Earlier Onset of Complications in Youth With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To evaluate the risk of complications in youth with type 2 diabetes. RESEARCH DESIGN AND METHODS: Population-based cohorts of 342 youth (1-18 years of age) with prevalent type 2 diabetes, 1,011 youth with type 1 diabetes, and 1,710 nondiabetic control youth were identified between 1986 and 2007 from a clinical registry and linked to health care records to assess long-term outcomes using ICD-9CM and ICD-10CA codes. RESULTS: Youth with type 2 diabetes had an increased risk of any complication (hazard ratio 1.47 [95% CI 1.02-2.12]). Significant adverse clinical factors included age at diagnosis (1.08 [1.02-2.12]), HbA1c (1.06 [1.01-1.12]), and, surprisingly, renin-angiotensin-aldosterone system (RAAS) inhibitor use (1.75 [1.27-2.41]). HNF-1α G319S polymorphism was protective in the type 2 diabetes cohort (0.58 [0.34-0.99]). Kaplan-Meier statistics revealed an earlier diagnosis of renal and neurologic complications in the type 2 diabetes cohort, manifesting within 5 years of diagnosis. No difference in retinopathy was seen. Cardiovascular and cerebrovascular diseases were rare; however, major complications (dialysis, blindness, or amputation) started to manifest 10 years after diagnosis in the type 2 diabetes cohort. Youth with type 2 diabetes had higher rates of all outcomes than nondiabetic control youth and an overall 6.15-fold increased risk of any vascular disease. CONCLUSIONS: Youth with type 2 diabetes exhibit complications sooner than youth with type 1 diabetes. Younger age at diagnosis is potentially protective, and glycemic control is an important modifiable risk factor. The unexpected adverse association between RAAS inhibitor use and outcome is likely a confounder by indication; however, further evaluation in young people is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".