Real‐World Use of Prophylactic Antibiotics in Insertable Cardiac Monitor Procedures
Bibliographic record
Abstract
BACKGROUND: The use of prophylactic antibiotics during insertable cardiac monitor (ICM) procedures is a carryover of the common practice used with therapeutic cardiac implantable electronic devices. We sought to characterize the current practice of ICM insertion procedures to evaluate the influence of prophylactic antibiotic administration on the occurrence of infections. METHODS: We characterized insertion procedures and procedure-related infections from an ongoing multicenter registry (Reveal LINQ(TM) Registry). In order to accurately capture infections, only patients enrolled before or the day of insertion who also had a record of whether or not preoperative antibiotics were used were included in this analysis. Infections were defined based on the physician's assessment and reported upon occurrence. Patients were categorized into two analysis cohorts based on prophylactic antibiotic use. RESULTS: We analyzed 375 patients from 14 U.S. centers (age 63.1 ± 15.6 years; male 54.1%). Approximately two-thirds of patients (66.4%) did not receive any preprocedural antibiotics. The overall infection rate was 1.1% (0.3-2.7% confidence interval [CI]) and corresponded to four events. In the group that did not receive preprocedural antibiotics, there were two minor infections (0.8%, [0.1-2.9% CI]), whereas in the group receiving preprocedural antibiotics a serious and a minor infection occurred (1.6%, [0.2-5.6% CI]); this serious infection resulted in an explant. CONCLUSIONS: Current real-world practice shows that ICM insertions are increasingly performed without the use of prophylactic antibiotics, which is associated with a very low infection rate.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".