Dexamethasone Prolongs Local Analgesia after Subcutaneous Infiltration of Bupivacaine Microcapsules in Human Volunteers
Bibliographic record
Abstract
BACKGROUND: The addition of small amounts of dexamethasone to extended-release formulations of bupivacaine in microcapsules has been found to prolong local analgesia in experimental studies, but no clinical data are available. METHODS: In a double-blinded study, 12 healthy male volunteers were randomized to receive simultaneous subcutaneous injections of bupivacaine microcapsules with dexamethasone and bupivacaine microcapsules without dexamethasone in each calf. Local analgesia was assessed with a validated human pain model; main parameters evaluated were thermal, mechanical, and pain detection thresholds and suprathreshold responses to heat and mechanical stimulation. Measurements were performed every 2 h for the first 8 h and daily for the week after injection. Primary endpoints were evaluation of maximal analgesic effect, time of onset, and duration of analgesia. Summary measures (area under curve [AUC]) were considered best estimate of analgesia. Safety evaluations were performed daily for the first week and at 2 weeks, 6 weeks, and 6 months after injection. RESULTS: The addition of dexamethasone significantly prolonged local analgesia of bupivacaine microcapsules without influence on maximal analgesic effect. AUC in all thermal measurements and the sensory mechanical threshold were significantly increased between 1-7 days after drug injection in the group given dexamethasone compared with the group not given dexamethasone. No serious side effects were observed. CONCLUSIONS: Addition of small amounts of dexamethasone to bupivacaine incorporated in microcapsules prolonged local analgesia compared with microcapsules with plain bupivacaine after subcutaneous administration in humans.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".