CC BY NC NDWessel GanzevoortPeter von DadelszenJ. Johanna SanchezEileen K. HuttonJennifer MenziesJoel SingerSue RossElizabeth AsztalosEvelyne ReyJim G ThorntonLaura A. MageeKellie E. MurphyMichael HelewaJean Marie MoutquinRoss WelchShoo K. LeeAndrée GruslinElizabeth AsztalosAlexander G. LoganAmiram GafniKellie E. MurphyTerry Lee2025-06-172025-06-172016-04-070001-63491600-041210.1111/aogs.12877https://trapdev.rcub.bg.ac.rs/handle/123456789/767375<jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>For women with chronic or gestational hypertension in <jats:styled-content style="fixed-case">CHIPS</jats:styled-content> (Control of Hypertension In Pregnancy Study, NCT01192412), we aimed to examine whether clinical predictors collected at randomization could predict adverse outcomes.</jats:p></jats:sec><jats:sec><jats:title>Material and methods</jats:title><jats:p>This was a planned, secondary analysis of data from the 987 women in the <jats:styled-content style="fixed-case">CHIPS</jats:styled-content> Trial. Logistic regression was used to examine the impact of 19 candidate predictors on the probability of adverse perinatal (pregnancy loss or high level neonatal care for &gt;48 h, or birthweight &lt;10th percentile) or maternal outcomes (severe hypertension, preeclampsia, or delivery at &lt;34 or &lt;37 weeks). A model containing all candidate predictors was used to start the stepwise regression process based on goodness of fit as measured by the Akaike information criterion. For face validity, these variables were forced into the model: treatment group (“less tight” or “tight” control), antihypertensive type at randomization, and blood pressure within 1 week before randomization. Continuous variables were represented continuously or dichotomized based on the smaller <jats:italic>p</jats:italic>‐value in univariate analyses. An area‐under‐the‐receiver‐operating‐curve (<jats:styled-content style="fixed-case">AUC ROC</jats:styled-content>) of ≥0.70 was taken to reflect a potentially useful model.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Point estimates for <jats:styled-content style="fixed-case">AUC ROC</jats:styled-content> were &lt;0.70 for all but severe hypertension (0.70, 95% CI 0.67–0.74) and delivery at &lt;34 weeks (0.71, 95% CI 0.66–0.75). Therefore, no model warranted further assessment of performance.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p><jats:styled-content style="fixed-case">CHIPS</jats:styled-content> data suggest that when women with chronic hypertension develop an elevated blood pressure in pregnancy, or formerly normotensive women develop new gestational hypertension, maternal and current pregnancy clinical characteristics cannot predict adverse outcomes in the index pregnancy.</jats:p></jats:sec>OPENAdultadverse outcomePreexisting hypertension610Blood Pressure2729 Obstetrics and Gynaecology618Predictive Value of TestsPregnancyPrenatal Diagnosisgestational hypertensionHumanschronic hypertensionperinatalRandomized Controlled Trials as TopicBritish ColumbiaPreexisting hypertension, chronic hypertension, gestational hypertension, prediction, adverse outcome, maternal, perinatalPatient SelectionPregnancy OutcomepredictionHypertension, Pregnancy-InducedmaternalArea Under CurveRegression AnalysisFemaleCan adverse maternal and perinatal outcomes be predicted when blood pressure becomes elevated? Secondary analyses from the <scp>CHIPS</scp> (Control of Hypertension In Pregnancy Study) randomized controlled trialpublication03 medical and health sciences0302 clinical medicine3. Good healthdoi_dedup___:7dd1a54ea960b0b9a89d65be0f6ade62PMC502120426915709