Gestational diabetes mellitus in twin pregnancies versus singleton pregnancies—A retrospective case–control study
Bibliographic record
Abstract
AIMS: To compare markers of glycaemic regulation in twin and singleton pregnancies in women with gestational diabetes mellitus (GDM). METHODS: A retrospective case-control study was performed. 53 twin and 212 matched singleton pregnant women with gestational diabetes were included. Data were obtained from patient files. Twin and singleton pregnant women were compared regarding clinical characteristics and parameters related to glucose metabolism. RESULTS: Compared to singleton pregnant women, twin pregnant women were diagnosed with GDM earlier in pregnancy (gestational age (GA) (weeks + days) 24 + 5 ± 5 + 2 vs. GA 27 + 2 ± 5 + 2; p = 0.002). The proportion of women treated with insulin was similar (24.1% vs. 24.5%, p = 1.0), but in twin pregnancies, insulin treatment was commenced earlier (GA 25 + 2 ± 4 + 6 vs. GA 30 + 1 ± 5 + 0; p = 0.003). At diagnosis, the HbA1c value was significantly lower in twin pregnant women (34 (5.3) ± 4.8 (2.6) vs. 35.9 (5.4) ± 5.4 (2.6), p = 0.03), but mean HbA1c values were similar in 2nd (33.9 (5.3) ± 4.6 (2.6) vs. 35.7 (5.4) ± 5.3 (2.6), p = 0.16) and 3rd trimester (35.1 (5.5) ± 4.2 (2.5) vs. 36.0 (5.4) ± 5.1 (2.6), p = 0.25). CONCLUSIONS: We have characterized the effect of twin pregnancy on parameters of glucose metabolism and glycaemic control in GDM in one of the largest studies of twin pregnant women with GDM to date. We conclude that twin pregnant women may have the GDM diagnosis earlier, but diurnal insulin requirements and HbA1c levels are comparable with singleton pregnant women.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".