Predictors of Fracture Risk of a Small Caliber Implantable Cardioverter Defibrillator Lead
Bibliographic record
Abstract
INTRODUCTION: The Sprint Fidelis 6949 implantable cardioverter defibrillator (ICD; Medtronic Inc., Minneapolis, MN, USA) lead has a high rate of fracture. Identification of predictors of subsequent fracture is useful in decision making about lead replacement and for future lead design. We sought to determine if there are clinical, procedural, or radiological features associated with a greater risk of subsequent lead fracture. METHODS: Patients with Sprint Fidelis 6949 lead fractures (Fracture group) were identified from our institutional database. Each patient in the Fracture group was matched to two controls, immediately preceeding and succeeding Sprint Fidelis 6949 implant. Clinical and procedural characteristics were compared. Chest radiographs performed 2 weeks after ICD implant were reviewed by an observer blinded to outcomes. The following features were assessed: ICD tip location, lead slack, kinking of the lead body (> or =90 degrees ), and presence of lead "crimping" within the anchoring sleeve. RESULTS: Twenty-six patients with Sprint Fidelis 6949 lead fractures were identified and were matched to 52 control patients. On univariate analysis, a higher left ventricular ejection fraction (LVEF), prior ipsilateral device implant, history of prior ICD lead fracture, and noncephalic venous access were associated with risk of lead fracture. On multivariate analysis, a higher LVEF was the only independent predictor of lead fracture (P = 0.006). Radiological features were similar between the two groups. CONCLUSIONS: In this study, a higher LVEF was associated with a greater risk of lead fracture in patients with Sprint Fidelis 6949 ICD leads. Radiographic features did not predict subsequent risk of lead fracture in our population. (PACE 2010; 437-443).
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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) | 0.001 | 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 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".