The use of minimal fluoroscopy for cardiac electrophysiology procedures: A meta‐analysis and review of the literature
Bibliographic record
Abstract
BACKGROUND: Conventional catheter ablation involves prolonged exposure to ionizing radiation, potentially leading to detrimental health effects. Minimal fluoroscopy (MF) represents a safer alternative, which should be explored. Data on the safety and efficacy of this technique are limited. HYPOTHESIS: Our hypothesis is that MF is of equal efficacy and safety to conventional catheter ablation with the use of fluoroscopy by performing a meta-analysis of both randomized controlled trials (RCTs) and real-world registry studies. METHODS: Pubmed and Embase were searched from their inception to July 2020 for RCTs, cohort and observational studies that assessed the outcomes of catheter ablation using a MF technique versus the conventional approach. RESULTS: Fifteen studies involving 3795 patients were included in this meta-analysis. There was a significant reduction in fluoroscopy and procedural time with no difference in acute success (odds ratio [OR]:0.74, 95% CI: 0.50-1.10, p = .14), long-term success (OR:0.92, 95% CI: 0.65-1.31, p = .38), arrhythmia recurrence (OR:1.24, 95% CI: 0.75-2.06, p = .97) or rate of complications. (OR:0.83, 95% CI: 0.46-1.48, p = .65). Additionally sub-group analysis for those undergoing catheter ablation for atrial fibrillation (AF) did not demonstrate a difference in success or complication rates (OR:0.86, 95% CI: 0.30-2.42, p = .77). Multivariate meta-regression did not identify the presence of moderator variables. CONCLUSION: This updated meta-analysis demonstrated an overall reduction in procedural and fluoroscopy time for those undergoing a minimal fluoroscopic approach. There was no significant difference in either acute or chronic success rates or complications between a MF approach and conventional approach for the management of all arrhythmias including those undergoing catheter ablation for AF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".