Lack of Validity of the Glucose Management Indicator in Type 1 Diabetes in Pregnancy
Bibliographic record
Abstract
OBJECTIVE: The glucose management indicator (GMI) is widely used as a replacement for HbA1c, but information in pregnancy is very limited. We assessed the accuracy of GMI and associations with pregnancy outcomes in type 1 diabetes. RESEARCH DESIGN AND METHODS: We compared HbA1c, continuous glucose monitoring (CGM) metrics, GMI at 12, 24, and 34 weeks' gestation and outcomes in 220 women from the Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) using logistic/linear regression and Bland-Altman plots. RESULTS: GMI equations performed less accurately in pregnancy, with higher bias, especially in first and third trimesters. GMI and mean CGM glucose had equivalent predictive capability over pregnancy outcomes. GMI did not offer additional predictive capability over time in range (63-140 mg/dL; 3.5-7.8 mmol/L), time above range (>140 mg/dL; >7.8 mmol/L), and average CGM glucose concentrations. CONCLUSIONS: GMI is not an accurate replacement for HbA1c in pregnancy in women with type 1 diabetes.
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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 | 0.060 | 0.209 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".