Montreal Cognitive Assessment (MoCA-J), we categorized the patients into cognitive impairment, mild cognitive impairment (MCI), and non-cognitive impairment. Changes in MMSE or MoCA-J scores of ≥2 points at discharge were classified as improvement or decline, and all others as maintenance. RESULTS: The cognitive impairment, MCI, and non-cognitive impairment categories comprised 215 (41.3%), 224 (40.2%), and 103 (18.5%) patients, respectively. The results of the cognitive function assessment at the time of discharge classified 90 patients (35.9%) into the maintenance group, 117 (46.6%) into the improvement group, and 44 (17.5%) into the decline group based on changes during hospitalization. There was a statistically significant difference among the three groups only in cognitive function at admission (P = 0.026). In multivariate analysis, those with MCI or cognitive impairment at admission and younger patients were associated with improved cognitive function during hospitalization. No factors were extracted that showed statistically significant associations with cognitive decline. CONCLUSION: Approximately half of the patients with cardiovascular disease experienced improvements in cognitive function during hospitalization, while approximately 20% showed a decline in cognitive function during the same period. These findings demonstrate the importance of assessing cognitive changes in hospitalized patients with cardiovascular disease. Future studies are needed to identify factors associated with changes in cognitive function.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".