Nail fold microangiopathy in adolescents with type 1 diabetes: Relation to diabetic vascular complications
Bibliographic record
Abstract
OBJECTIVES: Microangiopathy is implicated in the pathogenesis of diabetic vascular complications. Nail fold videocapillaroscopy (NVC) is an easy non-invasive tool of microvasculature assessment. This study compares the NVC changes in adolescents with Type1 diabetes (T1D) to healthy controls and correlates them to diabetic vascular complications. METHODS: Hundred thirty-five adolescents with T1D (disease duration 5 years) were compared to 135 matched controls. Diabetes duration, insulin therapy, fundus, and Toronto clinical scoring system (TCSS) were assessed. Fasting lipids, fraction-C of glycosylated hemoglobin (HbA1C), urinary albumin creatinine ratio (UACR), nerve conduction velocity, and NVC were performed. RESULTS: NVC changes were found in 120 adolescents with T1D (88.8%). These changes were significantly higher in adolescents with T1D than controls (p < .001). Significant positive relation was found between NVC changes and TCSS (p = .006), diabetes duration (p = .001), HbA1C (0.008), cholesterol (p = .011), LDL (0.016), UACR (p < .001), and nerve conduction velocity (p < .001). Multivariate logistic regression study revealed that diabetic nephropathy and neuropathy were independently associated with NVC changes (p < .001 and p = .007, respectively). CONCLUSION: Adolescents with T1D have significantly higher NVC changes than controls. These changes were more evident in those having vascular complications than those without. Thus, NVC can be a potential non-invasive tool for early assessment and follow-up of the microvasculature among adolescents with T1D.
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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) | 0.002 | 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".