Nutritional intakes of patients with chronic pain and the effect of soy protein on neuropathic facial pain: a pilot study
Bibliographic record
Abstract
Only scarce data exist about the nutrient intake and diet quality of subjects suffering from chronic pain as well as the effects of dietary nutrients on pain severity. We assessed nutrient intake adequacy of 79 patients with chronic pain and examined possible dietary correlates of pain levels (visual analog scale).Usual dietary intakes were estimated from three 24-h food recalls and compared to the US-Canadian Dietary Reference Intakes and with those of a healthy population of the same age and sex (Canadian Community Health Survey 2.2.). Intakes of many nutrients (notably vitamins D, E, K and potassium) were below Estimated Average Requirements and those of the general population in >39% of the patients, which suggests greater risks of nutrient deficiencies. Energy, carbohydrates and vitamin E intakes were weakly and negatively associated with pain levels (r≤-0.30, P≤0.043). Among the various forms of chronic pain, neuropathic facial pain lacks effective management. Soy protein has been shown to decrease neuropathic pain in animal and few human studies. Thus, we tested the feasibility, compliance and effects of a diet enriched with soy protein against milk protein on chronic neuropathic facial pain, in a pilot study using an N-of-1 design. Participants were randomly and blindly exposed to a soy or milk protein powder during 3 week-intervals, in 3 paired treatment periods. Dietary intakes (24-h food recall and food frequency questionaire), pain intensity (Numerical Rating Scale), depression levels (Beck Depression Inventory-II), and quality of life (Pain Disability Index) indices were assessed at baseline and followed up during each period. The soy protein rich diet did not improve pain symptoms. The dietary intervention was a feasible but difficulties were encountered with recruitment, retention into the study and acceptability of the treatment products. Due to these barriers resulting in a small sample size, the absence of a soy effect is inconclusive. Future studies should consider other dietary approaches or better quality protein powder products to improve acceptability. The effect of soy protein on pain severity also warrants confirmation with future larger studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".