Prevalence, Pattern and Factors Associated with Diabetic Peripheral Neuropathy in Benha City, Egypt
Bibliographic record
Abstract
Background:Diabetic peripheral neuropathy (DPN) is the most frequent kind of neuropathy globally. DPN is one of the most prevalent and serious microvascular consequences of diabetes.Objective: To assess prevalence of DPN, its pattern, severity and associated risk factors in Benha City, Egypt. Patients and methods: This cross-sectional observational study was conducted on 500 diabetic patients (type 1 and type 2). All patients were subjected tocomplications of diabetes especially microvascular and macrovascular complications, diabetic foot and history of previous operations, physical examinations (general, neurological, sensory examination and Toronto clinical scoring system (TCSS)) and laboratory investigations (CBC, hemoglobin A1c (HbA1c), kidney function tests, liver function tests, serum thyroid-stimulating hormone and lipogram).Results: Body mass index (BMI), height, duration of diabetes, HbA1c, and thyroid-stimulating hormone (TSH) had a strong positive significant correlation with TCSS score (r=0.338, P< 0.001; r=0.335, P< 0.001; r=0.630, P< 0.001; r=0.806, P< 0.001; r=0.332, P< 0.001 respectively). Low-density lipoprotein-cholesterol (LDL-C) level and triglycerides level had no significant correlation with TCSS score (r= 0.015, P= 0.743; r= 0.074, P= 0.097 respectively). Conclusions: The primary risk factors include higher BMI, height, hard working, smoking, poor glycemic management, extended diabetes mellitus (DM), metformin use, chronic kidney disease (CKD), and an abnormal thyroid profile. After documenting these findings, a greater effort should be made to lower the frequency and severity of PDN in diabetic patients by education emphasising regular foot care, strict glucose control, and lifestyle adjustment.
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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 | 0.000 |
| 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) | 0.002 | 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".