Cardiac Damage Staging Classification in Asymptomatic Moderate or Severe Primary Mitral Regurgitation
Bibliographic record
Abstract
Background Optimal timing for intervention remains uncertain in asymptomatic patients with primary mitral regurgitation (MR). We aimed to assess the prognostic value of a new cardiac damage staging classification in patients with asymptomatic moderate or severe primary MR. Methods Clinical, Doppler-echocardiographic, and outcome data prospectively collected in 338 asymptomatic patients (64 ± 15 years, 68% men) with at least moderate primary MR were retrospectively analyzed. Patients were hierarchically classified as per the following staging classification: no cardiac damage (stage 0), mild left ventricular or left atrial damage (stage 1), moderate or severe left ventricular or left atrial damage (stage 2), pulmonary vasculature or tricuspid valve damage (stage 3), or right ventricular damage (stage 4). Results There was a stepwise increase in 10-year mortality rates as per cardiac damage stage: 20.0% in stage 0, 25.6% in stage 1, 31.5% in stage 2, and 61.3% in stage 3-4 ( p < 0.001). The staging classification was significantly associated with increased risk of mortality (hazard ratio=1.41 per one-stage increase, 95% confidence interval: 1.07-1.85, p = 0.015) and the composite of cardiovascular mortality or hospitalization (hazard ratio=1.51 per one-stage increase, 95% confidence interval: 1.07-2.15, p = 0.020) in multivariable analysis adjusted for EuroSCORE II, mitral valve intervention as a time-dependent variable, and other risk factors. The proposed scheme showed incremental value over several clinical variables (net reclassification index=0.40, p = 0.03). Conclusions The new staging classification provides independent and incremental prognostic value in patients with asymptomatic moderate or severe MR.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".