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Stillbirth remains a global public health issue; in low-resource settings stillbirth rates remain high (>12 per 1,000 births target of Every Newborn Action Plan). Preeclampsia is major risk factor for stillbirths. This study aimed to determine the prevalence and risk factors for stillbirth amongst women with severe preeclampsia at Mpilo Central Hospital. A retrospective cross-sectional study was conducted of women with severe preeclampsia from 01/01/2016 to 31/12/2018 at Mpilo Central Hospital, Bulawayo, Zimbabwe. Multivariable logistic regression was used to determine risk factors that were independently associated with stillbirths. Of 469 women that met the inclusion criteria, 46 had a stillbirth giving a stillbirth prevalence of 9.8%. The risk factors for stillbirths in women with severe preeclampsia were: unbooked status (adjusted odds ratio (aOR) 3.01, 95% (confidence interval) CI 2.20–9.10), frontal headaches (aOR 2.33, 95% CI 0.14–5.78), vaginal bleeding with abdominal pain (aOR 4.71, 95% CI 1.12–19.94), diastolic blood pressure ≥150 mmHg (aOR 15.04, 95% CI 1.78–126.79), platelet count 0–49 × 109/L (aOR 2.80, 95% CI 1.26–6.21), platelet count 50–99 × 109/L (aOR 2.48, 95% CI 0.99–6.18), antepartum haemorrhage (aOR 12.71, 95% CI 4.15–38.96), haemolysis elevated liver enzymes syndrome (HELLP) (aOR 6.02, 95% CI 2.22–16.33) and fetal sex (aOR 2.75, 95% CI 1.37–5.53). Women with severe preeclampsia are at significantly increased risk of stillbirth. This study has identified risk factors for stillbirth in this high-risk population; which we hope could be used by clinicians to reduce the burden of stillbirths in women with severe preeclampsia. [ABSTRACT FROM AUTHOR]

Objective: Globally, preeclampsia is a significant contributor to adverse maternal outcomes. Once women develop eclampsia, they face considerable risks especially in countries with limited resources to deal with such a life-threatening complication. This study was carried out to investigate determinants of eclampsia in pregnant mothers with severe preeclampsia.Study Design: This institutional based study was completed at Mpilo Central Hospital, a quaternary referral unit from 1st January 2016 - 31st December 2018. In this study, pregnant women with severe preeclampsia/eclampsia were the study participants. The independent variables included socio-demographic and clinical characteristics, and maternal outcomes. Multivariable logistic regression analyses were used to determine independent association with p < 0.05 taken as statistically significant with 95% Confidence Interval (CI).Main Outcome Measure: Eclampsia.Results: Development of eclampsia was more frequent in women aged 14-19 years compared to women aged ≥ 35 years (adjusted odds ratio (AOR) 6.64, 95% CI 1.20-22.06, p = 0.02) and in primiparous women compared to women with parity ≥ 3 (AOR 2.76, 95% CI 1.48-5.15, p = 0.001). Eclampsia was more frequent in women with diastolic blood pressure of 131-150 mmHg (AOR 5.48, 95% CI 1.05-28.75, p = 0.04), and ≥ 150 mmHg (AOR 5.78, 95% CI 1.05-31.78, p = 0.04) compared with those with diastolic blood pressure of ≤ 110 mmHg. Symptoms of visual disturbances were also associated with eclampsia (AOR 2.13, 95% CI 1.08-4.18, p = 0.03).Conclusions: This study has identified independent determinants of eclampsia which can be used to identify which women should receive magnesium sulphate prophlyaxis or more intensive monitoring to prevent deterioration in maternal condition. [ABSTRACT FROM AUTHOR]

