Role of regional anesthesia and analgesia in enhanced recovery after colorectal surgery: a systematic review of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Effective analgesia is an important element of enhanced recovery after surgery (ERAS), but the clinical impact of regional anesthesia and analgesia for colorectal surgery remains unclear. OBJECTIVE: We aimed to determine the impact of regional anesthesia following colorectal surgery in the setting of ERAS. EVIDENCE REVIEW: We performed a systematic review of nine databases up to June 2020, seeking randomized controlled trials comparing regional anesthesia versus control in an ERAS pathway for colorectal surgery. We analyzed the studies with successful ERAS implementation, defined as ERAS protocols with a hospital length of stay of ≤5 days. Data were qualitatively synthesized. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. FINDINGS: Of the 29 studies reporting ERAS pathways, only 13 comprising 1170 patients were included, with modest methodological quality and poor reporting of adherence to ERAS pathways. Epidural analgesia had limited evidence of outcome benefits in open surgery, while spinal analgesia with intrathecal opioids may potentially be associated with improved outcomes with no impact on length of stay in laparoscopic surgery, though dosing must be further investigated. There was limited evidence for fascial plane blocks or other regional anesthetic techniques. CONCLUSIONS: Although there was variable methodological quality and reporting of ERAS, we found little evidence demonstrating the clinical benefits of regional anesthetic techniques in the setting of successful ERAS implementation, and future studies must report adherence to ERAS in order for their interventions to be generalizable to modern clinical practice. PROSPERO REGISTRATION NUMBER: CRD42020161200.
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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 | 0.035 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".