Opioid-Free Analgesia for Supratentorial Craniotomies: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Post-craniotomy pain can be severe and is often undermanaged. Opioids can interfere with neurological monitoring and are associated with adverse effects. This systematic review aimed to identify measures of opioid-free analgesia and compare their effectiveness with opioid analgesia for post-craniotomy pain in patients with supratentorial tumors. METHODS: EMBASE, MEDLINE, and Cochrane databases were searched from their inception to February 14, 2017, for randomized controlled trials (RCTs) evaluating opioid versus non-opioid analgesia post-supratentorial craniotomy. Two reviewers independently carried out study selection and data extraction. Risk of bias assessment was performed using the Cochrane Collaboration's tool. Outcomes were pain control (changes to pain scores or use of rescue analgesia) and adverse effects. Considering the number of studies and heterogeneity, a narrative synthesis was done without pooling and results were summarized using tables. Non-opioids were assessed for the potential to be equivalent to opioid-based analgesics for pain relief and adverse effects. RESULTS: Of 467 RCTs, 4 met our inclusion criteria (n = 186 patients). Patients with scalp blocks (2 RCTs) had less post-operative nausea and vomiting (PONV), but scalp block was not superior to morphine for analgesia. Acetaminophen (1 RCT) was less likely to induce PONV but provided inadequate pain relief compared to morphine and sufentanil. Dexmedetomidine (1 RCT) was not superior to remifentanil for analgesia although it delayed time to rescue analgesia. CONCLUSIONS: Limited evidence suggests that scalp blocks and dexmedetomidine have the potential to eliminate the need for opioid analgesia. Multimodal analgesia should be considered as significant opioid-sparing effects have been shown.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".