Development and validation of a prediction model for gestational hypertension in a Ghanaian cohort.

Abstract

To develop and validate a prediction model for identifying women at increased risk of developing gestational hypertension (GH) in Ghana. A prospective study. We used frequencies for descriptive analysis, χ² test for associations and logistic regression to derive the prediction model. Discrimination was estimated by the c-statistic. Calibration was assessed by calibration plot of actual versus predicted probability. Primary care antenatal clinics in Ghana. 2529 pregnant women in the development cohort and 647 pregnant women in the validation cohort. Inclusion criterion was women without chronic hypertension. Gestational hypertension. Predictors of GH were diastolic blood pressure, family history of hypertension in parents, history of GH in a previous pregnancy, parity, height and weight. The c-statistic of the original model was 0.70 (95% CI 0.67-0.74) and 0.68 (0.60 to 0.77) in the validation cohort. Calibration was good in both cohorts. The negative predictive value of women in the development cohort at high risk of GH was 92.0% compared to 94.0% in the validation cohort. The prediction model showed adequate performance after validation in an independent cohort and can be used to classify women into high, moderate or low risk of developing GH. It contributes to efforts to provide clinical decision-making support to improve maternal health and birth outcomes.