Should We Add Clonidine to Local Anesthetic for Peripheral Nerve Blockade? A Qualitative Systematic Review of the Literature
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Although clonidine has been shown to prolong analgesia in central neuraxial blocks, its use in peripheral nerve blocks remains controversial. We performed a systematic review of the current literature to determine the benefit of adding clonidine to peripheral nerve blocks. METHODS: A systematic, qualitative review of double-blind randomized controlled trials on the benefit of clonidine as an adjunct to peripheral nerve block was performed. Studies were identified by searching PubMed (www.ncbi.nlm.nih.gov/entrez) and EMBASE (www.embase.com) databases (July 1991 to October 2006) for terms related to clonidine as an adjunct to peripheral nerve blocks. Studies were classified as supportive if the use of clonidine demonstrated reduced pain and total analgesic consumption, or prolonged block duration versus negative if no difference was found. RESULTS: Twenty-seven studies were identified that met the inclusion criteria. Five studies included a systemic control group. The total number of patients reviewed was 1,385. The dose of clonidine varied from 30 to 300 mug. Overall 15 studies supported the use of clonidine as an adjunct to peripheral nerve blocks with 12 studies failing to show a benefit. Based on qualitative analysis, clonidine appeared to prolong analgesia when added to intermediate-acting local anesthetics for axillary and peribulbar blocks. CONCLUSIONS: Clonidine improves duration of analgesia and anesthesia when used as an adjunct to intermediate-acting local anesthetics for some peripheral nerve blocks. Side-effects appear to be limited at doses up to 150 mug. Evidence is lacking for the use of clonidine as an adjunct to local anesthetics for continuous catheter techniques. Further research is required to examine the peripheral analgesic mechanism of clonidine.
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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 | 0.053 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".