Economic evaluation of an absorbable antibiotic envelope for prevention of cardiac implantable electronic device infection
Bibliographic record
Abstract
AIMS: Recent evidence suggests that an antibiotic impregnated envelope inserted at time of cardiac implantable electronic device (CIED) implantation may reduce risk of subsequent CIED infection compared with standard of care (SoC). The objective of the current work was to perform a cost-effectiveness analysis comparing an antibiotic impregnated envelope with SoC at time of CIED insertion. METHODS AND RESULTS: Decision analytic models were used to project healthcare costs and benefits of two strategies, an antibiotic impregnated envelope plus SoC (Env+SoC) vs. SoC alone, in a cohort of patients undergoing CIED implantation over a 1-year time horizon. Evidence from published literature informed the model inputs. Probabilistic and deterministic sensitivity analyses were performed. The primary outcome was the incremental cost per infection prevented, assessed from the Canadian healthcare system perspective. Envelope plus SoC was associated with fewer CIED infection (7 CIED infections/1000 patients) at higher total costs ($29 033 000/1000 patients) compared with SoC (11 CIED infections and $27 926 000/1000 patients). The incremental cost per infection prevented over 1 year was $274 416. Use of Env+SoC was cost saving only when baseline CIED infection risk was increased to 6% (vs. base case of 1.2%). CONCLUSIONS: A strategy of Env+SoC was not economically favourable compared with SoC alone, and the opportunity cost of widescale implementation should be considered. Future work is required to develop validated risk stratification tools to identify patients at greatest risk of CIED infection. The value proposition of Env+SoC improves when applying this intervention to patients at greatest infection risk.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".