Comparing block characteristics of mixtures of short/intermediate- and long-acting local anesthetics for peripheral nerve block: a systematic review and meta-analysis
Bibliographic record
Abstract
Results from Randomized Controlled Trials (RCTs) on mixed Local Anesthetics (LA) are conflicting. We conducted a systematic review and meta-analysis on whether using mixed LA leads to faster onset of surgical block. We conducted systemic review and meta-analysis of RCTs. Medline and Embase without language restriction from inception to June 15, 2024, were searched. Included RCTs had to compare mixed LA to long-acting LA in adult surgical patients for onset or duration of nerve blocks. Onset time to surgical block was the primary outcome. The Cochrane Risk of Bias Tool with GRADE methodology was utilized to assess evidence quality. Nineteen trials including 1060 participants met the inclusion criteria. Mixed LA modestly reduced time to surgical block (-8.4 minutes; 95% CI -12.0 to -4.8 minutes; p = 0.0001; I 2 = 0.99), sensory block duration (-226.2 minutes; 95% CI -352.2 to -100.1 minutes; p = 0.002; I 2 = 0.98) and motor block duration (-259.2 minutes; 95% CI -399.5 to -119.0 minutes; p = 0.003; I 2 = 0.98) but not time to analgesic request duration (-130.5 minutes; 95% CI -265.9 to 4.9 minutes; p = 0.057; I 2 = 0.98). GRADE scoring ranged from low to very low. The existing evidence showed mixed LA led to a modest reduction in surgical block latency but also shortened block duration. Future studies should evaluate the role of mixed LA in lower limb blocks and optimal dosing of long-acting LA to balance onset latency and analgesic duration. CRD42024552801.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.046 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".