Postoperative Continuous Paravertebral Anesthetic Infusion for Pain Control in Posterior Cervical Spine Surgery
Bibliographic record
Abstract
INTRODUCTION: Patients who undergo posterior cervical spinal fusion procedures frequently experience significant postoperative pain. Use of a local anesthetic continuous infusion pump after surgery may improve these outcome variables. METHODS: After posterior cervical spine fusion procedures, 25 consecutive patients received continuous infusion of 0.5% bupivacaine into the subfascial aspects of the wound via an elastomeric pump. Data were collected prospectively by third party assessment using standard nursing protocols. This included numeric pain scores and opiate use over the first 4 postoperative days (PODs), length of hospitalization, and complications. In a retrospective analysis, we compared each study patient to a control patient who did not receive the continuous infusion of bupivacaine. Demographic variables and surgical procedure were similar among matched cases. RESULTS: Patients receiving continuous local anesthetic infusion used significantly less narcotics (P < .05) during the first 4 PODs: 24.4% on day 1, 34.1% on day 2, 53.5% on day 3, and 58.1% on day 4. A lower average pain score was observed among study patients on each POD (P < .05): 31.5% less on day 1, 13.0% on day 2, 24.0% on day 3, and 35.7% on day 4. Patients with the infusion device were discharged home earlier (POD 4.9 versus 6.7; P = .024) and demonstrated improvement in time to ambulation, first bowel movement, and discontinuation of the patient-controlled analgesia machine. No complications were associated with the device. CONCLUSION: Patients with the local anesthetic continuous infusion device required less narcotics and reported lower pain scores than control patients on each of the first 4 PODs. These results suggest that continuous infusion of local anesthetic into the paravertebral tissue during the immediate postoperative period is a safe and effective technique that achieves lower pain scores and narcotic use and improves multiple postoperative outcome variables.
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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 | 0.001 |
| 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 | 0.000 |
| 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".