Background: Clinical risk factors, a single blood pressure (BP) measurement, current biomarkers, and biophysical parameters can effectively identify risk of early‐onset preeclampsia but have limited ability to predict later‐onset preeclampsia and gestational hypertension. Clinical BP patterns hold promise to improve early risk stratification for hypertensive disorders of pregnancy. Methods and Results: After excluding preexisting hypertension, heart, kidney, or liver disease, or prior preeclampsia, the retrospective cohort (n=249 892) all had systolic BP <140 mm Hg and diastolic BP <90 mm Hg or a single BP elevation ≤20 weeks' gestation, prenatal care at <14 weeks' gestation, and a still or live birth delivery at Kaiser Permanente Northern California hospitals (2009–2019). The sample was randomly split into development (N=174 925; 70%) and validation (n=74 967; 30%) data sets. Predictive performance of multinomial logistic regression models for early‐onset (<34 weeks) preeclampsia, later‐onset (≥34 weeks) preeclampsia, and gestational hypertension was evaluated in the validation data set. There were 1008 (0.4%), 10 766 (4.3%), and 11 514 (4.6%) patients with early‐onset preeclampsia, later‐onset preeclampsia, and gestation hypertension, respectively. Models with 6 systolic BP trajectory groups (0–20 weeks' gestation) plus standard clinical risk factors performed substantially better than risk factors alone to predict early‐ and later‐onset preeclampsia and gestational hypertension, with C‐statistics (95% CIs) of 0.747 (0.720–0.775), 0.730 (0.722–0.739), and 0.768 (0.761–0.776) versus 0.688 (0.659–0.717), 0.695 (0.686–0.704) and 0.692 (0.683–0.701), respectively, with excellent calibration (Hosmer‐Lemeshow P =0.99, 0.99, and 0.74, respectively). Conclusions: Early pregnancy BP patterns up to 20 weeks' gestation plus clinical, social, and behavioral factors more accurately discriminate hypertensive disorders of pregnancy risk among low‐to‐moderate risk pregnancies. Early pregnancy BP trajectories improve risk stratification to reveal higher‐risk individuals hidden within ostensibly low‐to‐moderate risk groups and lower‐risk individuals considered at higher risk by US Preventive Services Task Force criteria.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) increase cardiovascular disease risk. Blood pressure (BP) trajectories ≤20 weeks’ gestation predict HDP outcomes. We hypothesized that early-pregnancy BP patterns stratify risk of developing hypertension years after pregnancy. METHODS: This prospective cohort of 174 774 women without prior hypertension, kidney, liver, or heart disease, or history of preeclampsia entered prenatal care ≤14 weeks and delivered a stillborn or live singleton birth at Kaiser Permanente Northern California hospitals (2009–2019). Electronic health records provided data, including HDP for each birth, longitudinal outpatient clinical BP measurements, International Classification of Diseases codes, and medication use to identify new-onset hypertension from 2 months through 14 years post-delivery (2009–2023). Latent class trajectory modeling identified 6 BP trajectory (BPT) groups capturing both BP levels and slopes from 0 to 20 weeks’ gestation. Multivariable Cox regression models estimated the hazard ratio (95% CIs) of new-onset hypertension after pregnancy associated with early-pregnancy BP trajectories, with effect modification by HDP. RESULTS: BP trajectories were associated with an increasing gradient of hypertension risk after pregnancy within each HDP group. Adjusted hazard ratios were higher among preeclampsia and gestational hypertension groups than for no HDP. From lowest to highest BPT groups, hazard ratios ranged from 2.91 to 27.31 for preeclampsia, 4.20 to 27.81 for gestational hypertension, and 2.92 to 10.96 for no HDP compared with lowest BP trajectories of the no HDP group (all reference 1.0). CONCLUSIONS: Early-pregnancy BP trajectories are strongly associated with new-onset hypertension years after pregnancy. Combined with HDP, they may stratify risk for targeted surveillance and early interventions and improve the prediction of cardiovascular disease risk in women.