Placental Growth Factor as a Predictor of Adverse Pregnancy Outcomes in Preeclamptic Women

INTRODUCTION Despite advances in care, preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality worldwide and its syndromic nature makes diagnosis and management difficult.1 Preeclampsia (PE) is a pregnancy-specific syndrome, defined by new onset hypertension and proteinuria after 20 weeks of gestation.2 It complicates 2-8% of pregnancies and accounts for more than 50,000 maternal death annually.2,3 In developing countries, where lack of access to appropriate maternal care is a major problem, maternal death rates are as high as 15% as compared with 0% to 1.8% in industrialized countries.1 A 10-year review of maternal mortality in Ebonyi state University Teaching Hospital showed that PE and eclampsia accounted for 6.1% of maternal death.4 Preeclampsia affects multiple organ systems and can lead to severe maternal and fetal complications.5-10 Maternal and perinatal morbidity and mortality resulting from PE are due to its complications.6-8 Maternal complications include eclampsia, cerebrovascular accident, placental abruption, disseminated intravascular coagulation, hemolysis, elevated liver enzymes, low platelets (HELLP) syndrome, liver hemorrhage or rupture, pulmonary edema, adult respiratory distress syndrome, acute renal failure, and death. Perinatal consequences include stillbirth, preterm delivery, fetal growth restriction (FGR), and neonatal death.5-10 The only curative treatment for PE is delivery of the placenta.9-13 The challenge in caring for women with PE is to identify those who are at increased risk of complications so that appropriate and timely delivery can be offered.14 Most of the symptoms associated with PE are common and nonspecific, which can lead to poor predictability of adverse outcomes.15 Moreover, the capacity to predict adverse maternal and perinatal outcomes remains poor.15 Recognition of those patients at risk of adverse outcomes related to PE can reduce or avert maternal and perinatal morbidity and mortality associated with the condition.16 Currently available biochemical makers such as proteinuria and uric acid have been shown to be poor predictors of adverse pregnancy outcomes in preeclamptic women.16-20 This suggests that a clinical diagnostic test able to predict maternal and fetal risk could be useful. Among biochemical markers, attention has recently focused on angiogenic factors, such as PlGF. Placental growth factor is an angiogenic growth factor related to vascular endothelial growth factor that is exclusively produced by the trophoblast.18 A growing body of evidence suggests that an imbalance of angiogenic/anti-angiogenic factors are involved in the pathophysiology of PE.18 Studies on the pathogenesis of PE support the hypothesis of a pathogenetic model of defective placentation resulting from reduced concentrations of angiogenic growth factors (free PlGF) and increased concentrations of anti-angiogenic factors such as soluble Fms-like tyrosine kinase-1 (sFlt-1).16-24 The majority of studies of PlGF testing have focused on either prediction of PE or confirmation of the diagnosis once PE is suspected. Even though this biomarker has excellent predictive value for PE, a major issue is that there is no clear intervention that can prevent the subsequent development of the disease. Several preventive measures such as supplementation with vitamin C and vitamin E, aspirin, or calcium fail to consistently prevent subsequent development of PE.19 Thus, the value remains either a "research procedure" or a method of risk assessment to identify patients who may benefit from more intensive surveillance. Currently studies are focused on evaluating the role of plasma angiogenic and anti-angiogenic factors in predicting the outcome of patients with PE. Studies have shown a positive correlation between low maternal serum PlGF levels and adverse maternal and fetal outcomes.21 These findings have led to speculation that PlGF might be useful in both the prediction of PE and prognosis with respect to the occurrence of related adverse outcomes. Considering the contribution of PE to maternal morbidity and mortality in Abakaliki and poor predictive accuracy of available biochemical markers on adverse pregnancy outcomes and the search for better predictive maker of adverse outcomes among preeclamptic women, a study on PlGF as a predictor of outcomes among preeclamptic women in Abakaliki is important. 