Hepatic fat and glucose tolerance in women with recent gestational diabetes
Bibliographic record
Abstract
OBJECTIVE: Women with a history of gestational diabetes mellitus (GDM) have an elevated risk of ultimately developing pre-diabetes and diabetes later in life. They also have an increased prevalence of fatty liver, but recent studies have reported conflicting findings on whether hepatic fat affects their risk of pre-diabetes/diabetes. Thus, we sought to evaluate the associations of liver fat with glucose homeostasis and determinants thereof in women with and without recent gestational dysglycemia. METHODS: Two hundred and fifty-seven women underwent an antepartum oral glucose tolerance test (OGTT), which diagnosed 97 with GDM, 40 with gestational impaired glucose tolerance (GIGT), and 120 with normal glucose tolerance (NGT). At a mean of 4.8 years post partum, they underwent an OGTT (which revealed that 52 had progressed to pre-diabetes/diabetes) and hepatic ultrasound, on which liver fat was graded as none (n=164), mild (n=66), or moderate (n=27). RESULTS: Liver fat was more prevalent in women with previous GDM than in those with GIGT or NGT (p=0.009) and in women with current pre-diabetes/diabetes than in those without (p=0.0003). As the severity of liver fat increased, there was a progressive worsening of insulin sensitivity and beta-cell function, coupled with rising fasting and 2-hour glucose (all p<0.0001). On multiple linear regression analyses, moderate liver fat was independently associated with lower insulin sensitivity (p=0.0002) and higher 2-hour glucose (p=0.009). Moreover, moderate liver fat emerged as an independent predictor of pre-diabetes/diabetes (OR=3.66, 95% CI 1.1 to 12.5). CONCLUSION: The higher prevalence of liver fat in women with previous GDM is associated with their increased risk of pre-diabetes/diabetes.
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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".