Cognitive Decline among Older Adults who Developed Acute Coronary Syndrome During Hospitalization for Non-cardiac Illness
Bibliographic record
Abstract
Background: Atypical presentations of acute coronary syndrome (ACS) delay its recognition and treatment in the elderly patients. Functional decline and delirium which are common to the elderly during hospitalization, leads to cognitive impairment and poor health outcomes. Steps taken for its prevention is usually not considered the top priority by the cardiologist. The present study was conducted to identify cognitive decline among elderly patients who developed ACS during hospitalization for noncardiac illness and their outcome. Materials and Methods: Three hundred and ten elderly patients above 60 years of age with ACS were included from June 26, 2020 to October 13, 2020. Subjects were divided into those admitted primarily due to an ACS (Group I, n = 94) and those developing ACS following admission for noncardiac illness (Group II, n = 216). Co-morbidities, medications, investigations, management, clinical outcome, and Montreal Cognitive Assessment scale were compared between the two groups at the time of admission, after 30 days and after 6 months. Results: Majority of the subjects were admitted due to acute kidney injury (27.1%) in Group II and had a non-ST elevation ACS (90.2%). Optimum management was given to a lesser extent due to the clinical condition of these patients. Poor clinical outcome, cognitive impairment during hospitalization and cognitive decline during follow-up was more in Group II. Conclusion: Clinicians must be vigilant for the development of cognitive impairment and cognitive decline when an elderly patient is admitted to the hospital, as early detection and optimum management provides better clinical and cognitive outcome.
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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 | 0.000 | 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".