Early intervention or watchful waiting for asymptomatic severe aortic valve stenosis: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The management of patients with severe but asymptomatic aortic stenosis is challenging. Evidence on early aortic valve replacement (AVR) versus symptom-driven intervention in these patients is unknown. METHODS: Electronic databases were searched, articles comparing early-AVR with conservative management for severe aortic stenosis were identified. Pooled adjusted odds ratio (OR) was computed using a random-effect model to determine all-cause and cardiovascular mortality. RESULTS: A total of eight studies consisting of 2201 patients were identified. Early-AVR was associated with lower all-cause mortality [OR 0.24, 95% confidence interval (CI) 0.13-0.45, P ≤ 0.00001] and cardiovascular mortality (OR 0.21, 95% CI 0.06-0.70, P = 0.01) compared with conservative management. The number needed to treat to prevent 1 all-cause and cardiovascular mortality was 4 and 9, respectively. The odds of all-cause mortality in a selected patient population undergoing surgical AVR (SAVR) (OR 0.16, 95% CI 0.09-0.29, P ≤ 0.00001) and SAVR or transcatheter AVR (TAVR) (OR 0.53, 95% CI 0.35-0.81, P = 0.003) were significantly lower compared with patients who are managed conservatively. A subgroup sensitivity analysis based on severe aortic stenosis (OR 0.24, 95% CI 0.11-0.52, P = 0.0004) versus very severe aortic stenosis (OR 0.20, 95% CI 0.08-0.51, P = 0.0008) also mirrored the findings of overall results. CONCLUSION: Patients with asymptomatic aortic valve stenosis have lower odds of all-cause and cardiovascular mortality when managed with early-AVR compared with conservative management. However, because of significant heterogeneity in the classification of asymptomatic patients, large scale studies are required.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.029 | 0.093 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it