Effect of Cocoa Supplementation on the Biochemical and Clinical Profile and the Somatosensory Processing of Diabetic Peripheral and Autonomic Neuropathy: A Randomized Clinical Trial
Bibliographic record
Abstract
Peripheral and autonomic neuropathy are common in type 2 diabetes; they are associated with oxidative stress and inflammation. Cocoa, rich in polyphenols, may offer neuroprotective benefits. This study evaluated the effect of cocoa supplementation on the biochemical, clinical, and somatosensory profile of neuropathy in individuals with type 2 diabetes. A 12-week, double-blind controlled trial involved 39 subjects randomized to receive cocoa capsules (50 mg polyphenols) or placebo (methylcellulose). Evaluations included glycemic and lipid profiles, neutrophil/lymphocyte ratio, blood pressure, standardized questionnaires, anthropometric measurements, and the rate-dependent depression of the H-reflex. In the cocoa group, the Toronto score decreased by 2.63 points and the BEST score decreased by 1.45 points. In the placebo group, these reductions were 1.84 and 2.21 points, respectively. Neither difference was statistically significant between groups (p > 0.05). Quality-of-Life questionnaire score decreased by 9.2 points in the cocoa group, but without significant difference to the placebo group (p = 0.501). Fasting glucose and HbA1c levels decreased in the placebo group by 38 mg/dL (0.28%) but were not significantly different from the cocoa group (p > 0.05). No other intra- or inter-group differences were significant (p > 0.05). Cocoa supplementation did not show significant improvements over the placebo in the measured outcomes. Both groups showed persistent abnormalities in spinal somatosensory processing, with an RDD of the H-reflex ≥ 0.5.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".