Investigation of Depression in Greek Patients with Diabetic Peripheral Neuropathy
Bibliographic record
Abstract
BACKGROUND: Considerable studies directly connect the complications in diabetic patients, and especially peripheral neuropathy, with the emergence of depression. Neuropathetic pain may deteriorate the general health status of the diabetic patient and glycaemic regulation. PURPOSE: The purpose of this study was to investigate the appearance and degree of diabetic peripheral neuropathy and its correlation with depression, with other parameters of the disease and also duration. METHODS: 57 diabetic patients participated with diagnosed diabetic peripheral neuropathy (male n=27, female n= 30, mean of age 72.7±6.35 years). The first part of Michigan Neuropathy Screening Instrument and the Zung Depression Rating Scale were used as tools for our study. Data was analysed with the SPSS 18.0 statistic program. RESULTS: 57.9% of the patients were overweight, 35.1% were obese and only 7% were within normal weight range. The BMI findings between the two genders indicate that male participants are more often obese than females. Women surpassed men in the category of overweight patients (p < 0.05). The score based on MNSI was high and between 3 to 12 (mean average of 8.19±2.60 with 8 as intermediate rate). Almost 60% of patients had severe neuropathy, only 2 were found with mild symptoms and the rest had moderate neuropathtic symptoms, based on the score summary from the questionnaire. Investigating in detail the relation of diabetic neuropathy and depression, it derives that a high degree of diabetic neuropathy is related with high score of depression [F(3.160)=9.821, p=0.001]. Moderate and severe neuropathy was found with almost the same levels of depression. CONCLUSIONS: The correlation between diabetic neuropathy and depression is confirmed, while a very high depression rate was found in patients with severe neuropathy. The issue needs further study by using common instruments to obtain comparative results from the scientific community.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".