Association of the Timing and Extent of Cardiac Implantable Electronic Device Infections With Mortality
Bibliographic record
Abstract
Importance: Cardiac implantable electronic device (CIED) infection is a potentially devastating complication with an estimated 12-month mortality of 15% to 30%. The association of the extent (localized or systemic) and timing of infection with all-cause mortality has not been established. Objective: To evaluate the association of the extent and timing of CIED infection with all-cause mortality. Design, Setting, and Participants: This prospective observational cohort study was conducted between December 1, 2012, and September 30, 2016, in 28 centers across Canada and the Netherlands. The study included 19 559 patients undergoing CIED procedures, 177 of whom developed an infection. Data were analyzed from April 5, 2021, to January 14, 2023. Exposures: Prospectively identified CIED infections. Main Outcomes and Measures: Time-dependent analysis of the timing (early [≤3 months] or delayed [3-12 months]) and extent (localized or systemic) of infection was performed to determine the risk of all-cause mortality associated with CIED infections. Results: Of 19 559 patients undergoing CIED procedures, 177 developed a CIED infection. The mean (SD) age was 68.7 (12.7) years, and 132 patients were male (74.6%). The cumulative incidence of infection was 0.6%, 0.7%, and 0.9% within 3, 6, and 12 months, respectively. Infection rates were highest in the first 3 months (0.21% per month), reducing significantly thereafter. Compared with patients who did not develop CIED infection, those with early localized infections were not at higher risk for all-cause mortality (no deaths at 30 days [0 of 74 patients]: adjusted hazard ratio [aHR], 0.64 [95% CI, 0.20-1.98]; P = .43). However, patients with early systemic and delayed localized infections had an approximately 3-fold increase in mortality (8.9% 30-day mortality [4 of 45 patients]: aHR, 2.88 [95% CI, 1.48-5.61]; P = .002; 8.8% 30-day mortality [3 of 34 patients]: aHR, 3.57 [95% CI, 1.33-9.57]; P = .01), increasing to a 9.3-fold risk of death for those with delayed systemic infections (21.7% 30-day mortality [5 of 23 patients]: aHR, 9.30 [95% CI, 3.82-22.65]; P < .001). Conclusions and Relevance: Findings suggest that CIED infections are most common within 3 months after the procedure. Early systemic infections and delayed localized infections are associated with increased mortality, with the highest risk for patients with delayed systemic infections. Early detection and treatment of CIED infections may be important in reducing mortality associated with this complication.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".