1.1 JUSTIFICATION FOR THE STUDY Preeclampsia has remained among the leading causes of maternal morbidity and mortality worldwide.22 Maternal deaths resulting from PE are due to complications associated with the condition.20-25 Clinical prediction of disease complications may facilitate initiation of timely management to prevent morbidity and mortality in the mother and baby. The studies on current predictive biomarkers (proteinuria or uric acid) of adverse outcomes among preeclamptic women have shown poor predictive results.24 Hence there is a need for identification of highly specific and sensitive biomarkers that would allow early identification of patients at risk and for prediction of adverse outcomes for women who developed the condition and thus help in providing proper prenatal care. Placental growth factor appears to be a promising tool in this regard. Literature search showed that this study has not been done in Abakaliki. Hence, the outcome of this study will help to make evidence based recommendations on the role of maternal serum level of PlGF in the management of preeclamptic women in Abakaliki. 3.0 AIM AND OBJECTIVES AND RESEARCH QUESTION 3.1 AIM The aim of the study is to test the predictive accuracy of maternal free PlGF concentration for pregnancy adverse outcomes in patients with preeclampsia based on a single assay at the time of admission. 3.2 SPECIFIC OBJECTIVES To compare the mean serum level of PlGF among preeclamptic women with and without adverse pregnancy outcomes. To evaluate the relationship between the level of PlGF and adverse maternal outcomes. To determine the association between serum PlGF level and adverse perinatal outcomes. To estimate the cut off value of PlGF associated with adverse pregnancy outcomes. To determine the sensitivity and specificity of cut off value of PlGF associated with adverse pregnancy outcomes. 3.3 RESEARCH QUESTION Is maternal PlGF level predictive of adverse pregnancy outcomes in preeclamptic women in the Federal Teaching Hospital and Saint Patrick Mile 4 Hospital Abakaliki? 3.4 NULL HYPOTHESIS There is no association between maternal serum PlGF concentration and adverse pregnancy outcomes in preeclamptic women 3.5 ALTERNATE HYPOTHESIS There is an association between maternal PlGF level and adverse pregnancy outcomes in preeclamptic women. 4.0 METHODOLOGY 4.1 STUDY AREA This study will be done at the antenatal ward, labour ward, postnatal ward and neonatal intensive care unit department of the Federal Teaching Hospital, Abakaliki, Ebonyi State. Federal Teaching Hospital, Abakaliki is a federal tertiary health care institution located at the state capital. It is a product of a merger of the former Federal Medical Centre, Abakaliki and the then Ebonyi State University Teaching Hospital by the Federal Government of Nigeria in 2011. The department of Obstetrics and Gynaecology of the hospital maintains gynaecological emergency, antenatal clinic, antenatal ward, labour ward, theatre complex and postnatal ward for both booked and unbooked patients. These are managed by Consultants and Resident Doctors with trained Nurses and Midwives. There are 25 Consultants manning 5 units in the department with an average of 5 Consultants per unit. The units run the antenatal and gynaecological clinics on each of the working days of the week. In 2017, three thousand and two hundred deliveries were taken and there were 204 cases of preeclampsia. The maternal mortality ratio in a 10 year review of maternal death in the hospital was 1, 359 per 100,000 live births.4 Ebonyi State is one of the five states in the Southeast geopolitical zone of Nigeria created in 1996 from the old Abakaliki division of Enugu State and old Afikpo division of former Abia State. It has 13 local government areas with an estimated population of about 4.3 million, with a land mass of approximately 5, 932 sq km.33 The state is bordered in the north by Benue State, east by the Cross river Sate; south by Abia State and West by Enugu state. 4.2 SAMPLING METHOD Total sampling method will be used for the study. All women diagnosed with preeclampsia on admission who meet the inclusion criteria and give informed consent will be recruited for the study. The study participants will be followed up until hospital discharge after delivery. 4.3 DIAGNOSIS OF PREECLAMPSIA Measurement of blood pressure: Upper arm blood pressure will be measured by the researcher or research assistant using the Mercury Sphygmomanometer (ELKO B.P APPARATUS) after the study participant has rested for 5 minutes. All of the participants will be seated on a chair in an upright position with back support. A cuff will be placed around the non-dominant upper arm, which will be supported at the level of the heart; with the bladder of the cuff in the midline over the brachial artery pulsation. The systolic and diastolic blood pressures will be determined by Korokoff I and V respectively. Preeclampsia will be defined as hypertension (systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg on ≥ 2 recordings taken ≥ 4 hours apart after 20 weeks' gestation or a single measurement of systolic blood pressure of 160 mmHg and/or diastolic blood pressure of 110 mmHg with proteinuria (≥ 2+ by dipstick). 