Regional analgesia for minimally invasive cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Minimally invasive cardiac surgery (MICS) has expanded during the recent years due to interest in improved patient satisfaction and decreased stay in the hospital. To assist in these interests, postoperative pain control is aimed at decreasing opioid usage but maintaining adequate pain control. Regional anesthesia has the ability to provide these goals. This review article will describe different regional anesthesia techniques and discuss the evidence of their use in MICS. METHODS: A literature search was conducted in MEDLINE (PubMed) and EMBASE with keywords and narrowed to publications between 1998 and 2018. The results are reviewed, analyzed, and discussed in this paper. RESULTS: Thoracic epidurals provide improved pain control and decreased stay in the intensive care unit. Thoracic paravertebral blocks are as effective as thoracic epidurals for postoperative pain control. Serratus anterior plane block provides adequate pain control but does not control pain as well as paravertebral blocks. Intrapleural blocks provide sufficient pain control and can be placed by the surgeon. Pectoral fascial blocks, intercostal blocks, and erector spinae plane blocks described in case reports seem to be viable options for postoperative pain control. CONCLUSIONS: As cardiac surgery moves toward smaller incisions and MICS with the goal of enhanced recovery, multimodal analgesic techniques should be explored for postoperative pain control. The regional techniques discussed in this article show a trend toward improved pain control and decreased stay in the intensive care unit.
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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 | 0.003 | 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) | 0.005 | 0.001 |
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".