Should case management be considered a component of obstetrical interventions for pregnancies at risk of preterm birth?
Bibliographic record
Abstract
Preterm birth remains the leading cause of morbidity and mortality among nonanomalous neonates in the United States. Unfortunately, preterm birth rates remain high despite current medical interventions such as progestogen supplementation and cerclage placement. Case management, which encompasses coordinated care aimed at providing a more comprehensive and supportive environment, is a key component in improving health and reducing costs in other areas of medicine. However, it has not made its way into the general lexicon and practice of obstetrical care. Case management intended for decreasing prematurity or ameliorating its consequences may include specialty clinics, social services, coordination of specialty services such as nutrition counseling, home visits or frequent phone calls by specially trained personnel, and other elements described herein. It is not currently included in nor is it advocated for as a recommended prematurity prevention approach in the American College of Obstetricians and Gynecologists or Society for Maternal-Fetal Medicine guidelines for medically indicated or spontaneous preterm birth prevention. Our review of existing evidence finds consistent reductions or trends toward reductions in preterm birth with case management, particularly among individuals with high a priori risk of preterm birth across systematic reviews, metaanalyses, and randomized controlled studies. These findings suggest that case management has substantial potential to improve the environmental, behavioral, social, and psychological factors with patients at risk of preterm birth.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".