Risk of Infective Endocarditis After Invasive Dental Procedures in Patients With Congenital Heart Disease
Bibliographic record
Abstract
BACKGROUND: Invasive dental procedures (IDPs) may trigger infective endocarditis (IE) in patients with congenital heart disease (CHD). However, data quantifying this risk remain limited. This study aimed to investigate the association between IDPs and the risk of IE in CHD. METHODS: We conducted a nationwide, self-controlled case series study using Taiwan's National Health Insurance Research Database (2009-2019). The overall risk period was defined as 0-4 months after an IDP, further divided into 4 consecutive monthly risk periods. Incidence rate ratios (IRRs) were estimated using conditional Poisson regression. RESULTS: Among 132,123 CHD patients, 633 who experienced hospitalization for IE were analyzed. The adjusted IRR for IE was 2.27 (95% confidence interval [CI] 1.93-2.68) during the overall risk period after an IDP. The risk was highest in the first month post-IDP (IRR 3.03, 95% CI 2.40-3.82), then declined over the second (IRR 1.91, 95% CI 1.45-2.52), third (IRR 1.63, 95% CI 1.21-2.20), and fourth (IRR 1.32, 95% CI 0.95-1.84) months. Elevated first-month IE risk was observed in both severe (IRR 4.01, 95% CI 1.53-10.52) and simple CHD (IRR 2.98, 95% CI 2.35-3.79). Similar risk patterns were observed across all subgroups, irrespective of CHD severity, sex, age, or comorbidities. CONCLUSIONS: This nationwide study provides new evidence of an increased risk of IE after IDPs in patients with CHD, with the risk persisting for up to 3 months. These findings highlight the need for increased clinical awareness and monitoring of IE in CHD patients undergoing IDPs.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".