Are there increased periprocedural complications with the MRI-conditional Medtronic Revo SureScan Pacing System?
Bibliographic record
Abstract
BACKGROUND: The use of magnetic resonance imaging (MRI)-conditional permanent pacemakers has increased significantly. In this meta-analysis, we examine the safety of MRI-conditional pacing systems in comparison with conventional systems. METHODS: An electronic search was performed using major databases, including studies that compared the outcomes of interest between patients receiving MRI-conditional pacemakers (MRI group) versus conventional pacemakers (control group). RESULTS: Six studies (5 retrospective and 1 prospective non-randomised) involving 2,118 adult patients were identified. The MRI-conditional pacemakers, deployed in 969 patients, were all from a single manufacturer (Medtronic Pacing System with 5086 leads). The rate of pacemaker lead dislodgement (atrial and ventricular) was significantly higher in the MRI group (3% vs. 1%, OR 2.47 (95% CI 1.26; 4.83), p = 0.008). The MRI group had a significantly higher rate of pericardial complications (2% vs. 1%, OR 4.23 (95% CI 1.18; 15.10), p = 0.03) and a numerically higher overall complication rate in comparison with the conventional group (6% vs. 3%, OR 2.02 (95% CI 0.88; 4.66), p = 0.10) but this was not statistically significant. CONCLUSIONS: In this meta-analysis, the rates of pacemaker lead dislodgement and pericardial complications were significantly higher with the Medtronic MRI-conditional pacing system.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.018 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".