Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT04058405 |
Other study ID # |
MpiloCH |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
November 12, 2018 |
Est. completion date |
August 31, 2021 |
Study information
Verified date |
September 2021 |
Source |
Mpilo Central Hospital |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
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.
Description:
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.