Methods
Study population . This retrospective cohort study was conducted at Kaiser Permanente, a US healthcare system providing healthcare and insurance coverage. Participating regions were Washington, Southern California, and Northern California, which together serve about 8 million people generally representative of the surrounding communities.17 Data came from EHRs and linked birth certificate data. These data have been used in many pregnancy studies,18-21 and important variables and methods have been validated.22-25 Study procedures were approved by the regions’ institutional review boards and those of Washington State and California, with a waiver of consent.
The population was women age 15-49 years with a singleton live or stillbirth from 2005 through 2014. Women were required to be enrolled in Kaiser Permanente from 16 weeks’ gestation through delivery, to have at least one blood pressure (BP) measured before 20 weeks, and to have chronic or gestational hypertension (defined from BP values, diagnosis codes and medication fills; our algorithm is shown in Table S1 and has been published26). We included both chronic or gestational hypertension because in clinical practice, it can be difficult to determine which type of hypertension is present and because these conditions may represent different points on a continuum of disease.
Women had to have filled at least one antihypertensive medication before 36 weeks gestation, to be on monotherapy, and to have been enrolled in Kaiser Permanente for at least 150 days before their qualifying fill. They could contribute more than one pregnancy to these analyses. We excluded deliveries exposed to teratogenic medications or certain high-risk maternal medical conditions (see Table S1 for more information). The sample size was determined by the number of eligible births.
Exposures. From pharmacy data, we identified fills for labetalol, methyldopa, nifedipine and other β-blockers (Table S1). We considered labetalol separately from other β-blockers because it is a combined α and β-blocker and unlike other β-blockers, it is recommended as first-line in US guidelines.6 Exposure was defined based on the earliest fill after the first prenatal visit (typically at 8-10 weeks’ gestation) or, if the visit date was unknown, at ≥ 10 weeks gestation; we called this the ‘index fill’. Using intent to treat principles, women’s exposure status was fixed rather than time-varying, because subsequent medication switches could be affected by the initial medication choice.
Outcomes. Outcomes included small for gestational age (SGA), preterm delivery, neonatal intensive care unit (NICU) admission, preeclampsia, maternal ICU admission, and stillbirth or termination at > 20 weeks. SGA was defined using sex and race-specific US birthweight curves.27 The primary outcome was birthweight <10th percentile for gestational age and a secondary outcome < 3rdpercentile. Deliveries missing birthweight (n=32) were excluded from SGA analyses. We defined preterm delivery using gestational age from the EHR (preferentially) or birth certificate data, with the primary outcome being delivery before 37 weeks gestation and a secondary outcome, delivery before 34 weeks. We considered preterm delivery a potential measure of medication effectiveness, because less effective medications could lead to higher risk of uncontrolled maternal hypertension or fetal growth restriction (a potential consequence of severe hypertension) and via these pathways, to indicated preterm delivery. The automated data available to us do not reliably distinguish spontaneous vs. indicated preterm births. We identified ICU admissions using EHR data. Preeclampsia was identified from inpatient diagnosis codes after 20 weeks’ gestation, an approach with a positive predictive value (PPV) of 90%.28 We reviewed 45 charts meeting those criteria and found a PPV of 93%. We identified preeclampsia cases with “severe features” using modified criteria from the American College of Obstetricians & Gynecologists,29 drawing on BP values, laboratory results and diagnosis codes (Table S1).
Potential stillbirths and terminations after 20 weeks’ gestation were identified using EHR data; we included as outcomes the 76% of potential cases validated through medical record review or linkage to fetal death certificates. We grouped together stillbirths and terminations for several reasons. Terminations after 20 weeks might be done for fetal anomalies, which could in theory be affected by medication choice, as there is no definitive evidence about birth defect risk for some widely used antihypertensive medications. Also, the decision to terminate might be influenced by severe uncontrolled maternal hypertension, which could be a consequence of the initial medication choice. Finally, we hypothesized that variation in coding might lead to similar clinical scenarios being classified as either a stillbirth or termination in different instances.
Covariates . Covariates included maternal age at delivery, Kaiser Permanente region, delivery year, hypertension type (chronic or gestational), BP values, race/ethnicity, parity, maternal education, pregestational diabetes, depression, tobacco use, body mass index (BMI), and prior use of certain medications (Table S1). Hypertension was categorized as chronic if it was present prior to pregnancy or during the first 20 weeks gestation and as gestational otherwise. To account for hypertension severity, we identified the most recent BP value prior to the index fill and also determined whether a woman experienced one or more BPs ≥ 160/110 before pregnancy or during this pregnancy before the index fill. We categorized history of antihypertensive medication use as no use prior to the index fill, continuous use up to the index fill (allowing for 80% adherence), or prior use with a gap. Other covariates included prior use of angiotensin converting enzyme inhibitors, angiotensin receptor blockers, thiazide diuretics, diabetes medications, benzodiazepines, statins, antidepressants or antiseizure medications.
Analyses . Descriptive analyses included counts and proportions for categorical variables and means and standard deviations for continuous variables. Primary analyses used logistic regression to model study outcomes, with labetalol as the referent group. Inverse probability of treatment weights (IPTW) were used to account for confounding. We calculated weighted outcome prevalences for each medication group and adjusted odds ratios (aORs) and 95% confidence intervals (CIs). We used the bootstrap to account for multiple pregnancies per woman and for the estimation of the weights.30,31 Treatment weights were generated from propensity scores calculated using a multinomial logistic regression model including all covariates shown in Table 1 except for BMI, education, parity, and timing of prenatal care. We omitted these variables because they were well balanced before weighting and a small proportion of deliveries had missing information for each of these characteristics. Table S2 lists variables in the propensity score. To improve statistical efficiency, we calculated stabilized weights including some baseline covariates in both the outcome model and the numerator of the weights.32,33These were Kaiser Permanente region, race/ethnicity, diabetes, type of hypertension (chronic vs. gestational), and gestational age at index fill.
For statistical modeling, we categorized delivery year as 2005-2008, 2009-2010, 2011-2012, and 2013-2014. We grouped together the four earliest years because very few deliveries were included from 2005-2006, when only one region had electronic BP values available. Maternal age was categorized as < 30, 30-34, 35-39 or ≥ 40 years. Gestational age at the index fill was modeled as a linear spline with knots at 140 and 210 days. The systolic and diastolic BP values closest to the index fill were modeled using linear splines, with knots at 140 mm Hg and 90 mm Hg respectively. Deliveries missing race/ethnicity (0.5%) were grouped with those with “other” race/ethnicity and treated as a category of race/ethnicity in statistical models.
To assess covariate balance, we calculated the average standardized mean differences across all treatment groups before and after IPTW.34,35
We excluded stillbirths/terminations from analyses of SGA, NICU and preterm delivery because they are competing events. We used inverse probability of censoring weights to account for possible bias due to excluding stillbirths; Table S3 lists the variables used to model these weights.
In sensitivity analyses, we restricted the analysis to women with chronic hypertension (87% of the population) and excluded women with pregestational diabetes. In subgroup analyses, we examined new users separately from women with prior antihypertensive treatment. Analyses were performed using R, version 3.5.
Funding. This study was funded by the US National Institute on Child Health and Human Development grant R01HD082141. The grant proposal underwent external peer review for scientific quality, and priority was assessed by scientific staff and a scientific council at NICHD. The Group Health Foundation funded Dr. Chen’s fellowship. The funders did not play a role in conducting the research or writing the paper.
Patient involvement. There was no patient or public involvement in the study.