Regional Anesthesia With Paravertebral Blockade Is Associated With Improved Outcomes in Patients Undergoing Minithoracotomy Cardiac Surgery
Bibliographic record
Abstract
Objective: Severe postoperative pain has been shown to affect many patients following minimally invasive cardiac surgeries (MICS). Multimodal pain management with regional anesthesia, particularly by delivery of local anesthetics using a paravertebral catheter (PVC), has been shown to reduce pain in operations involving thoracotomy incisions. However, few studies have reported high-quality safety and efficacy outcomes of PVCs following MICS. Methods: Patients who underwent MICS at Vancouver General Hospital between 2016 and 2019 ( N = 123) were reviewed for perioperative opioid-narcotic use. Primary outcomes were postoperative opioid use and hospital length of stay (LOS). Statistical analyses were performed using univariate and multivariable regression models to determine independent risk factors. Results: A total of 54 patients received routine systemic analgesia (control), 53 patients received a paravertebral catheter (PVC), and 16 patients received another mode of regional analgesia (non-PVC). The mean hospital LOS was significantly different in patients in the PVC group at 5.8 ± 2.0 days versus 8.3 ± 7.1 days in the control and 6.6 ± 2.3 days in the non-PVC group ( P = 0.033). The percentage of patients who did not require postoperative oxycodone was significantly higher in the PVC group (48.1%), compared with the control (24.5%) and non-PVC (37.5%; P = 0.043) groups. Conclusions: The administration of regional anesthesia using PVCs was associated with reduced need for opioids and a shorter LOS. The reduction in postoperative opioids may reduce the risk of potential opioid dependency in this population. Future studies should involve randomized controlled trials with systematic evaluation of pain scores to verify current study results.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".