Comparative effectiveness of initiating nifedipine versus labetalol in early gestation for chronic hypertension in pregnancy
Bibliographic record
Abstract
Background: Limited data exist on the comparative effectiveness and safety of first-line medications to treat chronic hypertension in pregnancy. We compared nifedipine versus labetalol initiation before 23 weeks gestation for risk of pregnancy loss (miscarriage or stillbirth) and preterm birth (<37 weeks). Methods: We identified pregnancies in Merative's MarketScan commercial claims data with estimated last menstrual periods between July 1, 2016 and February 1, 2022. We included those with a new nifedipine or labetalol fill before 23 weeks gestation. We estimated risks, risk differences (RDs) per 100 pregnancies, and risk ratios (RRs) among nifedipine versus labetalol initiators using a weighted Aalen-Johansen estimator to account for confounding and informative censoring. We also conducted a post hoc analysis to estimate the comparative effect of nifedipine versus labetalol on risk of preeclampsia. Results: We identified 987 nifedipine and 4,570 labetalol initiators during the study period. The weighted risk of pregnancy loss was 7.0% among nifedipine and 6.0% among labetalol initiators (RD=1.1 [-0.7, 2.8]; RR=1.18 [0.87, 1.59]). Weighted risks of preterm birth were 29.4% versus 22.2%, respectively (RD=7.2 [3.9, 10.5], RR=1.32 [1.13, 1.55]). In post hoc analyses, the weighted risks of preeclampsia were 38.6% versus 33.9%, respectively (RD=4.7 [0.7, 8.7], RR=1.14 [1.01, 1.28]). Findings were consistent across various sensitivity analyses. Conclusions: Compared to labetalol initiators, nifedipine initiators experienced an increased risk of preterm birth but not pregnancy loss. The elevated risk of preterm birth may be explained by an increased risk of preeclampsia among nifedipine initiators, resulting in medically indicated preterm birth.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".