Can adverse maternal and perinatal outcomes be predicted when blood pressure becomes elevated? Secondary analyses from the CHIPS (Control of Hypertension In Pregnancy Study) randomized controlled trial

Laura A Magee; Peter von Dadelszen; Joel Singer; Terry Lee; Evelyne Rey; Susan Ross; Elizabeth Asztalos; Kellie E Murphy; Jennifer Menzies; Johanna Sanchez; Amiram Gafni; Andrée Gruslin; Michael Helewa; Eileen Hutton; Shoo K Lee; Alexander G Logan; Wessel Ganzevoort; Ross Welch; Jim G Thornton; Jean Marie Moutquin

doi:10.1111/aogs.12877

Can adverse maternal and perinatal outcomes be predicted when blood pressure becomes elevated? Secondary analyses from the CHIPS (Control of Hypertension In Pregnancy Study) randomized controlled trial

Acta Obstet Gynecol Scand. 2016 Jul;95(7):763-76. doi: 10.1111/aogs.12877. Epub 2016 Apr 7.

Authors

Laura A Magee^{1

2

3

4}, Peter von Dadelszen^{1

2

3

4}, Joel Singer^{3

5}, Terry Lee⁶, Evelyne Rey⁷, Susan Ross⁸, Elizabeth Asztalos^{9

10

11}, Kellie E Murphy^{10

11}, Jennifer Menzies³, Johanna Sanchez¹¹, Amiram Gafni¹², Andrée Gruslin¹³, Michael Helewa¹⁴, Eileen Hutton¹⁵, Shoo K Lee⁹, Alexander G Logan¹⁶, Wessel Ganzevoort¹⁷, Ross Welch¹⁸, Jim G Thornton¹⁹, Jean Marie Moutquin²⁰

Affiliations

¹ St. George's University of London, London, UK.
² St. George's University Hospitals NHS Trust, London, UK.
³ Obstetrics and Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada.
⁴ Child and Family Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.
⁵ School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
⁶ Centre for Health Evaluation and Outcome Sciences (CH_EOS), Providence Health Care Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.
⁷ Medicine and Obstetrics and Gynaecology, University of Montreal, Montreal, Quebec, Canada.
⁸ Obstetrics and Gynaecology, University of Alberta, Edmonton, Alberta, Canada.
⁹ Pediatrics, University of Toronto, Toronto, Ontario, Canada.
¹⁰ Obstetrics and Gynaecology, University of Toronto, Toronto, Ontario, Canada.
¹¹ The Centre for Mother, Infant and Child Research, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.
¹² Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
¹³ Obstetrics and Gynaecology, University of Ottawa, Ottawa, Ontario, Canada.
¹⁴ Obstetrics and Gynaecology, University of Manitoba, Winnipeg, Manitoba, Canada.
¹⁵ Obstetrics and Gynaecology, McMaster University, Hamilton, Ontario, Canada.
¹⁶ Medicine, University of Toronto, Toronto, Ontario, Canada.
¹⁷ Obstetrics and Gynaecology, University of Amsterdam, Amsterdam, the Netherlands.
¹⁸ Obstetrics and Gynaecology, Derriford Hospital, Plymouth, UK.
¹⁹ Obstetrics and Gynaecology, University of Nottingham, Nottingham, UK.
²⁰ Obstetrics and Gynaecology, Sherbrooke University, Sherbrooke, Quebec, Canada.

Abstract

Introduction: For women with chronic or gestational hypertension in CHIPS (Control of Hypertension In Pregnancy Study, NCT01192412), we aimed to examine whether clinical predictors collected at randomization could predict adverse outcomes.

Material and methods: This was a planned, secondary analysis of data from the 987 women in the CHIPS 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 >48 h, or birthweight <10th percentile) or maternal outcomes (severe hypertension, preeclampsia, or delivery at <34 or <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 p-value in univariate analyses. An area-under-the-receiver-operating-curve (AUC ROC) of ≥0.70 was taken to reflect a potentially useful model.

Results: Point estimates for AUC ROC were <0.70 for all but severe hypertension (0.70, 95% CI 0.67-0.74) and delivery at <34 weeks (0.71, 95% CI 0.66-0.75). Therefore, no model warranted further assessment of performance.

Conclusions: CHIPS 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.

Keywords: Preexisting hypertension; adverse outcome; chronic hypertension; gestational hypertension; maternal; perinatal; prediction.

Publication types

Evaluation Study

MeSH terms

Adult
Area Under Curve
Blood Pressure*
British Columbia
Female
Humans
Hypertension, Pregnancy-Induced / diagnosis*
Hypertension, Pregnancy-Induced / prevention & control
Patient Selection*
Predictive Value of Tests
Pregnancy
Pregnancy Outcome
Prenatal Diagnosis*
Randomized Controlled Trials as Topic
Regression Analysis