Impact of maternal body mass index and gestational weight gain on maternal and neonatal outcomes in twin pregnancies
Bibliographic record
Abstract
INTRODUCTION: To date, there have only been provisional recommendations about the appropriate gestational weight gain in twin pregnancies. This study aimed to contribute evidence to this gap of knowledge. MATERIAL AND METHODS: Using a cohort of 10 603 twin pregnancies delivered between 2000 and 2015 in the state of Hessen, Germany, the individual and combined impact of maternal body mass index and gestational weight gain on maternal and neonatal outcomes was analyzed using uni- and multivariable logistic regression models. The analysis used newly defined population-based quartiles of gestational weight gain in women carrying twin pregnancies (Q1: <419.4 g/week [low weight gain], Q2-Q3: 419.4-692.3 g/week [optimal weight gain], Q4: >692.3 g/week [high weight gain]) and the World Health Organization body mass index classification. RESULTS: was associated with significantly increased rates of cesarean deliveries (aOR1.2, 95% CI: 1.01-1.41) and pregnancy-induced hypertensive disorders (aOR 1.53, 95% CI: 1.11-2.1) but not with any adverse neonatal outcome. Perinatal mortality (aOR 2.23, 95% CI: 1.38-3.6), preterm birth (aOR 1.88, 95% CI: 1.58-2.25), APGAR'5 < 7 (aOR 1.61, 95% CI: 1.19-2.17) and admissions to the neonatal intensive care unit (aOR 1.6, CI: 1.38-1.85) were increased among women with low gestational weight gain. Rates of cesarean deliveries were high in both women with low (aOR 1.25, 95% CI: 1.05-1.48) and high gestational weight gain (aOR 1.17, 95% CI: 1.01-1.35). A high gestational weight gain was also associated with higher rates of hypertensive disorders in pregnancy (aOR 2.32, 95% CI: 1.79-3.02) and postpartum hemorrhage (aOR 1.72, 95%CI: 1.12-2.63). The risk of preterm birth, low Apgar scores and NICU admissions showed a converse linear relation with pre-pregnancy body mass index in women with low gestational weight gain. CONCLUSIONS: In twin pregnancies, nonoptimal weekly maternal weight gain seems to be strongly associated with maternal and neonatal adverse outcomes. Since gestational weight gain is a modifiable risk factor, health care providers have the opportunity to counsel pregnant women with twins and target their care accordingly. Additional research to confirm the validity and generalizability of our findings in different populations is warranted.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".