dc.contributor.author Wessel Ganzevoort
dc.contributor.author Peter von Dadelszen
dc.contributor.author J. Johanna Sanchez
dc.contributor.author Eileen K. Hutton
dc.contributor.author Jennifer Menzies
dc.contributor.author Joel Singer
dc.contributor.author Sue Ross
dc.contributor.author Elizabeth Asztalos
dc.contributor.author Evelyne Rey
dc.contributor.author Jim G Thornton
dc.contributor.author Laura A. Magee
dc.contributor.author Kellie E. Murphy
dc.contributor.author Michael Helewa
dc.contributor.author Jean Marie Moutquin
dc.contributor.author Ross Welch
dc.contributor.author Shoo K. Lee
dc.contributor.author Andrée Gruslin
dc.contributor.author Elizabeth Asztalos
dc.contributor.author Alexander G. Logan
dc.contributor.author Amiram Gafni
dc.contributor.author Kellie E. Murphy
dc.contributor.author Terry Lee
dc.date.accessioned 2025-06-17T14:17:56Z
dc.date.available 2025-06-17T14:17:56Z
dc.date.issued 2016-04-07
dc.description.abstract <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>
dc.description.epage 776
dc.description.spage 763
dc.description.volume 95
dc.identifier.doi 10.1111/aogs.12877
dc.identifier.issn 0001-6349
dc.identifier.issn 1600-0412
dc.identifier.openaire doi_dedup___:7dd1a54ea960b0b9a89d65be0f6ade62
dc.identifier.pmc PMC5021204
dc.identifier.pmid 26915709
dc.identifier.uri https://trapdev.rcub.bg.ac.rs/handle/123456789/767375
dc.openaire.affiliation King's College London
dc.openaire.collaboration 1
dc.publisher Wiley
dc.rights OPEN
dc.rights.license CC BY NC ND
dc.source Acta Obstetricia et Gynecologica Scandinavica
dc.subject Adult
dc.subject adverse outcome
dc.subject Preexisting hypertension
dc.subject 610
dc.subject Blood Pressure
dc.subject 2729 Obstetrics and Gynaecology
dc.subject 618
dc.subject Predictive Value of Tests
dc.subject Pregnancy
dc.subject Prenatal Diagnosis
dc.subject gestational hypertension
dc.subject Humans
dc.subject chronic hypertension
dc.subject perinatal
dc.subject Randomized Controlled Trials as Topic
dc.subject British Columbia
dc.subject Preexisting hypertension, chronic hypertension, gestational hypertension, prediction, adverse outcome, maternal, perinatal
dc.subject Patient Selection
dc.subject Pregnancy Outcome
dc.subject prediction
dc.subject Hypertension, Pregnancy-Induced
dc.subject maternal
dc.subject Area Under Curve
dc.subject Regression Analysis
dc.subject Female
dc.subject.fos 03 medical and health sciences
dc.subject.fos 0302 clinical medicine
dc.subject.sdg 3. Good health
dc.title Can 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 trial
dc.type publication

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