Hypertension in thoracic aortic aneurysm and dissection: considerations in the choice of antihypertensive agents for the long-term management
Bibliographic record
Abstract
Abstract Background Thoracic aortic aneurysm (TAA) is a life-threatening condition that often remains asymptomatic until a catastrophic aortic dissection (TAD) occurs. Hypertension is a major risk factor, yet current guidelines provide limited direction on the most effective antihypertensive strategy. Prior concerns regarding calcium channel blockers (CCBs) and aortic pathology have further complicated treatment decisions. To address this critical gap, we conducted the first head-to-head comparison of different antihypertensive classes in managing both TAA and TAD. Methods A comprehensive systematic review was performed, screening over 6,000 studies from MEDLINE and EMBASE up to August 2024. A total of 27 studies met inclusion criteria and were analyzed. Results Hypertension significantly increases the risk of both TAA (HR 1.77, 95% CI: 1.47–2.13, p<0.01) and TAD (HR 2.51, 95% CI: 1.75–3.60). Among antihypertensive agents, CCBs demonstrated the greatest reduction in adverse outcomes (HR 0.46, 95% CI: 0.32–0.67, p<0.01), followed by beta-blockers (HR 0.61, 95% CI: 0.45–0.84, p=0.002) and ARBS/ACE inhibitors(HR 0.75, 95% CI: 0.66–0.85, p<0.0001). Notably, beta-blockers provided significant protection in Type B dissection but did not show a marked reduction in adverse events for Type A dissection whereas ACE inhibitors/ARBs did show significant protection for type A dissection. Conclusion Our findings highlight the outsized role of hypertension in driving aortic disease, with an even stronger link to dissection than aneurysm formation. CCBs emerge as the most effective therapy, particularly for Type B dissection, followed by beta-blockers and ARBS/ACE inhibitors. These insights provide critical evidence to optimize antihypertensive management in high-risk patients, potentially influencing future clinical guidelines.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".