Vers une autonomie croissante de l'apprenant du francais langue etrangere (Toward an Increasing Autonomy of the French as a Foreign Language Learner)?.
Bibliographic record
Abstract
The Marfan syndrome (MFS) patients are highly predisposed to thoracic aortic aneurysm and/or dissection, with virtually every patient having evidence of aortic disease at some point during their lifetime. We conducted a meta-analysis to investigate the efficacy of angiotensin receptor blockers (ARBs) in slowing down the progression of aortic dilatation in MFS patients. PUBMED, EMBASE, and COCHRANE databases were searched for relevant articles published from inception to February 1, 2020. We included randomized clinical trials evaluating the effect of ARBs on aortic root size in patients with MFS with a follow-up period of at least 2.5 years. Seven studies were included with a total of 1,510 patients. Our analysis demonstrated a significantly smaller change in aortic root and ascending aorta dilation in the ARBs treated group when compared with placebo (mean difference 0.68; 95% confidence interval [CI] -1.31 to -0.04; p = 0.04, I<sup>2</sup> = 94%, and mean difference -0.13, 95% CI -0.17 to -0.09; p < 0.00001, I<sup>2</sup> = 0%, respectively). ARBs as an add-on therapy to beta-blockers resulted in a significantly smaller change in aortic root dilation when compared with the arm without ARBs (mean difference -2.06, 95% CI -2.54 to -1.58; p < 0.00001, I<sup>2</sup> = 91%). However, there was no statistically significant difference in the number of clinical events (aortic complications/surgery) observed in the ARBs arm when compared with placebo (Risk ratio of 1.01, 95% CI 0.74 to 1.38; p = 0.94, I<sup>2</sup> = 0%). In conclusion, ARBs therapy is associated with a slower progression of aortic root dilation when compared with placebo and as an addition to beta-blocker therapy.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".