Risk Factors for Microalbuminuria in Children and Adolescents with Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to investigate the influence of sex, age, diabetes duration, puberty, blood pressure, glycemic control and parental blood pressure on microalbuminuria in children with type 1 diabetes. STUDY DESIGN: The study was a multicenter cross-sectional survey including 702 children and adolescents (age = 14.3+/-2.9 yr) with type 1 diabetes duration of 7.6+/-3.1 yr. One third of the population had not undergone pubertal development. Blood pressure was measured in children and their parents using a Dinamap instrument. Microalbuminuria was defined as a urinary albumin excretion rate > or = 15 microg/min measured on at least two out of three urine collections. HbA1c centrally measured by HPLC, was 8.7+/-1.5%. RESULTS: The proportion of permanent microalbuminuria was 5.1+/-1.6%. The prevalence was significantly enhanced after 10 yr of diabetes duration (11.6+/-5.2%) and complete puberty (8.2+/-3.1%). Independent risk factors for microalbuminuria tested in a logistic regression model were diabetes duration (OR/1 yr = 1.04-1.32), complete puberty (OR = 5.02-8.0), and maternal hypertension (OR = 1.94-4.28). HbA1c had a borderline independent and significant effect (OR/1% = 0.96-1.62; p = 0.07). CONCLUSIONS: Our results indicate that pubertal adolescents with a long duration of the disease and maternal history of hypertension are candidates for targeted interventions with the objective of reducing the rate of developing nephropathy in these individuals.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".