Comparative Risk Assessment in Hypertensive Patients With Metabolic Syndrome by Exploring Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers
Bibliographic record
Abstract
Cognitive impairment is a common clinical complication in patients with hypertension and metabolic syndrome. Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) are common antihypertensive agents popularly used, but their relative effects on cognitive outcomes are ambiguous. The aim of this study was to compare the effect of ARB versus ACEI on cognitive decline in hypertensive patients with or at risk of metabolic syndrome. We performed a systematic review and meta-analysis based on the PRISMA 2020 guidelines. Searches were performed in PubMed, Embase, Scopus, and Web of Science up to April 2025. The review included studies with adults ≥50 years and trials comparing ARBs vs ACEIs, with the results involving cognitive outcomes. Studies of both cohorts and randomized controlled trials (RCTs) were eligible. Bias risk was analyzed using the Newcastle-Ottawa scale (version 2011) and Cochrane RoB 2.0. Random-effects meta-analysis was performed, and evidence was graded using GRADE (Grading of Recommendations, Assessment, Development, and Evaluations). Ten studies (six cohort studies, three prospective studies, one RCT) with over 6.5 million participants were included. Cognitive outcomes included mild cognitive impairment, dementia, and amyloid accumulation. ARBs were associated with an 11% lower risk of cognitive decline compared to ACEIs (HR: 0.89; 95% CI: 0.80-0.98; I² = 0%). Subgroup analysis showed that there were stronger effects for cognitive versus cardiovascular outcomes. Blood-brain barrier-penetrant ARBs provided additional benefits, particularly in APOE ε4 carriers. The overall certainty of evidence was moderate. In hypertensive patients, especially those meeting the criteria for metabolic syndrome, ARBs were linked with stronger cognitive protection than ACEIs. These observations encourage ARB use in those who were susceptible to cognitive decline, but additional trials are needed for confirmation.
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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 | 0.025 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".