AI Article Synopsis
- - The study aimed to explore how three atherosclerosis indexes relate to the risk of stroke in individuals aged 65 and older from China between 2011 and 2015.
- - Using multivariate logistic regression, researchers found that the highest quartiles of the atherogenic index of plasma (AIP), Castelli risk index I (CRI-I), and Castelli risk index II (CRI-II) indicated increased odds of stroke compared to the lowest quartiles.
- - The findings suggest that higher levels of these atherosclerosis indexes significantly correlate with an increased risk of stroke, highlighting their potential as predictive factors in elderly populations.
Article Abstract
Background: To evaluate the associations of three atherosclerosis indexes with stroke in a population aged 65 years and older.
Methods: A sample was obtained from wave 2011 to wave 2015 of the China Health and Retirement Longitudinal Study. Multivariate logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for stroke in the quartiles of three atherosclerosis indexes, and restricted cubic splines were constructed.
Results: Four hundred and fifty-four of the 21,913 eligible participants had stroke. After multivariate adjustments and with respect to the lowest quartiles, the ORs (95% CIs) of stroke in the highest quartiles of the atherogenic index of plasma (AIP), the Castelli risk index I (CRI-I), and the Castelli risk index II (CRI-II) were 1.35 (0.99-1.83), 1.52 (1.13-2.06), and 1.40 (1.05-1.86), respectively. When assessed as a continuous exposure, per-unit increases in the AIP, CRI-I, and CRI-II were independently associated with a 49% (OR: 1.49, 95% CI: 1.07-2.08), 6% (OR: 1.06, 95% CI: 1.02-1.11), and 14% (OR: 1.14, 95% CI: 1.03-1.27) increase in the risk of stroke, respectively.
Conclusion: The three atherosclerosis indexes studied-the AIP, CRI-I, and CRI-II-were found to be predictors of stroke in a Chinese population.
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|---|---|
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315396 | PLOS |
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11658487 | PMC |
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