Risk of complications in patients undergoing pulmonary vein antrum isolation: a single centre experience
Bibliographic record
Abstract
Abstract Background Pulmonary vein antrum isolation (PVAI) is the gold standard approach to treat symptomatic atrial fibrillation (AF) refractory to medical therapy. While PVAI may result in a number of potential complications, there is a growing body of literature supporting safety of same day discharge post-PVAI. Purpose To retrospectively evaluate the incidence of post-procedure acute adverse events (AE), and elucidate factors associated with increased risk of such complications in patients undergoing PVAI. Methods Patients underwent PVAI between 2004-2021 at a tertiary care centre, and were followed-up at 3, 6 and 12 months post-PVAI. All procedures were performed utilizing intra-cardiac echocardiography. Baseline characteristics of patients who experienced acute AE were compared with those in patients who did not. Univariate and multivariate logistic regression models adjusted for age, sex, type of AF, left atrial size, and comorbidities were employed to evaluate risk factors for acute AE. Results 2829 patients (mean age: 61.5±10.4 years, 33.7% female, 64.1% paroxysmal AF) were included in this study. Overall incidence of acute AE was 92 (3.3%), which included: 60 (2.1%) patients with access site hematoma, 20 (0.7%) patients with hematoma requiring treatment, and 12 (0.4%) patients with cardiac tamponade. Other complications included: 5 (0.18%) strokes or transient ischemic attacks (TIA), 3 (0.10%) esophageal fistulas, and 1 (0.03%) phrenic nerve injury. Females (4.2% vs 2%, P=0.001), patients older than 75 years (3.3% vs 2.7%, P=0.8), non-paroxysmal AF (3.4% vs 2.4%, P=0.1), body mass index ≥ 35 kg/m2 (3.6% vs 2.7%, p=0.04), those with an implanted device (6.7% vs 2.3%, p=0.004), and sinus node dysfunction (SND) (6.6% vs 2.5%, p=0.001) had a greater rate of acute AEs. Patients with comorbidities, including hypertension (3.4% vs 2%, P=0.04), Type 2 diabetes ( 3.2% vs 2.7%, p=0.7), congestive heart failure (5.6% vs 2.5%, P=0.008), and coronary artery disease (3.9% vs 2.6%, p=0.1) also manifested higher rate of acute AE. In the multivariate logistic regression model, female sex (OR= 2.5 [1.4, 4.4]), CHF (OR= 2.6 [1.3, 4.9]) and SND (OR=2.6 [1.1, 5.5] were associated with increased AE risk when adjusted for age, AF type, and other comorbidities. Conclusion In the multivariate model, female sex, a history of congestive heart failure, and SND were independently associated with a greater risk of AE following PVAI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".