Objectives: Hypertensive disorders of pregnancy are major causes of global maternal and neonatal morbidity and mortality. This study aimed to develop and validate models to predict composite adverse maternal and neonatal outcome in severe preeclampsia in low-resource settings.Study Design: A retrospective cross-sectional study of women with severe preeclampsia giving birth in a tertiary referral centre in Zimbabwe between 01/01/2014-31/12/2018. Candidate variables identified from univariable logistic regression (p < 0.2) were entered into stepwise backward elimination logistic regression models to predict composite adverse maternal and neonatal outcomes. Models' performance was assessed by the area under the curve of the receiver operator characteristic (AUC ROC). The models were validated internally using bootstrap-based methods and externally using the Preeclampsia Integrated Estimate of RiSk dataset.Main Outcome Measures: The co-primary outcomes were composite adverse maternal outcome and composite adverse neonatal outcome.Results: 549 women had severe preeclampsia from whom 567 neonates were born. The predictive model for composite adverse maternal outcome included maternal age, gestational age on admission, epigastric pain, vaginal bleeding with abdominal pain, haemoglobin concentration and platelets; the AUC ROC was 0.796 (95% CI 0.758-0.833). External validation showed poor discrimination (AUC ROC 0.494, 95% CI 0.458-0.552). The model for composite adverse neonatal outcome included: gestational age, platelets, alanine transaminase and birth weight; the AUC ROC was 0.902 (95% CI 0.876-0.927).Conclusions: While the models accurately predicted composite adverse maternal and neonatal outcomes in the study population, they did not in another cohort. Understanding factors which affect model performance will help optimize prediction of adverse outcomes in severe preeclampsia. [ABSTRACT FROM AUTHOR]

Objectives: In low resource settings symptoms and signs may be used to identify which women require intervention to mitigate the risks of severe preeclampsia. This study aimed to report the frequency of signs and symptoms in women with severe preeclampsia and to determine their predictive value for adverse maternal and perinatal outcomes.Study Design: A retrospective cross-sectional study of women with severe preeclampsia from 01/01/2016 to 31/12/2018 at Mpilo Central Hospital, Bulawayo, Zimbabwe. Multivariate logistic regression was used to determine whether symptoms and signs were independently associated with the co-primary outcomes.Main Outcome Measures: The co-primary outcome measures were a composite of maternal complications including major organ dysfunction or mortality and a composite measure of severe perinatal morbidity or mortality.Results: Symptoms were present in 58.8% of women with severe preeclampsia; headache and epigastric pain were most commonly reported (47.9% and 22.4% of women respectively). Most symptoms and signs were not independently predictive of adverse maternal or perinatal outcomes. Vaginal bleeding with abdominal pain reduced odds of adverse maternal outcome (Adjusted Odds Ratio (AOR) 0.16, 95% Confidence Interval (CI) 0.03-0.84; p = 0.03), systolic blood pressure of 161-180 mmHg increased odds of adverse maternal outcome (AOR 2.71, 95% CI 1.14-6.41, p = 0.03) and birthweight ≤ 1500 g increased odds of adverse perinatal outcome (AOR 23.21, 95% CI 7.70-69.92, p < 0.001).Conclusions: Maternal signs and symptoms are ineffective predictors of maternal or perinatal morbidity and mortality; as such they cannot be used alone to predict which women would benefit from intervention in severe preeclampsia. [ABSTRACT FROM AUTHOR]

Hypertensive disorders in pregnancy are a leading cause of maternal and perinatal morbidity and mortality, especially in low-resource settings. Identifying mothers and babies at greatest risk of complications would enable intervention to be targeted to those most likely to benefit from them. However, current risk prediction models have a wide range of sensitivity (42–81%) and specificity (87–92%) indicating that improvements are needed. Furthermore, no predictive models have been developed or evaluated in Zimbabwe. This proposal describes a single centre retrospective cross-sectional study which will address the need to further develop and test statistical risk prediction models for adverse maternal and neonatal outcomes in low-resource settings; this will be the first such research to be carried out in Zimbabwe. Data will be collected on maternal demographics characteristics, outcome of prior pregnancies, past medical history, symptoms and signs on admission, results of biochemical and haematological investigations. Adverse outcome will be defined as a composite of maternal morbidity and mortality and perinatal morbidity and mortality. Association between variables and outcomes will be explored using multivariable logistic regression. Critically, new risk prediction models introduced for our clinical setting may reduce avoidable maternal and neonatal morbidity and mortality at local, national, regional and international level. [ABSTRACT FROM AUTHOR]