Regional analgesia for cardiac surgery
Bibliographic record
Abstract
PURPOSE OF REVIEW: Regional anesthesia is gaining attention as a valuable component of multimodal, opioid-sparing analgesia in cardiac surgery, where improving the patient's quality of recovery while minimizing the harms of opioid administration are key points of emphasis in perioperative care. This review serves as an outline of recent advancements in a variety of applications of regional analgesia for cardiac surgery. RECENT FINDINGS: Growing interest in regional analgesia, particularly the use of newer "chest wall blocks", has led to accumulating evidence for the efficacy of multiple regional techniques in cardiac surgery. These include a variety of technical approaches, with results consistently demonstrating optimized pain control and reduced opioid requirements. Regional and pain management experts have worked to derive consensus around nerve block nomenclature, which will be foundational to establish best practice, design and report future research consistently, improve medical education, and generally advance our knowledge in this vital area of perioperative patient care. SUMMARY: The field of regional analgesia for cardiac surgery has matured over the last several years. A variety of regional techniques have been described and shown to be efficacious as part of the multimodal, opioid-sparing approach to pain management in the cardiac surgical setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".