Maternal vascular indices at 36 weeks' gestation in the prediction of preeclampsia.

BACKGROUND: Epidemiological studies have shown that women with preeclampsia (PE) are at increased long term cardiovascular risk. This risk might be associated with accelerated vascular ageing process but data on vascular abnormalities in women with PE are scarce. OBJECTIVE: This study aimed to identify the most discriminatory maternal vascular index in the prediction of PE at 35 to 37 weeks' gestation and to examine the performance of screening for PE by combinations of maternal risk factors and biophysical and biochemical markers at 35 to 37 weeks' gestation. STUDY DESIGN: This was a prospective observational nonintervention study in women attending a routine hospital visit at 35 0/7 to 36 6/7 weeks' gestation. The visit included recording of maternal demographic characteristics and medical history, vascular indices, and hemodynamic parameters obtained by a noninvasive operator-independent device (pulse wave velocity, augmentation index, cardiac output, stroke volume, central systolic and diastolic blood pressures, total peripheral resistance, and fetal heart rate), mean arterial pressure, uterine artery pulsatility index, and serum concentration of placental growth factor and soluble fms-like tyrosine kinase-1. The performance of screening for delivery with PE at any time and at <3 weeks from assessment using a combination of maternal risk factors and various combinations of biomarkers was determined. RESULTS: The study population consisted of 6746 women with singleton pregnancies, including 176 women (2.6%) who subsequently developed PE. There were 3 main findings. First, in women who developed PE, compared with those who did not, there were higher central systolic and diastolic blood pressures, pulse wave velocity, peripheral vascular resistance, and augmentation index. Second, the most discriminatory indices were systolic and diastolic blood pressures and pulse wave velocity, with poor prediction from the other indices. However, the performance of screening by a combination of maternal risk factors plus mean arterial pressure was at least as high as that of a combination of maternal risk factors plus central systolic and diastolic blood pressures; consequently, in screening for PE, pulse wave velocity, mean arterial pressure, uterine artery pulsatility index, placental growth factor, and soluble fms-like tyrosine kinase-1 were used. Third, in screening for both PE within 3 weeks and PE at any time from assessment, the detection rate at a false-positive rate of 10% of a biophysical test consisting of maternal risk factors plus mean arterial pressure, uterine artery pulsatility index, and pulse wave velocity (PE within 3 weeks: 85.2%; 95% confidence interval, 75.6%-92.1%; PE at any time: 69.9%; 95% confidence interval, 62.5%-76.6%) was not significantly different from a biochemical test using the competing risks model to combine maternal risk factors with placental growth factor and soluble fms-like tyrosine kinase-1 (PE within 3 weeks: 80.2%; 95% confidence interval, 69.9%-88.3%; PE at any time: 64.2%; 95% confidence interval, 56.6%-71.3%), and they were both superior to screening by low placental growth factor concentration (PE within 3 weeks: 53.1%; 95% confidence interval, 41.7%-64.3%; PE at any time: 44.3; 95% confidence interval, 36.8%-52.0%) or high soluble fms-like tyrosine kinase-1-to-placental growth factor concentration ratio (PE within 3 weeks: 65.4%; 95% confidence interval, 54.0%-75.7%; PE at any time: 53.4%; 95% confidence interval, 45.8%-60.9%). CONCLUSION: First, increased maternal arterial stiffness preceded the clinical onset of PE. Second, maternal pulse wave velocity at 35 to 37 weeks' gestation in combination with mean arterial pressure and uterine artery pulsatility index provided effective prediction of subsequent development of preeclampsia.

Ophthalmic artery Doppler at 36 weeks' gestation in prediction of pre-eclampsia: validation and update of previous model.

