Subcutaneous Lidocaine for Cancer-Related Pain
Bibliographic record
Abstract
Background: Intravenous lidocaine infusions have been shown to be effective for cancer related pain, but access is restricted to acute care settings. If able to be shown to be safe and effective, the subcutaneous route could expand access to residential hospices or patients' homes. Objectives: This randomized, double-blind, placebo controlled, 2 × 2 crossover trial evaluated the effectiveness, safety, toxicity, and impact on quality of life of a limited duration subcutaneous lidocaine infusion (SCLI) for chronic cancer pain. Methods: Patients with the life expectancy of three months or more, who were experiencing cancer-related pain with a worst severity of at least 4 on a 0–10 scale despite a trial of at least one opioid and appropriate adjuvant analgesic, received two subcutaneous infusions at least a week apart; lidocaine 10 mg/kg over 5.5 hours and saline placebo. The primary outcome was either a reduction in worst pain intensity of two points out of 10 or a reduction in 24 hours opioid dose of at least 30% without worsening of pain scores, in seven days. Results: The SCLI was only effective for two subjects. One of these subjects experienced a drop in worst pain score and the other experienced a reduction in opioid dose. Conclusions: A weight-based subcutaneous infusion of lidocaine does not achieve sufficiently predictable blood levels for determining lidocaine responsiveness. This study does not allow any conclusion to be drawn on whether or not lidocaine would have been more effective had it been titrated to higher blood levels.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".