The association between adipocytokines and glycemic control in women with gestational diabetes mellitus
Bibliographic record
Abstract
Objective: To evaluate the relationship between adipocytokines and glycemic control.Study design: Prospective observational trial of gestations with gestational diabetes mellitus (GDM). Fasting glucose (FG), insulin, adiponectin, leptin, chemerin, retinol-binding protein 4 (RBP-4), osteocalcin, and resistin were measured. HomeOstasis model assessment of insulin resistance (HOMA-IR) and QUantitative insulin sensitivity ChecK Index (QUICKI) were calculated. Women who required medications for glycemic control were compared to women using nutritional therapy only.Results: Overall, 75 women were included −26 (34.7%) required medications to achieve good glycemic control. Factors associated with poor control are as follows: low resistin (aOR 0.84), HOMA-IR (aOR 1.96), QUICKI (aOR 0.62), first trimester FG (aOR 1.43), and maternal age (aOR 1.26). HOMA-IR and QUICKI performed highest for prediction. Resistin, first trimester FG, maternal age, and QUICKI had an AUC of 0.878, sensitivity and specificity of 87.5% for the prediction of the need for medications.Conclusions: Low resistin is associated with poor control. A model utilizing maternal age, first trimester fasting glucose, and first visit QUICKI yields good predictability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".