Implantable Cardioverter-Defibrillators in Tetralogy of Fallot
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Tetralogy of Fallot is the most common form of congenital heart disease in implantable cardioverter-defibrillator (ICD) recipients, yet little is known about the value of ICDs in this patient population. METHODS AND RESULTS: We conducted a multicenter cohort study in high-risk patients with Tetralogy of Fallot to determine actuarial rates of ICD discharges, identify risk factors, and characterize ICD-related complications. A total of 121 patients (median age 33.3 years; 59.5% male) were enrolled from 11 sites and followed up for a median of 3.7 years. ICDs were implanted for primary prevention in 68 patients (56.2%) and for secondary prevention in 53 (43.8%), defined by clinical sustained ventricular tachyarrhythmia or resuscitated sudden death. Overall, 37 patients (30.6%) received at least 1 appropriate and effective ICD discharge, with a median ventricular tachyarrhythmia rate of 213 bpm. Annual actuarial rates of appropriate ICD shocks were 7.7% and 9.8% in primary and secondary prevention, respectively (P=0.11). A higher left ventricular end-diastolic pressure (hazard ratio 1.3 per mm Hg, P=0.004) and nonsustained ventricular tachycardia (hazard ratio 3.7, P=0.023) independently predicted appropriate ICD shocks in primary prevention. Inappropriate shocks occurred in 5.8% of patients yearly. Additionally, 36 patients (29.8%) experienced complications, of which 6 (5.0%) were acute, 25 (20.7%) were late lead-related, and 7 (5.8%) were late generator-related complications. Nine patients died during follow-up, which corresponds to an actuarial annual mortality rate of 2.2%, which did not differ between the primary and secondary prevention groups. CONCLUSIONS: Patients with tetralogy of Fallot and ICDs for primary and secondary prevention experience high rates of appropriate and effective shocks; however, inappropriate shocks and late lead-related complications are common.
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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) | 0.000 | 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 it