Primary prevention of post-pericardiotomy syndrome using corticosteroids: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Post-pericardiotomy syndrome is a well-recognized inflammatory phenomenon that commonly occurs in patients following cardiac surgery. Due to the increased morbidity and resource utilization associated with this condition, research has recently focused on ways of preventing its prevention this condition; primarily using colchicine, NSAIDs and corticosteroids. Areas covered: This systematic review summarizes the three clinical studies that have used corticosteroids for PPS primary prevention in the perioperative period. Due to the heterogeneity amongst these three studies in terms of population (both pediatric and adult patients), surgical procedure, administration regimen and results (only 1/3 studies reporting a positive effect), the effectiveness of corticosteroids remains unproven. Expert commentary: Corticosteroids have shown to be useful in the treatment of PPS but have thus far have shown mixed results as a primary prevention method. Research on patients taking corticosteroids pre-operatively have shown a significant reduction in the risk of developing PPS. Further research is required to determine if corticosteroids are helpful in preventing PPS in patient undergoing cardiac surgery, before any recommendations regarding their use in cardiovascular surgery can be made.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".