Perivalvular Extension of Infective Endocarditis After Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: Infective endocarditis (IE) following transcatheter aortic valve replacement (TAVR) has been associated with a dismal prognosis. However, scarce data exist on IE perivalvular extension (PEE) in such patients. METHODS: This multicenter study included 579 patients who had the diagnosis of definite IE at a median of 171 (53-421) days following TAVR. PEE was defined as the presence of an intracardiac abscess, pseudoaneurysm, or fistula. RESULTS: A total of 105 patients (18.1%) were diagnosed with PEE (perivalvular abscess, pseudoaneurysm, fistula, or a combination in 87, 7, 7, and 4 patients, respectively). A history of chronic kidney disease (adjusted odds ratio [ORadj], 2.08; 95% confidence interval [CI]: 1.27-3.41; P = .003) and IE secondary to coagulase-negative staphylococci (ORadj, 2.71; 95% CI: 1.57-4.69; P < .001) were associated with an increased risk of PEE. Surgery was performed at index IE episode in 34 patients (32.4%) with PEE (vs 15.2% in patients without PEE, P < .001). In-hospital and 2-year mortality rates among PEE-IE patients were 36.5% and 69.4%, respectively. Factors independently associated with an increased mortality were the occurrence of other complications (stroke post-TAVR, acute renal failure, septic shock) and the lack of surgery at index IE hospitalization (padj < 0.05 for all). CONCLUSIONS: PEE occurred in about one-fifth of IE post-TAVR patients, with the presence of coagulase-negative staphylococci and chronic kidney disease determining an increased risk. Patients with PEE-IE exhibited high early and late mortality rates, and surgery during IE hospitalization seemed to be associated with better outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".