Comparison of Retrolaminar Paravertebral Infiltration of a Non-Steroid Mixture with Conventional Epidural Steroid Infiltration in Patients Suffering from Chronic Radicular Pain- A Retrospective Study
Bibliographic record
Abstract
Abstract Introduction:Chronic radicular pain is often treated by epidural steroid infiltration (ESI). In 2014, Food and Drug Administration (FDA) issued a letter warning that ESI may result in rare but serious adverse events, including “loss of vision, stroke, paralysis, and death”. In this retrospective study, we compare retrolaminar paravertebral infiltration (PVI) of a non-steroid-mixture with ESI. Method: We identified 31 patients registered in the Quebec Pain Registry suffering from chronic lumbar or cervical radicular pain referred to the Centre Hospitalier de l’Université de Montréal (CHUM) pain clinic between 2009 to 2014. These patients received ultrasound-guided retrolaminar PVI with a mixture of morphine 1 mg, ketamine 10 mg, neostigmine 0.5 mg, naloxone 2 ng, and bupivacaine 10 mg. The control group, matched for gender, age, and DN4 sub-scale score at baseline, consisted of 31 patients with the same pathology; they were treated by fluoroscopic-guided ESI. Principal pathologies in both groups were disc disorders and/or foraminal stenosis. All patients received only one infiltration during the six months following the initial visit. The numerical rating scale (NRS-11) was assessed at the first visit and six months later. The BPI, PCS and SF-12 were compared in both groups. Overall satisfaction in pain relief after six months was assessed with a scale of 1 (very unsatisfied) to 6 (very satisfied). Results: Average NRS-11 scores for the seven days preceding the first visit and after six months were compared in both groups. The same comparison was made for overal1 treatment satisfaction. There is no significant difference in the NRS-11 and in the satisfaction scores between the two groups. Discussion/conclusion: Neither of the two methods was shown to be superior to the other in pain relief and overall treatment satisfaction after six months. Considering the possible complications and side effects of ESI, PVI with a non-steroid mixture might be considered as an alternative method. Possibly, multiple PVIs could further decrease pain. Well-designed studies are needed to evaluate this hypothesis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".