The Impact of Valve Surgery on 6-Month Mortality in Left-Sided Infective Endocarditis
Bibliographic record
Abstract
BACKGROUND: The role of valve surgery in left-sided infective endocarditis has not been evaluated in randomized controlled trials. We examined the association between valve surgery and all-cause 6-month mortality among patients with left-sided infective endocarditis. METHODS AND RESULTS: A total of 546 consecutive patients with left-sided infective endocarditis were included. To minimize selection bias, propensity score to undergo valve surgery was used to match patients in the surgical and nonsurgical groups. To adjust for survivor bias, we matched the follow-up time so that each patient in the nonsurgical group survived at least as long as the time to surgery in the respective surgically-treated patient. We also used valve surgery as a time-dependent covariate in different Cox models. A total of 129 (23.6%) patients underwent surgery within 30 days of diagnosis. Death occurred in 99 of the 417 patients (23.7%) in the nonsurgical group versus 35 deaths among the 129 patients (27.1%) in the surgical group. Eighteen of 35 (51%) patients in the surgical group died within 7 days of valve surgery. In the subset of 186 cases (93 pairs of surgical versus nonsurgical cases) matched on the logit of their propensity score, diagnosis decade, and follow-up time, no significant association existed between surgery and mortality (adjusted hazard ratio, 1.3; 95% confidence interval, 0.5 to 3.1). With a Cox model that incorporated surgery as a time-dependent covariate, valve surgery was associated with an increase in the 6-month mortality with an adjusted hazard ratio of 1.9 (95% confidence interval, 1.1 to 3.2). Because the proportionality hazard assumption was violated in the time-dependent analysis, we performed a partitioning analysis. After adjustment for early (operative) mortality, surgery was not associated with a survival benefit (adjusted hazard ratio, 0.92; 95% confidence interval, 0.48 to 1.76). CONCLUSIONS: The results of our study suggest that valve surgery in left-sided infective endocarditis is not associated with a survival benefit and could be associated with increased 6-month mortality, even after adjustment for selection and survivor biases as well as confounders. Given the disparity between the results of our study and those of other observational studies, well-designed prospective studies are needed to further evaluate the role of valve surgery in endocarditis management.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".