Posterior left pericardiotomy: what is the advantage in cardiac surgery?
Bibliographic record
Abstract
OBJECTIVES: Postoperative atrial fibrillation (POAF) is the most common complication following cardiac surgery and is associated with prolonged in-hospital stay and increased costs, morbidity (including stroke and heart failure) and mortality. Posterior pericardiotomy (PP) is a surgical intervention aimed at draining the pericardium into the left pleural cavity to reduce POAF occurrence. This review summarizes the current evidence on the use of PP and highlights future perspectives for clinical research. METHODS: The present work is a narrative review, a systematic literature search was therefore not performed. After collegial discussion, the most relevant papers as per the authors' opinion were selected and formed the basis of the present review. RESULTS: Several studies support the hypothesis that PP decreases the incidence of POAF, pericardial effusion and cardiac tamponade after cardiac surgery. Although an increased incidence of pleural effusion has been reported after PP, this finding does not translate into increased pulmonary complications. Whether the systematic use of PP during cardiac surgery improves long-term outcomes is unclear. CONCLUSIONS: PP is a simple and safe technique that holds the potential to positively impact cardiac surgical patients' postoperative course. The results of upcoming, multicentre trials will help shed definitive light on this topic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.019 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".