{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T21:32:21Z","timestamp":1790112741621,"version":"4.0.1"},"reference-count":53,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"15","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Clinical risk factors, a single blood pressure (BP) measurement, current biomarkers, and biophysical parameters can effectively identify risk of early\u2010onset preeclampsia but have limited ability to predict later\u2010onset preeclampsia and gestational hypertension. Clinical BP patterns hold promise to improve early risk stratification for hypertensive disorders of pregnancy.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">\n              After excluding preexisting hypertension, heart, kidney, or liver disease, or prior preeclampsia, the retrospective cohort (n=249\u2009892) all had systolic BP &lt;140\u2009mm Hg and diastolic BP &lt;90\u2009mm\u2009Hg or a single BP elevation \u226420\u2009weeks' gestation, prenatal care at &lt;14\u2009weeks' gestation, and a still or live birth delivery at Kaiser Permanente Northern California hospitals (2009\u20132019). The sample was randomly split into development (N=174\u2009925; 70%) and validation (n=74\u2009967; 30%) data sets. Predictive performance of multinomial logistic regression models for early\u2010onset (&lt;34\u2009weeks) preeclampsia, later\u2010onset (\u226534\u2009weeks) preeclampsia, and gestational hypertension was evaluated in the validation data set. There were 1008 (0.4%), 10\u2009766 (4.3%), and 11\u2009514 (4.6%) patients with early\u2010onset preeclampsia, later\u2010onset preeclampsia, and gestation hypertension, respectively. Models with 6 systolic BP trajectory groups (0\u201320\u2009weeks' gestation) plus standard clinical risk factors performed substantially better than risk factors alone to predict early\u2010 and later\u2010onset preeclampsia and gestational hypertension, with C\u2010statistics (95% CIs) of 0.747 (0.720\u20130.775), 0.730 (0.722\u20130.739), and 0.768 (0.761\u20130.776) versus 0.688 (0.659\u20130.717), 0.695 (0.686\u20130.704) and 0.692 (0.683\u20130.701), respectively, with excellent calibration (Hosmer\u2010Lemeshow\n              <jats:italic>P<\/jats:italic>\n              =0.99, 0.99, and 0.74, respectively).\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">Early pregnancy BP patterns up to 20\u2009weeks' gestation plus clinical, social, and behavioral factors more accurately discriminate hypertensive disorders of pregnancy risk among low\u2010to\u2010moderate risk pregnancies. Early pregnancy BP trajectories improve risk stratification to reveal higher\u2010risk individuals hidden within ostensibly low\u2010to\u2010moderate risk groups and lower\u2010risk individuals considered at higher risk by US Preventive Services Task Force criteria.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.123.029617","type":"journal-article","created":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T09:35:16Z","timestamp":1689154516000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":25,"title":["Early Pregnancy Systolic Blood Pressure Patterns Predict Early\u2010 and Later\u2010Onset Preeclampsia and Gestational Hypertension Among Ostensibly Low\u2010to\u2010Moderate Risk Groups"],"prefix":"10.1161","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2039-1964","authenticated-orcid":false,"given":"Erica P.","family":"Gunderson","sequence":"first","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California Oakland CA USA"},{"name":"Department of Health Systems Science, Kaiser Permanente Bernard J. 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Tyson School of Medicine Pasadena CA USA"},{"name":"Departments of Epidemiology, Biostatistics and Medicine University of California, San Francisco San Francisco CA USA"},{"name":"Department of Medicine Stanford University Palo Alto CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2671-3207","authenticated-orcid":false,"given":"James M.","family":"Roberts","sequence":"additional","affiliation":[{"name":"Magee\u2010Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, Epidemiology and Clinical and Translational Research University of Pittsburgh Pittsburgh, PA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8228-0282","authenticated-orcid":false,"given":"Mai N.","family":"Nguyen\u2010Huynh","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California Oakland CA USA"},{"name":"Department of Neurology, 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