A systematic review of the pharmacological management of aortic root dilation in Marfan syndrome
Bibliographic record
Abstract
BACKGROUND: Marfan syndrome causes aortic dilation leading to dissection and death. This systematic review examined the use of beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers in the management of aortic dilation in this disease. METHODS: We searched four databases--Medline, EMBASE, Web of Science, and The Cochrane Central Register of Controlled Trials--two conference proceedings, references of retrieved articles, and a web-based trial registry. The primary outcome was mortality. The secondary outcomes were aortic dissection, need for elective surgical repair, change in aortic dilation, and adverse events. Two reviewers selected studies, abstracted data, and assessed study quality. Meta-analyses were not performed because of study heterogeneity. RESULTS: A total of 18 studies were included--12 completed and six in progress. Of the completed studies, three before-and-after treatment, one prospective cohort, three retrospective cohorts, and two randomised control trials examined beta-blockers; one randomised and one non-randomised trial examined angiotensin-converting enzyme inhibitors; and one retrospective cohort study examined angiotensin II receptor blockers. Studies in progress are all randomised trials. Mortality was not impacted by drug therapy, although studies were underpowered with respect to this outcome. All drug classes were associated with a decrease in the rate of aortic dilation (angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers >beta-blockers); none had an impact on other secondary outcomes. CONCLUSIONS: On the basis of existing evidence, beta-blockers, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers slow the progression of aortic dilation in Marfan syndrome. Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers may have more effect than beta-blockers; however, more methodologically rigorous studies currently in progress are needed to evaluate the impact of drug therapy on clinical outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".