Reduced incidence of CIED infections with peri- and post-operative antibiotic use in CRT-P/D and ICD procedures
Bibliographic record
Abstract
Higher cardiac implantable electronic device (CIED) infection incidence has been observed with cardiac resynchronization therapy pacemaker/defibrillator (CRT-P/D) and implantable cardioverter defibrillator (ICD) devices compared to traditional pacemakers with a 1.2% rate reported at 1 year. CIED infection management has high morbidity/mortality. A previous study from this institution demonstrated significantly reduced CIED infection rate when peri/post-operative antibiotics were given for traditional pacemaker procedures. The present study examines CIED infection incidence following peri/post-operative antibiotics during CRT-P/D and ICD procedures. All patients who underwent CRT-P/D and ICD procedures from 1996 to 2015 received IV cephalexin/clindamycin pre- and 8-hours post-procedure followed by 5 days of oral therapy. There were 427 procedures (CRT-P = 146 (34.2%); CRT-D = 142 (33.3%); ICD = 139 (32.6%)). Mean age at time of procedure was 61.6 years. Mean follow-up duration was 4.26 years. CIED infection occurred in 6 patients (ICD = 4, CRT-P = 1, CRT-D = 1), amounting to a rate of 4.96/1000 device-years in total. Times to CIED infection from procedure were: 1.7, 3.5, 6.7, 7.3, 7.9 and 9.2 years. Five out of 6 infections occurred in patients with repeat procedures. This study demonstrates that administration of peri- followed by post-operative antibiotics during CRT-P/D and ICD procedures is associated with a very low rate of CIED infection. This rate of 4.96 infections per 1000 device-years compares favorably to contemporary rates of 8.9 infections per 1000 device-years. Most CIED infections occur late and well-beyond the 1-year follow-up of the Prevention of Arrhythmia Device Infection Trial, the largest trial on this question. This approach should be considered pending a definitive trial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".