Intravenous adenosine alleviates neuropathic pain: a double blind placebo controlled crossover trial using an enriched enrolment design
Bibliographic record
Abstract
Adenosine analogs produce analgesic actions in nociceptive paradigms and alleviate manifestations of neuropathic pain in nerve injury models in rodents. In humans, previous work indicates an analgesic effect for adenosine administered intravenously in postoperative and neuropathic pain. In this double blind placebo controlled crossover trial, we used an enriched enrolment design to determine the effects of intravenous adenosine (50 microg/kg/min over 60min) on neuropathic pain. In Phase 1 of the trial, adenosine was administered in an open label manner, while in Phase 2 adenosine was administered in a double blind placebo controlled manner to 23 adenosine responders who had experienced a 30% or greater response in the open trial. Outcome measures included the McGill pain questionnaire (MPQ), which generates a pain rating index (PRI), and contains a visual analog scale (VAS) of pain intensity, the neuropathy pain scale (NPS), and a VAS for pain relief. Subjects also graded the degree of allodynia and hyperalgesia using a VAS. Adenosine led to a significant reduction in spontaneous pain according to the MPQ-PRI, the MPQ-VAS and the VAS for pain relief. The NPS showed a pattern similar to the MPQ-PRI, with statistically significant reductions in scales 1 (intensity), 3 (hot), 6 (sensitive), 7 (itchy) and 9 (unpleasant). Adenosine also led to a significant reduction in pinprick hyperalgesia, but not in allodynia. Three patients from Phase 1 of the trial experienced long term resolution of their pain following intravenous adenosine (5,16,25 months). The results of this study support previous reports that indicate intravenous adenosine alleviates neuropathic pain and hyperalgesia.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".