Cognitive Disorders in Patients with Cardiac Angina Referred to Sayad Shirazi Hospital in 2024
Bibliographic record
Abstract
Background: Cognitive disorder occurs when a person has difficulty remembering, learning new things, concentrating, or making decisions that affect their daily life. There is a relationship between cardiovascular-coronary diseases and the risk factors of these diseases with cognitive disorders. Objectives: The present study was conducted with the aim of investigating cognitive disorder in patients with unstable cardiac angina compared to non-sufferers. Methods: This case-control study was conducted on 45 patients with unstable cardiac angina and 45 non-sufferers referred to Sayad Shirazi Hospital in 2024. The tool for data collection was the Montreal cognitive assessment test (MoCA). Data were analyzed using SPSS version 23 software with the Chi-square test and Fisher's exact test. The risk and effective factors associated with developing the disease were measured using logistic regression and expressed as odds ratios (OR) with a 95% confidence interval (CI). Results: Although the cognitive status of cardiac angina patients compared to non-sufferers was suggestive of mild cognitive disorders (MCI), the difference was not statistically significant (P = 0.31). The risk of cognitive disorder in people with cardiac angina was 1.71 times higher (OR = 1.71, P = 0.21, 95% CI: 0.74 - 3.94) than in those without cardiac angina. The risk of cognitive disorder in men with cardiac angina was 4.35 times higher (OR = 4.35, P = 0.21, 95% CI: 1.19 - 15.86) than in women, and in diabetics with cardiac angina, it was 5.78 times higher. Conclusions: The risk of cognitive disorder is higher in people with cardiac angina. Also, men and diabetics with unstable angina are more susceptible to cognitive disorders.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".