Impact of Choice of Prophylaxis on the Microbiology of Cardiac Implantable Electronic Device Infections: Insights From the Prevention of Arrhythmia Device Infection Trial (PADIT)
Bibliographic record
Abstract
Abstract Background The Prevention of Arrhythmia Device Infection Trial (PADIT) investigated whether intensification of perioperative prophylaxis could prevent cardiac implantable electronic device (CIED) infections. Compared with a single dose of cefazolin, the perioperative administration of cefazolin, vancomycin, bacitracin, and cephalexin did not significantly decrease the risk of infection. Our objective was to compare the microbiology of infections between study arms in PADIT. Methods This was a post hoc analysis. Differences between study arms in the microbiology of infections were assessed at the level of individual patients and at the level of microorganisms using the Fisher exact test. Results Overall, 209 microorganisms were reported from 177 patients. The most common microorganisms were coagulase-negative staphylococci (CoNS; 82/209 [39.2%]) and S. aureus (75/209 [35.9%]). There was a significantly lower proportion of CoNS in the incremental arm compared with the standard arm (30.1% vs 46.6%; P = .04). However, there was no significant difference between study arms in the frequency of recovery of other microorganisms. In terms of antimicrobial susceptibility, 26.5% of microorganisms were resistant to cefazolin. CoNS were more likely to be cefazolin-resistant in the incremental arm (52.2% vs 26.8%, respectively; P = .05). However, there was no difference between study arms in terms of infections in which the main pathogen was sensitive to cefazolin (77.8% vs 64.3%; P = .10) or vancomycin (90.8% vs 90.2%; P = .90). Conclusions Intensification of the prophylaxis led to significant changes in the microbiology of infections, despite the absence of a decrease in the overall risk of infections. These findings provide important insight on the physiopathology of CIED infections. Trial registration NCT01002911.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".