EP15.18: Anomalies, growth and performance of obstetrical ultrasound in an indigenous birth cohort of mothers with type 2 diabetes: the next generation study
Bibliographic record
Abstract
There is emerging evidence that indigenous women with diabetes in pregnancy and their offspring have poorer health outcomes compared to the non-Indigenous population. The purpose of this analysis was to determine the performance of obstetrical ultrasound in this high-risk population. This was a retrospective cohort study of ultrasound data from pregnancies within the next generation cohort. The next generation longitudinal study is an indigenous birth cohort of children born to mothers with pre-gestational type 2 diabetes. Antenatal variables, perinatal outcomes, and ultrasound information from stored reports and images were collected. Antenatal ultrasound diagnoses were correlated to postnatal findings by a blinded observer and descriptive statistics then used to analyse outcomes within the cohort. McNemar's and paired t-tests were used to further compare outcomes. For this review, 112 mother-child pairs between 1995 and 2015 were identified. Most mothers in this cohort were young (mean age 21 years), overweight/obese (72%), and had suboptimal glycemic control periconceptionally (median HbA1C 9.3%). 25% of midtrimester scans were reported as incomplete due to inadequate visualisation of fetal anatomy and required repeat examinations. Almost 1 in 5 fetuses had structural anomalies, the most common of which were renal. Midtrimester ultrasound missed one-third of anomalies including 3 of 7 cardiac defects in this cohort. Fetal ultrasound also significantly underestimated birth weight (p < 0.05). Knowledge of the high incidence of incomplete anatomic survey at time of midtrimester scans and missed anomalies (particularly cardiac) can be used to better inform timing, performance and counseling of obstetrical ultrasound in this population. The significant underestimation of birth weight may also directly impact intrapartum and postnatal care and warrants further study. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".