Efficacy and Safety of Intravenous Immunoglobulin as Adjuvant Treatment for Refractory Neuropathic Pain. Results of an Open-Label, Multicenter Study
Bibliographic record
Abstract
INTRODUCTION: Neuropathic pain is frequently associated with many peripheral nervous system diseases and its successful treatment is an area of significant and critical unmet need. METHODS: Twenty adult outpatients of both sexes who had been suffering from painful polyneuropathy resistant to conventional therapies for at least 6 months and up to a maximum of 5 years and who reported severity of pain >60 units on a visual analog scale (VAS) at baseline were included in this open-label pilot study. Patients were randomly 1:1 allocated to receive adjuvant intravenous immunoglobulin (IVIG) (Flebogamma®, 2 g/kg) in addition to their regular therapy or to continue with the previous therapy (control group). RESULTS: The mean value of pain intensity (VAS) in the IVIG group dropped from 88 at baseline to 49 after the first week, and to 28 after 4 weeks, while values in the control group only slightly changed, from 85 to 78 after 1 week and to 75 after 4 weeks (P < 0.01). Almost 100% of patients reported strong/medium pain (Short Form McGill Pain Questionnaire) in both groups at baseline, while after 4-8 weeks, pain was reduced to moderate/light in 90% of patients in the IVIG group, whereas no improvement was reported in the control group (P < 0.01). In patients' quality of life, scores of the IVIG group (Short Form 36, Clinical Global Impression of Change, and Patient Global Impression of Change questionnaires) in all the follow-up were significantly higher than those of the control group (P < 0.01). CONCLUSION: This unblinded pilot study showed a beneficial effect of IVIG on neuropathic pain intensity and quality of life in patients resistant to conventional treatments.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".