4.4 SAMPLE SIZE ESTIMATION The sample size calculation was based on the formula N=Z\^2 x SD\^2/d\^2 Z1-α = Standard normal variate at 5% type 1 error (P\<0.05) is 1.96 SD = Standard deviation of variable based on previous studies (The SD of PlGF value which preeclamptic women were predicted to developed adverse pregnancy outcomes was 0.56. Note: 0.56 was derived by getting the average SD of PlGF for developing adverse pregnancy outcomes from two previous studies ).25,26 d = Absolute error or precision (set at 10%) Therefore, N= 120.5 Adding 10% attrition rate which is approximately 12. Therefore the sample size is 140. 4.5 SPECIMEN COLLECTION AND TRANSPORT On admission women who give consent for the study will have their urine and blood samples taken. Bed side urinalysis to know the degree of proteinuria will be carried out by the researcher or research assistants using True-Screen Combi 11 reagent strips (Lifesane Biotech, USA). The blood sample will be taken and transferred to a universal specimen bottle and the specimen taken to the hospital laboratory for analysis. 4.6 SPECIMEN PROCESSING, STORAGE AND ANALYSIS At laboratory processing of the specimen will be carried out by three medical laboratory scientists and the researcher. Assay will be performed as soon as 40 samples are ready. Estimation of free PlGF levels will be done by ELISA technique using the Human PlGF ELISA kit (Roche Diagnostics, Germany). The result of the test will be reported in pg/ml. 4.7 QUALITY CONTROL Three medical laboratory scientists will be involved in the sample analysis with the aid of the researcher under the supervision of a chemical pathologist. Three laboratory scientists will be dedicated to sample analysis while the chemical pathologist will occasionally test random samples to ensure that the results are corresponding with results of the test samples from the other three. 4.8 RESEARCH ASSISTANTS Research assistants comprise the 2 residents and 5 house officers from each team and each assigned a specific role to play during the study period. There will be three training sessions for the assistants during which the details of the study with the role of each assistant will be explained. Retraining sessions may be done in the course of the study if deemed necessary. Whatsapp chat group will be created for easy communication. 4.9 DATA COLLECTION METHOD The data would be collected using a proforma that has four parts which include the socio-demographic characteristics of the study participants, Blood pressure, Urinalysis result, adverse maternal and perinatal outcomes and PlGF level. After delivery, data proforma sheets will be completed for all participants before entering the information into a database. 4.10 STATISTICAL ANALYSIS The data analysis will be performed using the SPSS version 22.0 program for Windows (IBM Corp. Amork, New York, U.S.A). Categorical variables would be presented as frequencies and percentages while continuous variables would be presented as mean ± standard deviation. The mean PlGF values of women with and without adverse outcomes will be compared using the Student's t-test. To determine the best cut off value of PlGF (designated as X) for the prediction of adverse outcomes, the receiver operating characteristic (ROC) curve analysis would be used and areas under the curve (AUC) calculated. Logistic regression would be used to determine the association between the cut off value of PlGF and each of the composite maternal and perinatal adverse outcomes. Multivariable logistic regression would be constructed to account for potentially confounding factors selected based on clinical information (maternal age, gestational age at presentation, parity and mode of delivery). The sensitivity and specificity would be determined for the cut point cited above. A p value \<0.05 would be considered statistically significant. 4.11.0 ETHICAL CONSIDERATION 4.11.1 ETHICAL APPROVAL Ethical approval for the study has been sought for and obtained from the hospital Research Ethics Committee with approval number FETHA/REC/VOL2/2018/041. Informed consent will be obtained from each study participants. 4.12 SOURCE OF FUNDING There is no source of funding for this study. The researchers will bear the cost of the study. 4.13 STRENGTH AND LIMITATION OF THE STUDY The strength of the study is that a single biomaker, PlGF, would be assayed and the test would be performed once, which is cost-saving. The limitation of this study is that long term follow up of participants will not be carried out and adverse outcomes that will occur following hospital discharge will not be assessed. In addition, reliable results are obtained when the assay procedure is performed with a complete adherence to good laboratory practice and this will be ensured by quality control that will be put in place in course of the study.