OBJECTIVE: To validate and extend a model incorporating maternal ophthalmic artery Doppler at 35-37 weeks' gestation in the prediction of subsequent development of pre-eclampsia (PE). METHODS: This was a prospective validation study of screening for PE (defined according to the 2019 American College of Obstetricians and Gynecologists criteria) by maternal ophthalmic artery peak systolic velocity (PSV) ratio in 6746 singleton pregnancies undergoing routine care at 35 + 0 to 36 + 6 weeks' gestation (validation dataset). Additionally, the data from the validation dataset were combined with those of 2287 pregnancies that were previously used for development of the model (training dataset), and the combined data were used to update the original model parameters. The competing-risks model was used to estimate the individual patient-specific risk of delivery with PE at any time and within 3 weeks from assessment by a combination of maternal demographic characteristics and medical history with PSV ratio alone and in combination with the established PE biomarkers of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum soluble fms-like tyrosine kinase-1 (sFlt-1). We evaluated the predictive performance of the model by examining, first, the ability to discriminate between the PE and non-PE groups using the area under the receiver-operating-characteristics curve and the detection rate (DR) at fixed screen-positive (SPR) and false-positive rates of 10% and, second, calibration by measuring the calibration slope and calibration-in-the-large. McNemar's test was used to compare the performance of screening by a biophysical test (maternal factors, MAP, UtA-PI and PSV ratio) vs a biochemical test (maternal factors, PlGF and sFlt-1), low PlGF concentration (< 10th percentile) or high sFlt-1/PlGF concentration ratio (> 90th percentile). RESULTS: In the validation dataset, the performance of screening by maternal factors and PSV ratio for delivery with PE within 3 weeks and at any time after assessment was consistent with that in the training dataset, and there was good agreement between the predicted and observed incidence of PE. In the combined data from the training and validation datasets, good prediction for PE was achieved in screening by a combination of maternal factors, MAP, UtA-PI, PlGF, sFlt-1 and PSV ratio, with a DR, at a 10% SPR, of 85.0% (95% CI, 76.5-91.4%) for delivery with PE within 3 weeks and 65.7% (95% CI, 59.2-71.7%) for delivery with PE at any time after assessment. The performance of a biophysical test was superior to that of screening by low PlGF concentration or high sFlt-1/PlGF concentration ratio but not significantly different from the performance of a biochemical test combining maternal factors with PlGF and sFlt-1 for both PE within 3 weeks and PE at any time after assessment. CONCLUSION: Maternal ophthalmic artery PSV ratio at 35-37 weeks' gestation in combination with other biomarkers provides effective prediction of subsequent development of PE. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

STATIN trial: predictive performance of competing-risks model in screening for pre-eclampsia at 35-37 weeks' gestation.

OBJECTIVE: To examine the predictive performance of a previously reported competing-risks model of screening for pre-eclampsia (PE) at 35-37 weeks' gestation by combinations of maternal risk factors, mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum soluble fms-like tyrosine kinase-1 (sFlt-1) in a validation dataset derived from the screened population of the STATIN study. METHODS: This was a prospective third-trimester multicenter study of screening for PE in singleton pregnancies by means of a previously reported algorithm that combines maternal risk factors and biomarkers. Women in the high-risk group were invited to participate in a trial of pravastatin vs placebo, but the trial showed no evidence of an effect of pravastatin in the prevention of PE. Patient-specific risks of delivery with PE were calculated using the competing-risks model, and the performance of screening for PE by maternal risk factors alone and by various combinations of risk factors with MAP, UtA-PI, PlGF and sFlt-1 was assessed. The predictive performance of the model was examined by, first, the ability of the model to discriminate between the PE and no-PE groups using the area under the receiver-operating-characteristics curve (AUC) and the detection rate at a fixed false-positive rate of 10%, and, second, calibration by measurements of calibration slope and calibration-in-the-large. RESULTS: The study population of 29 677 pregnancies contained 653 that developed PE. In screening for PE by a combination of maternal risk factors, MAP, PlGF and sFlt-1 (triple test), the detection rate at a 10% false-positive rate was 79% (95% CI, 76-82%) and the results were consistent with the data used for developing the algorithm. Addition of UtA-PI did not improve the prediction provided by the triple test. The AUC for the triple test was 0.923 (95% CI, 0.913-0.932), demonstrating very high discrimination between affected and unaffected pregnancies. Similarly, the calibration slope was 0.875 (95% CI, 0.831-0.919), demonstrating good agreement between the predicted risk and observed incidence of PE. CONCLUSION: The competing-risks model provides an effective and reproducible method for third-trimester prediction of term PE. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Prediction of pre-eclampsia in twin pregnancy by maternal factors and biomarkers at 11-13 weeks' gestation: data from EVENTS trial.

