Good agreement between hyperinsulinemic‐euglycemic clamp and 2 hours oral minimal model assessed insulin sensitivity in adolescents
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Rates of dysglycemia are increasing in youth, secondary to obesity and decreased insulin sensitivity (IS) in puberty. The oral minimal model (OMM) has been developed in order to measure IS using an easy oral glucose load, such as an oral glucose tolerance test (OGTT), instead of an hyperinsulinemic-euglycemic clamp (HE-clamp), a more invasive and time-consuming procedure. However, this model, following a standard 2 hour- OGTT has never been validated in youth, a population known for a different physiologic response to OGTT than adults. Thus, we compared IS measurements obtained from OMM following a 2-hour OGTT to HE-clamp and isotope tracer-assessed tissue IS in adolescents. We also compared the liver/muscle-specific IS from HE-clamp with other liver/muscle-specific IS surrogates following an OGTT previously validated in adults. METHODS: ) and other OGTT-derived muscle and liver IS indices were correlated with HE-clamp tissue-specific IS. RESULTS: correlated with HE-clamp-measured peripheral IS (r = 0.64, P <.0001 and r = 0.73; P <.0001, respectively) and the correlation coefficient trended higher than the Matsuda index (r = 0.59; P =.003). The other tissue-specific indices were poorly correlated with their HE-clamp measurements. CONCLUSION: In adolescent girls, the 2-hour OMM provided the best estimate of peripheral IS. Additional surrogates for hepatic IS are needed for youth.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".