Placental biophysical model for prediction of early onset fetal growth restriction in first and second trimester of pregnancy: A prospective cohort study.

INTRODUCTION: To assess the placental biometry, placental biomarkers and uterine artery Doppler in each trimester of pregnancy for prediction of early-onset fetal growth restriction (EO FGR). METHODS: In this prospective cohort study placental biometry; biomarkers PAPP-A, sFLT-1, and PlGF along with the uterine artery blood flow evaluation was done serially at 11-14, 20-24 and 28-32 weeks of gestation. The above parameters were compared between women with early onset FGR and controls. RESULTS: Out of 1008 fully followed cases, the small for gestational age fetuses were 227/1008 (22.5 %), and EO FGR were 84/1008(8.3 %).The placental length, volume, and PlGF levels were significantly lower, whereas the uterine artery PI(Ut PI) was significantly higher at all time points among cases. The sFLT-1 level showed a significant increase among cases, whereas it decreased among controls from the first to the second trimester. The detection rate using PV/UtA PI was 60 % in the first trimester and 66.7 % in the second trimester at 30 % FPR. CONCLUSION: The PV/Ut PI in first and the second trimester was a good marker for the prediction of pregnancies at increased risk of developing EO FGR.

Materno-fetal outcome with PlGF above or below cutoff during second half of pregnancy in high-risk women.

OBJECTIVE: To evaluate the materno-fetal outcome of high-risk women using placental growth factor (PlGF). METHODS: This prospective cohort study was performed at a tertiary care hospital from September 2019 to April 2022. Women having clinically major or minor high risk factors of pre-eclampsia were included after consent. The placental growth factor (PlGF) was evaluated among high-risk women at 20-22, 28-30, and 34-36 weeks of gestation. They were followed throughout pregnancy until delivery. Materno-fetal outcome was evaluated based on PlGF levels at three different time points. The gestational age specific cutoff was derived. Those with levels below cutoff were taken as cases and those with values above cutoff were considered as controls. The odds of having complications if the PlGF was below cutoff were determined. RESULTS: Out of 287 high-risk women, 46 (16%) had pre-eclampsia (PE). The derived cutoff of PlGF was 224, 211, and 176 pg/mL at 20-22, 28-30, and 34-36 weeks, respectively. With PlGF below the cutoff at 20-22 weeks the odds of having HELLP syndrome was 15.8, with low PlGF at 28-30 weeks the odds for developing early onset PE was 11.3. Low PlGF was also significantly associated with preterm delivery (P < 0.001) and early onset FGR (P < 0.001). The sensitivity (91.7%) and specificity (78.5%) of PlGF for PE prediction was highest at 28-30 weeks. CONCLUSION: Low PlGF at 28-30 weeks was associated with high likelihood of developing early onset PE, and the PlGF cutoff should be gestational age specific.

Antenatal risk stratification for preeclampsia with sFlt-1/PlGF ratio: Which is the best time to test?

OBJECTIVE: To find out the predictive value of sFlt-1/PlGF ratio for antenatal risk stratification (ARS) of women at high risk of preeclampsia (PE). METHODS: Antenatal women at high risk of PE underwent sFlt-1/PlGF ratio at 20-22, 28-30 and 34-36 weeks and were followed till delivery. Those who developed PE were cases those who had normal outcome were controls, the cases and controls were compared. RESULTS: Hypertension in pregnancy was seen in 116/287 (40.4 %), 46/287(16.0 %) had PE and 21(7.3 %) had early onset PE. Mean arterial pressure at 20-22 weeks was the high in those who developed early onset PE (109.08 ± 9.74 mmHg). The sFlt-1/PlGF ratio of 38 or more at 20-22 weeks resulted in either PE or adverse fetal outcome in all cases. Whereas, the ratio of less than 38 ruled out PE in all cases up to 29 + 6 weeks. At 28-30 weeks, the ratio less than 38 predicted no PE up to 34 weeks and no complication up to 29+6 weeks. The sensitivity for the detection at later gestation further decreased as the gestation advanced however the specificity was above 98 % at all gestations. The positive predictive value of the test increased with the advancing gestation, the negative predictive value was 93 % or higher at all gestations. CONCLUSION: The usefulness of sFlt-1/PlGF ratio ≥38 for risk stratification was validated in the study, the testing at 28-30 weeks appeared to be the best time to test for PE prediction in high risk women.

Role of sFLT-1/PlGF ratio in predicting severe adverse materno-fetal outcome in high risk women.

