Rating the seriousness of maternal and child health outcomes linked with pregnancy weight gain
Bibliographic record
Abstract
BACKGROUND: Current pregnancy weight gain guidelines were developed based on implicit assumptions of a small group of experts about the relative seriousness of adverse health outcomes. Therefore, they will not necessarily reflect the values of women. OBJECTIVE: To estimate the seriousness of 11 maternal and child health outcomes that have been consistently associated with pregnancy weight gain by engaging patients and health professionals. METHODS: We collected data using an online panel approach with a modified Delphi structure. We selected a purposeful sample of maternal and child health professionals (n = 84) and women who were pregnant or recently postpartum (patients) (n = 82) in the United States as panellists. We conducted three concurrent panels: professionals only, patients only, and patients and professionals. During a 3-round online modified Delphi process, participants rated the seriousness of health outcomes (Round 1), reviewed and discussed the initial results (Round 2), and revised their original ratings (Round 3). Panellists assigned seriousness ratings (0, [not serious] to 100 [most serious]) for infant death, stillbirth, preterm birth, gestational diabetes, preeclampsia, small-for-gestational-age (SGA) birth, large-for-gestational-age (LGA) birth, unplanned caesarean delivery, maternal obesity, childhood obesity, and maternal metabolic syndrome. RESULTS: Each panel individually came to a consensus on all seriousness ratings. The final median seriousness ratings combined across all panels were highest for infant death (100), stillbirth (95), preterm birth (80), and preeclampsia (80). Obesity in children, metabolic syndrome in women, obesity in women, and gestational diabetes had median seriousness ratings ranging from 55 to 65. The lowest seriousness ratings were for SGA birth, LGA birth, and unplanned caesarean delivery (30-40). CONCLUSION: Professionals and women rate some adverse outcomes as being more serious than others. These ratings can be used to establish the range of pregnancy weight gain associated with the lowest risk of a broad range of maternal and child health outcomes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".