Adequacy of Prenatal Care in Young Pregnant Adolescents: A Retrospective Cohort Study [26C]
Bibliographic record
Abstract
INTRODUCTION: Adolescents often receive suboptimal prenatal care, which may account for increased adverse outcomes. We determined the distribution of inappropriate prenatal care by maternal age, examined the temporal trend of inappropriate care among adolescents ages 12-15 and their effects on neonatal outcomes. METHODS: Using the CDC Period Linked Birth/Infant Death File, we conducted a retrospective cohort study of adolescents ages 12-15 who delivered between 2011-2015. Adequacy of care was measured using the R-G INDEX. Linear regression analysis was used to measure adequacy of care and unconditional multivariate logistic regression was used to examine its effects on neonatal outcomes. RESULTS: We observed decreasing rates of inappropriate care with rising maternal age. Among 63,484 adolescents ages 12-15, 14,845 (23.38%) received inappropriate care with rates rising significantly during the study period. Inappropriate care was most common among mothers ages 12-15 who were of Black (31.74%) or Hispanic ethnicity (26.66%), those with more than one prior birth (two prior births 30.30%), those presenting to their first prenatal visit at >7 months gestation (97.51%), and those with higher BMIs (BMI 25-29.9 28.16%, BMI 35-39.9 29.69%, BMI 40+ 33.78%). Neonates born to adolescents ages 12-15 and who received inappropriate prenatal care were significantly more likely to involve IUGR (7.58%, OR1.40, 95% CI (1.30-1.51)), infant deaths (1.33%, OR 1.35, 95% CI (1.15-1.58)) and NICU admissions (9.84%, OR 1.27, 95% CI (1.19-1.35)). CONCLUSION: Inappropriate care decreased with rising maternal age. Adolescents ages 12-15 experienced increasing rates of inappropriate care from 2011-2015 and were associated with certain demographics and poorer neonatal outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".