Randomised study for the Optimal Treatment of symptomatic patients with low-gradient severe Aortic valve Stenosis and preserved left ventricular ejection fraction (ROTAS trial)
Bibliographic record
Abstract
BACKGROUND: The best management of symptomatic patients with low-gradient (LG) severe aortic stenosis (AS) and preserved left ventricular ejection fraction (LVEF) has not been established. The Randomised study for the Optimal Treatment of symptomatic patients with low-gradient severe Aortic valve Stenosis (ROTAS) trial aimed to assess the superiority of aortic valve replacement (AVR) versus medical treatment (MT) in this specific group of AS patients. METHODS: Patients with symptomatic LG severe AS and preserved LVEF (>50%) underwent dobutamine stress echocardiography and/or CT-aortic calcium score to confirm AS severity and were then randomised 1:1 to AVR or MT. The primary endpoint was a composite of overall death and/or cardiovascular hospitalisation. RESULTS: The ROTAS study was stopped early because of insufficient recruitment. In the end, only 52 patients (age 79±7 years; women 54%; NYHA III-IV 27%; median STS score 3.3%) were included in the study. During follow-up (mean: 14±7 months), the primary endpoint occurred in 12 (23%) patients. Compared with MT, AVR was not associated with a significant prognostic benefit (events: 5/26 (19%) vs 7/26 (27%) (HR 0.76, 95% CI 0.24 to 2.39, p=0.63). During follow-up, 11 (42%) patients in the MT group developed class I criteria for AVR or severe symptoms justifying a cross-over to the AVR group. CONCLUSIONS: Because of the small number of included patients and short follow-up the ROTAS trial was underpowered and unable to demonstrate a difference in the study endpoint between treatment arms. In patients in the MT arm, a regular echocardiographic and clinical assessment might be useful to disclose those developing class I indications of AVR or severe AS-related symptoms. TRIAL REGISTRATION NUMBER: NCT01835028.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".