Assessment of MiR-191-5p as a Predictive Marker of Early Diabetic Sensorimotor Polyneuropathy in Patients with Newly Diagnosed Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Diabetic sensorimotor polyneuropathy (DSPN) is the most common complication of type 2 diabetes mellitus (T2DM) and the major cause of nontraumatic lower limb amputation. We aimed in the current research to investigate miR-191-5p as a noninvasive predictive biomarker of DSPN among patients recently diagnosed with T2DM in associations with clinical and electrophysiological tests.Methods: We conducted fifty cases recently diagnosed with T2DM and 50 healthy control subjects. contributors were evaluated by clinical and laboratory investigations in addition to nerve conduction studies. circulatory miR-191-5p assessed using the Real-Time PCR method.Results: miR-191-5p levels were lower in patients with DSPN compared to patients without DSPN and controls. Remarkably, miR-191-5p levels were significantly negatively correlated with cardiometabolic risk factors and neuropathy scores; Neuropathy Disability Score (NDS), Neuropathy Symptom Score (NSS), and Toronto Clinical Scoring System (TCSS), p ˂0.001*. The linear regression test revealed that TCSS, HbA1c, and LDL were the main independent variables against Mir-191-5p levels in patients with DSPN, p ˂0.001*. To assess the predictive values of miR-191-5p we applied the ROC curve the cutoff values of miR-191-5p as a predictive marker for DSPN was (0.559), with a sensitivity of (95%) and a specificity of (98.7%), with the AUC was 0.958 (0.922-0.993), p ˂0.001*). Conclusion: circulating miR-191-5p was significantly downregulated in patients recently diagnosed with T2DM, more specifically in patients with DSPN, and it could be used as a biomarker for predicting diabetes and DSPN.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".