Incidence, severity and perioperative risk factors for atrial fibrillation following pulmonary resection
Bibliographic record
Abstract
OBJECTIVES: Postoperative atrial fibrillation (PAF) occurs commonly following pulmonary resection. Our aims were to quantify the incidence and severity of PAF using the Thoracic Morbidity & Mortality classification system, and identify risk factors for PAF. METHODS: All consecutive patients undergoing pulmonary resection at a single centre (January 2008 - April 2010) were enrolled. PAF was defined as postoperative, electrocardiographically documented and requiring initiation of pharmacological therapy. Univariate and multivariate analyses of risk factors associated with the development of PAF were conducted. RESULTS: The incidence of PAF was 11.8% (n = 43) of 363 pulmonary resections (open: n = 173; 47.7%; video-assisted: n = 177; 48.8%; converted: n = 13; 3.6%): sublobar (n = 93; 25.6%), lobectomy (n = 237; 65.3%), bilobectomy (n = 7; 1.9%) and pneumonectomy (n = 24; 6.6%). Twenty-eight cases (65.1%) were uncomplicated/transient, and 15 cases (34.9%) were complicated/persistent PAF, defined as lasting for >7 days (40.0%), requiring cardioversion (13.3%), vasopressors (33.3%), in-hospital use of anticoagulants (46.7%) and/or anticoagulants on discharge (26.7%). Patients with PAF had increased mean lengths of hospital stay (10.5 days vs 6.9 days; P = 0.04). Peak onset of PAF occurred 2.5 (standard deviation (SD) ± 1.3) days after pulmonary resection, lasting for 1.8 ± 2.8 (mean, ±SD) days. Multivariate analysis identified (relative risk; 95% confidence interval): age ≥70 years (2.3; 1.1-5.1), history of angioplasty/stents/angina (4.0; 1.4-11.3), thoracotomy (3.6; 1.4-9.3), conversion to open thoracotomy (16.5; 2.2-124.0) and extent of surgery/stage (7.1; 1.0-49.4) as predictors of PAF. CONCLUSIONS: While the majority of PAF is uncomplicated and transient, one-third of cases lead to persistence or major intervention. Age, coronary artery disease and extent of surgery/stage increase the risk of PAF following pulmonary resection. Identifying patients with elevated risk may lead to targeted prophylaxis to reduce the incidence of PAF.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".