Study of Diabetic Peripheral Neuropathy in Adults of Telangana
Bibliographic record
Abstract
Background: Diabetic peripheral neuropathy (DPN) predisposes to foot ulceration and gangrene. It has been reported thatprevalence of DPN is lower in Indians relative to Caucasians. Studies among recent onset patients with type 2 diabetesmellitus (Type2-M) are very few. We studied the prevalence and risk factors of DPN in patients with newly diagnosedType2DM.Methods: We prospectively studied 80 consecutive patients over age 30 with a duration of diabetes ≤1 year. Every patientunderwent a clinical and biochemical evaluation and was screened for DPN using TCSS scale (Toronto clinical scoringsystem) and Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale.Results: The cases had a mean age of 60.28 years and duration of symptoms of DM is <1year prior to presentation. Theoverall prevalence of DPN was 12.5%. The prevalence of DPN showed an increasing trend with FBS (trend chi-square=3.517, P = 0.0304). A logistic regression analysis showed that DPN was independently associated with Fasting Blood Sugar(P = 0.0304), Body mass index (P= 0.0389), HbA1c (P = 0.0451), family history (P= 0.0426) and physical activity (P= 0.0219)but not with age, sex and education.Conclusions: Our study showed high prevalence of PN in recently diagnosed patients with Type2DM, which wasindependently associated with age and duration of symptoms of diabetes prior to the diagnosis. FBS, HbA1c, BMI, werefound to be risk factors for prevalence of Diabetic Neuropathy.
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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 | 0.001 | 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".