Anesthetic management of complex spine surgery in adult patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this article is to review the evidence regarding the anesthetic management of blood loss, pain control, and position-related complications of adult patients undergoing complex spine procedures. RECENT FINDINGS: The most recent evidence of the anesthetic management of complex spine surgery was identified with a systematic search and graded. In our review, prophylactic tranexamic acid and optimal prone positioning were shown to be effective blood conservation strategies with minimal risks to the patients. Cell saver was cost-effective in complex surgeries with expected blood loss of greater than 500 ml. As for pain control, most interventions only produced mild analgesic effects, suggesting a multimodal approach is necessary to achieve optimal pain control after spine surgery. Regional techniques and NSAIDs were effective but because of their risks, their usage should be discussed with the surgical team. Further studies are required to assess the effectiveness, cost-effectiveness, and risks associated with combined uses of different analgesic interventions. On the basis of the available evidence, we recommend a combined use of gabapentinoids, ketamine, and opioids to achieve optimal analgesia. Lastly, literature for position-related injuries is heavily relied on case reports and the Anesthesia Closed Claim Study because of their rarity. Therefore, we advocate for a structured team-based approach with checklists to minimize position-related complications. SUMMARY: As the number and complexity of spine procedures are being performed worldwide is increasing, we suggested to bundle the aforementioned effective interventions as part of an ERAS spine protocol to improve the patient outcome of spine surgery.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".