Metabolic Syndrome and Ischemic Stroke Risk by Sex: Meta-analysis (I12-2B)
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MetS) is a prevalent constellation of vascular risk factors, including elevated blood pressure, elevated blood glucose, obesity, and dyslipidemia. The differential effect of metabolic syndrome and stroke risk by sex has not been well characterized. OBJECTIVE: To examine the association of the metabolic syndrome and risk of ischemic stroke in men and women through meta-analysis of prospective studies. DESIGN/METHODS: We comprehensively searched PubMed, Cochrane library, and bibliographies of major articles from 1980 to 2014 using pre-specified key terms. Prospective studies were included if they reported MetS prevalence and stroke risk in women and men. Two reviewers independently assessed studies to determine eligibility. Multivariate adjusted risk estimates of stroke with 95[percnt] confidence interval were used as measures of the association between MetS and comparison between women and men. Pooled risk ratio estimates across trials were synthesized by using a random-effects model based on Mantel-Haenszel methods. Forest plots were constructed. RESULTS: Of 1,364 articles retrieved, 7 studies met eligibility criteria with 47,219 participants and 1,472 stroke events. Forty-nine percent of participants were women. Prevalence of MetS in women was 30[percnt] (95[percnt] confidence interval [CI] 29[percnt]-31[percnt]), in men was 23.6[percnt] (95[percnt] CI 19.1-28.9[percnt]). Women with MetS had a near 4-folds increased risk for stroke compared to those without MetS (risk ratio [OR] 3.98, 95[percnt]CI 2.9-5.6). The MetS effect on stroke was less on men (RR 2.21, 95[percnt]CI 1.43-3.40). CONCLUSIONS: The metabolic syndrome is prevalent, and a significant risk factor for ischemic stroke with differential effects by sex. Women with metabolic syndrome had a near 2 folds higher stroke risk than men with metabolic syndrome. Future studies are needed to elucidate the mechanism by which the metabolic syndrome exerts higher stroke burden on women.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.091 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".