2-4THE RISK OF STROKE IN HYPERTENSIVE PATIENTS WITH LEFT VENTRICULAR HYPERTROPHY DETERMINED BY ELECTROCARDIOGRAPHIC DIAGNOSTIC CRITERIA: A SYSTEMATIC REVIEW AND META-ANALYSES
Bibliographic record
Abstract
Introduction: Hypertensive patients with left ventricular hypertrophy (LVH) as determined by electrocardiographic (ECG) diagnostic criteria are at increased risk for stroke. This systematic review and meta-analysis aimed to evaluate the risk for hypertensive patients with LVH to develop stroke. Methods: A literature search with a predetermined search strategy was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. Databases were gathered from Pubmed, MEDLINE Complete via EBSCOhost, and Proquest. Articles were reviewed based on following criteria: studies’ participants are hypertensive, having left ventricular hypertrophy evaluated by valid diagnostic criteria, not combined with other diagnostic tools and compared with control group having normal heart structure; outcome assessment are related to cerebrovascular event; sample size is at least 30 participants; follow-up period of at least 1 year; relevant study design, participant characteristics, and results. We assess the quality of studies using the Cochrane Risk of Bias Tool 2.0, Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement, and Newcastle Ottawa Scale (NOS). Between-study heterogeneity was evaluated using the Cochran Q test (v2). Results: The search strategy identified 131 studies. After article selection, we included seven articles to be analyzed qualitatively and two articles into meta-analysis. All cohort studies have adequate reporting qualities with a high-quality assessment score (8.0). All randomized trials have a low risk of bias. Our meta-analysis using fixed-effect found that LVH evaluated by Cornell Product (CP) in hypertensive patients, 45–80 years old, had a 22% higher risk for stroke compared with patients without LVH by a follow up of around five years (HR, 1.22; 95% CI, 1.06–1.40; p = 0.005). When evaluated by Sokolow-Lyon criteria, the risk was increased to 61% (HR, 1.61; 95% CI, 1.37–1.90; p < 0.00001). When random effects are applied, we identified an insignificant risk for patients evaluated by CP, while the result remained to be significant if using SL. Conclusion: There is a significantly increased risk for hypertensive patients having LVH to develop stroke within five years when analyzed by SL criteria. Evaluation using CP criteria have an inconsistent result when fixed, and the random effect was applied. Thus, future studies with a larger sample size need to be conducted.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.040 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".