OBJECTIVE: To evaluate the role of angiogenic biomarkers in predicting severe adverse materno-fetal outcome (SAO) among women at high risk of preeclampsia (PE). METHOD: All antenatal women at high risk of PE underwent MAP estimation, sFlt-1/PlGF ratio, uterine artery evaluation at 20-22, 28-30 and 34-36 weeks of gestation and were followed until delivery. The severe adverse outcome included severe PE, severe fetal growth restriction with Doppler changes and intrauterine death or early neonatal death. Those who developed SAO were cases and rest were controls, the cases and controls were compared using univariate and multivariate logistic regression analysis. RESULTS: In 54/287(18.8 %) SAO was observed, and they comprised of severe PE (21/287, 7.3 %), FGR with absent or reverse diastolic flow on Doppler (23/287, 8.0 %) and intrauterine death or early neonatal death (10/287, 3.5 %). For detecting complications up to 30 weeks, the sFLT-1/PlGF ratio at 20 weeks (cut off ≥ 38) was the best test (accuracy- 97.6 %) followed by MAP and uterine artery Doppler PI. For detecting complications up to 34 weeks, prediction was good (accuracy -80.4 %) when sFLT-1/PlGF ratio was combined with uterine artery PI. The predictive value of the complications before 34 weeks was far superior to that after 34 weeks. Combining the sFLT-1/PlGF ratio with the uterine artery PI improved the accuracy of the test (79 % to 87 %). CONCLUSION: Increased sFlt-1/PlGF ratio, was a good predictive marker for SAO in the study population. The accuracy of prediction was better for those who developed the complications before 34 weeks.

Ultrasound placental image texture analysis using artificial intelligence to predict hypertension in pregnancy.

BACKGROUND: The placental pathological changes in hypertensive disorders of pregnancy (HDP) starts early in pregnancy, the deep convolutional neural networks (CNN) can identify these changes before its clinical manifestation. OBJECTIVE: To compare the placental quantitative ultrasound image texture of women with HDP to those with the normal outcome. METHODS: The cases were enrolled in the first trimester of pregnancy, good quality images of the placenta were taken serially in the first, second, and third trimester of pregnancy. The women were followed till delivery, those with normal outcomes were controls, and those with HDP were cases. The images were processed and classified using validated deep learning tools. RESULTS: Total of 429 cases were fully followed till delivery, 58 of them had HDP (13.5%). In the first trimester, there was a significant difference in the placental length (p = .033), uterine artery PI (p = .019), biomarkers PAPP-A (p = .001) PlGF (p = .013) and placental image texture (p = .001) between the cases and controls. In the second trimester the uterine artery PI, serum PAPP-A (p = .010) and PlGF (p = .005) levels were significantly low among women who developed hypertension later on pregnancy. The image texture disparity between the two groups was highly significant (p < .001). The model "resnext 101_32x8d" had Cohen kappa score of 0.413 (moderate) and the accuracy score of 0.710 (good). In the first trimester the best sensitivity and specificity was observed for abnormal placental image texture (70.6% and 76.6%, respectively) followed by PlGF (64% and 50%, respectively), in the second trimester the abnormal image texture had the highest sensitivity and specificity (60.4% and 73.3%, respectively) followed by uterine artery PI (58.6% and 54.7%, respectively). Similarly in the third trimester, uterine artery PI had sensitivity and specificity of 60.3% and specificity of 50.7%, whereas the abnormal image texture had sensitivity and specificity of 83.5%. CONCLUSION: Ultrasound placental analysis using artificial intelligence (UPAAI) is a promising technique, would open avenues for more research in this field.

Prediction of hypertension in pregnancy in high risk women using maternal factors and serial placental profile in second and third trimester.

INTRODUCTION: To evaluate the role of placental profile markers in second and third trimester of pregnancy in predicting hypertensive disorders of pregnancy (HDP) in women at high risk of preeclampsia. METHOD: Women who were at high risk of preeclampsia underwent ßhCG, ultrasound assessment of placental length, thickness and its ratio, uterine artery Doppler at 20-24 weeks and 28-32 weeks of gestation, the outcome at delivery was noted. Those who developed HDP were cases and those with normal outcome were controls. The placental profile markers among cases and controls were compared. RESULTS: Hypertensive disorders of pregnancy was seen in 72/160 (45%) high risk women The serum ß hCG levels at 20-24 weeks (p = 0.001) and 28-32 weeks (p = 0.018) was significantly high in women who had preeclampsia. Placental thickness was found to be less in among all subgroups of HDP, for preeclampsia, it was significantly low at 20-24 weeks (AUC- 0.743; sensitivity- 75%, specificity- 66.3%) and 28 weeks (AUC -0.764, sensitivity - 75.0% specificity - 78.7%). Uterine artery S/D ratio was considerable high in women with chronic hypertension (AUC -0.765), gestational hypertension (AUC -0.771) and preeclampsia (AUC -0.726) at 20-24 weeks. In preeclampsia group, uterine artery PI was highest and the best marker at 20-24 weeks (AUC -0.935, sensitivity - 100.0%, specificity - 87.6%). DISCUSSION: The placental profile markers may be used to provide closer follow up in high risk pregnancies with abnormal placental profile levels, while less intense follow up in those with normal levels, thus channelizing the resources.