Lead Integrity Alert Is Useful for Assessment of Performance of Biotronik Linox Leads
Bibliographic record
Abstract
INTRODUCTION: Medtronic's Lead Integrity Alert (LIA) software algorithm is useful for detecting abnormal parameters across various ICD-lead families. However, its utility in the assessment of the Biotronik Linox™ family of high-voltage (HV) leads is unknown. METHODS: We conducted a retrospective cohort study to assess the performance of the LIA algorithm to detect abnormalities and lead failure in Linox ICD-leads. All LIA-enabled Medtronic devices connected to an active Linox lead were included. The alerts were adjudicated by 2 blinded electrophysiologists and correlated with clinical data. RESULTS: Between 2008 and 2012, data from 208 patients with 564 patient-years of follow-up were available for analysis. The median follow-up duration was 32 (IQR 21-41 months). Twenty-one LIA triggers were noted in 20 different patients. The median delay until a positive LIA was 32 months (IQR 21-41 months) postimplant with a 5-year lead survival free from LIA of 76%. Ninety-five percent (19/20) LIA alerts were true lead failures. The most common LIA triggers were short V-V intervals (85%) and nonsustained ventricular tachycardia (85%). Abrupt changes of the ICD-lead impedance occurred in 5/20 triggers. Inappropriate ICD-shocks were strongly associated with a positive LIA (30% vs. 7.4%; P = 0.006). Of the explanted Linox leads 53% had visible abnormalities. The sensitivity, specificity, and positive predictive value for lead failure in the presence of a LIA trigger were 87%, 99.5%, and 95.2%, respectively. CONCLUSIONS: A positive LIA trigger in Biotronik Linox ICD-leads is highly predictive of lead failure. LIA is useful in ongoing surveillance of lead performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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".