Association between ranolazine therapy and cognitive decline in elderly patients with ischemic heart disease
Bibliographic record
Abstract
Introduction: Ischemic Heart Disease (IHD) represents one of the major causes of mortality and morbidity in the geriatric population This clinical complexity of these patients substantially impacts their quality of life and is associated with an increased risk of cognitive impairment (CoI). Ranolazine, plays a pivotal role in managing anginal symptoms and improving exercise tolerance. Objective: To investigate the potential protective effect of Ranolazine on CoI over time in elderly patients with IHD and multiple comorbidities. Methods: We performed a single-center, prospective, observational cohort study. The primary endpoint was a reduction in MMSE score ≥3 points during follow-up compared to baseline values. Results: 519 patients with a mean age of 74.2 ± 6.8 years were enrolled and divided into two groups based on Ranolazine use. The groups demonstrated comparable distribution by sex; however, Ranolazine group, although younger, displayed increased severity of anginal symptoms (Canadian Angina Scale 2.6 vs. 2.3; p < 0.0001), higher prevalence of previous acute coronary syndrome (p < 0.046), sarcopenia (p < 0.0001), and type 2 diabetes mellitus (p < 0.040). During a 4-year follow-up, 186 cases of CoI were observed (8.9 events/100 patient-years) in the general population. The incidence of CoI was significantly lower in the Ranolazine group compared to the control group (5.7 vs. 10.3 events/100 patient-years; p < 0.001). Multivariate analysis revealed a statistically significant association between CoI and the use of Ranolazine, GLP-1RAs, and SGLT2i. Specifically, Ranolazine use was associated with a 61% odds reduction in CoI. Conclusion: The use of Ranolazine is associated with a significant odds reduction in CoI in elderly patients with IHD and multiple comorbidities. The neuroprotective effect of Ranolazine may be attributed to the improvement of anginal symptoms and consequent optimization of functional status and quality of life, advocating for a comprehensive therapeutic strategy in geriatric patient management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".