Safety Profile of Liver FibroScan in Patients with Cardiac Pacemakers or Implantable Cardioverter-Defibrillators
Bibliographic record
Abstract
Background. Emerging evidence suggests that nonalcoholic fatty liver disease (NAFLD) is associated with coronary artery diseases and arrhythmias. The FibroScan (Echosens, France), a widely available, noninvasive device, is able to detect liver fibrosis and steatosis within this patient population. However, the FibroScan is currently contraindicated in patients with cardiac pacemakers (PM) or implantable cardioverter-defibrillators (ICD).Objective. To determine the safety profile of FibroScan testing in patients with PM or ICD.Methods. Consecutive outpatients undergoing routine device interrogations at a tertiary level teaching hospital underwent simultaneous liver stiffness measurements. PM or ICD performance data, device types, patient demographics, medical history, and previous laboratory and conventional liver imaging results were collected.Results. Analysis of 107 subjects with 33 different types of implanted cardiac devices, from 5 different companies (Medtronic, Sorin, ELA Medical, Boston Scientific, and St. Jude), did not demonstrate any adverse events as defined by abnormal device sensing/pacing or ICD firing. This population included high risk subjects undergoing active pacing ( n=53 ) and with right pectoral PM placement ( n=1 ). None of the subjects had any clinical signs of decompensated congestive heart failure or cirrhosis during the exam.Conclusion. TE with FibroScan can be safely performed in patients with PM or ICD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".