Infectious consequences of hematoma from cardiac implantable electronic device procedures and the role of the antibiotic envelope: A WRAP-IT trial analysis
Bibliographic record
Abstract
BACKGROUND: Hematoma is a complication of cardiac implantable electronic device (CIED) procedures and may lead to device infection. The TYRX antibacterial envelope reduced major CIED infection by 40% in the randomized WRAP-IT (World-wide Randomized Antibiotic Envelope Infection Prevention Trial) study, but its effectiveness in the presence of hematoma is not well understood. OBJECTIVE: The purpose of this study was to evaluate the incidence and infectious consequences of hematoma and the association between envelope use, hematomas, and major CIED infection among WRAP-IT patients. METHODS: All 6800 study patients were included in this analysis (control 3429; envelope 3371). Hematomas occurring within 30 days postprocedure (acute) were characterized and grouped by study treatment and evaluated for subsequent infection risk. Data were analyzed using Cox proportional hazard regression modeling. RESULTS: Acute hematoma incidence was 2.2% at 30 days, with no significant difference between treatment groups (envelope vs control hazard ratio [HR] 1.15; 95% confidence interval [CI] 0.84-1.58; P = .39). Through all follow-up, the risk of major infection was significantly higher among control patients with hematoma vs those without (13.1% vs 1.6%; HR 11.3; 95% CI 5.5-23.2; P <.001). The risk of major infection was significantly lower in the envelope vs control patients with hematoma (2.5% vs 13.1%; HR 0.18; 95% CI 0.04-0.85; P = .03). CONCLUSION: The risk of hematoma was 2.2% among WRAP-IT patients. Among control patients, hematoma carried a >11-fold risk of developing a major CIED infection. This risk was significantly mitigated with antibacterial envelope use, with an 82% reduction in major CIED infection among envelope patients who developed hematoma compared to control.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".