Device‐Related Infection Among Patients With Pacemakers and Implantable Defibrillators: Incidence, Risk Factors, and Consequences
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Device-related infection is a major limitation of device therapy for cardiac arrhythmia. METHODS: The authors analyzed the incidence and risk factors for cardiac device infection (CDI) among consecutive patients implanted with pacemaker (PM) or implantable cardioverter defibrillator (ICD) (including cardiac resynchronization therapy devices) at a tertiary health center in Hamilton, Ontario, Canada. Most patients with device-related infections were identified by an internal infection control system that reports any positive wound and blood cultures following surgery, between 2005 and the present. A retrospective review of patient records was also performed for all patients who received an ICD or PM between July 1, 2003 and March 20, 2007. RESULTS: A total of 24 infections were identified among 2,417 patients having device surgery (1%). Fifteen of these infections (60%) were diagnosed within 90 days of the last surgical procedure. Univariate analysis showed that patients presenting with CDI were more likely to have had a device replacement, rather than a new implant, had more complex devices (dual/triple chamber vs single), and were more likely to have had a prior lead dislodgement. Multivariate analysis found device replacement (P = 0.02) and cardiac resynchronization therapy (CRT)/dual-chamber devices (P = 0.048) to be independent predictors of infection. One patient developed septic pulmonary emboli after having laser-assisted lead extraction. No patient died and 22 patients received a new device. CONCLUSION: CDI occurs in about 1% of cases in high volume facilities. Pulse generator replacement surgery and dual- or triple-chamber device implantation were associated with a significantly increased risk of infection.
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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) | 0.001 | 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 it