Effect of Lifestyle Interventions on Diabetic Peripheral Neuropathy in Patients with Type 2 Diabetes, Result of a Randomized Clinical Trial
Bibliographic record
Abstract
OBJECTIVES: Diabetic peripheral neuropathy (DPN) is the most common and troublesome complication of diabetes leading to great morbidity and resulting in a huge economic burden for diabetes care. Over half of people with diabetes develop neuropathy. Also, DPN is a major cause of reduced quality of life due to pain, sensory loss, gait instability, fall-related injury, and foot ulceration and amputation. The aim of this study was evaluating the effects of lifestyle interventions on diabetic neuropathy severity in diabetes type 2 outpatients. METHODS: This clinical trial conducted on 74 patients with DPN that divided with random allocation into intervention or control group. The lifestyle interventions applied in the intervention group beginning four educational sessions on lifestyle that emphasize strategies for lowering blood sugar, increasing physical activity, promoting weight loss, prudent diet, and foot caring. Each session was lasted for1.5 hour. Then patients followed for 12 weeks. During this period, they received counseling on mentioned lifestyle interventions. DPN severity in both groups measured using modified Toronto Clinical Neuropathy Score (mTCNS) at the beginning of study and at the end of counseling for 12 weeks. RESULTS: Comparing differences of mean of DNP severity before and after lifestyle intervention between two groups of study, there was a significant difference (p<0.001). DNP severity in control group had not any change or it increased in some participants, but DNP decreased in intervention group, after applying lifestyle intervention. CONCLUSION: Lifestyle interventions can contribute to reducing DPN severity, and consequently decreasing neuropathic pain.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".