OBJECTIVES: First, to validate a previously developed model for screening for pre-eclampsia (PE) by maternal characteristics and medical history in twin pregnancies; second, to compare the distributions of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum pregnancy-associated plasma protein-A (PAPP-A) in twin pregnancies that delivered with PE to those in singleton pregnancies and to develop new models based on these results; and, third, to examine the predictive performance of these models in screening for PE with delivery at < 32 and < 37 weeks' gestation. METHODS: Two datasets of prospective non-intervention multicenter screening studies for PE in twin pregnancies at 11 + 0 to 13 + 6 weeks' gestation were used. The first dataset was from the EVENTS (Early vaginal progesterone for the preVention of spontaneous prEterm birth iN TwinS) trial and the second was from a previously reported study that examined the distributions of biomarkers in twin pregnancies. Maternal demographic characteristics and medical history from the EVENTS-trial dataset were used to assess the validity of risks from our previously developed model. The combined data from the first and second datasets were used to compare the distributional properties of log10 multiples of the median (MoM) values of UtA-PI, MAP, PlGF and PAPP-A in twin pregnancies that delivered with PE to those in singleton pregnancies and develop new models based on these results. The competing-risks model was used to estimate the individual patient-specific risks of delivery with PE at < 32 and < 37 weeks' gestation. Screening performance was measured by detection rates (DR) and areas under the receiver-operating-characteristics curve. RESULTS: The EVENTS-trial dataset comprised 1798 pregnancies, including 168 (9.3%) that developed PE. In the validation of the prior model based on maternal characteristics and medical history, calibration plots demonstrated very good agreement between the predicted risks and the observed incidence of PE (calibration slope and intercept for PE < 32 weeks were 0.827 and 0.009, respectively, and for PE < 37 weeks they were 0.942 and -0.207, respectively). In the combined data, there were 3938 pregnancies, including 339 (8.6%) that developed PE and 253 (6.4%) that delivered with PE at < 37 weeks' gestation. In twin pregnancies that delivered with PE, MAP, UtA-PI and PlGF were, at earlier gestational ages, more discriminative than in singleton pregnancies and at later gestational ages they were less so. For PAPP-A, there was little difference between PE and unaffected pregnancies. The best performance of screening for PE was achieved by a combination of maternal factors, MAP, UtA-PI and PlGF. In screening by maternal factors alone, the DR, at a 10% false-positive rate, was 30.6% for delivery with PE at < 32 weeks' gestation and this increased to 86.4% when screening by the combined test; the respective values for PE < 37 weeks were 24.9% and 41.1%. CONCLUSIONS: In the assessment of risk for PE in twin pregnancy, we can use the same prior model based on maternal characteristics and medical history as reported previously, but in the calculation of posterior risks it is necessary to use the new distributions of log10 MoM values of UtA-PI, MAP and PlGF according to gestational age at delivery with PE. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Revised competing-risks model in screening for pre-eclampsia in twin pregnancy by maternal characteristics and medical history.

BACKGROUND: We have proposed previously that the competing-risks model for prediction of pre-eclampsia (PE) based on maternal characteristics and medical history (prior model), developed in singleton pregnancies, can be extended to risk assessment for twins; in dichorionic (DC) and monochorionic (MC) twin pregnancies with the same characteristics as in singleton pregnancies, the distribution of gestational age at delivery with PE was shifted to the left by 8 and 10 weeks, respectively. However, in a subsequent validation study, we found that, in both the training and validation datasets, the observed incidence of PE was lower than the predicted one and such overestimation of risk was particularly marked for early PE. OBJECTIVES: First, to develop a new extension of the competing-risks prior model in screening for PE by maternal demographic characteristics and medical history in twin pregnancies in a training dataset. Second, to examine the predictive performance of this model in screening for PE with delivery < 34 weeks (early PE), < 37 weeks (preterm PE) and at any gestational age (all PE) in twins in a validation dataset. Third, to demonstrate the application of screening in a mixed population of singleton and twin pregnancies. METHODS: The data for this study were obtained from two prospective non-intervention multicenter screening studies for PE in twin pregnancies at 11 + 0 to 13 + 6 weeks' gestation. The training and validation datasets consisted of 2219 and 2999 women, respectively. We used the training dataset to fit a model in which the effect of twins on shifting the distribution of gestational age at delivery with PE in singletons to the left should not be the same for all gestational ages but the shift should depend on the singleton prior mean; the effect increases with increasing prior mean. We examined the predictive performance of the model in the training and validation datasets using the area under the receiver-operating characteristics curve (AUC) and calibration plots. Data on 16 747 singleton pregnancies obtained from the Screening ProgRamme for prE-Eclampsia (SPREE) study were included to examine the performance of screening in a mixed population of singleton and twin pregnancies. RESULTS: Calibration plots and calibration intercept and slope demonstrate superior predictive performance of the new model in the validation dataset. Although the AUC for twin pregnancies is lower than in singleton pregnancies, performance of screening in a mixed population of singleton and twin pregnancies is superior to that in singletons (AUC of 0.790 in a mixed population comprising 2% twins and 98% singletons compared to 0.775 in singletons). For the risk cut-offs likely to be used in practice, all twin pregnancies screen positive using maternal characteristics and medical history. CONCLUSIONS: A new competing-risks model in screening for PE by maternal risk factors in twin pregnancy has been developed and, using this model, the predicted risks for early PE, preterm PE and all PE are in relatively good agreement with the observed incidence of the disease. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Validation of competing-risks model in screening for pre-eclampsia in twin pregnancy by maternal factors.

OBJECTIVE: To examine the predictive performance of the competing-risks model in screening for pre-eclampsia (PE) by maternal demographic characteristics and medical history in twin pregnancy, in a training dataset used for development of the model and a validation dataset. METHODS: The data for this study were derived from two prospective non-intervention multicenter screening studies for PE in twin pregnancies at 11 + 0 to 13 + 6 weeks' gestation. The first study of 2219 women, which was reported previously, was used to develop the competing-risks model for prediction of PE and is therefore considered to be the training set. The validation study comprised 2999 women. Patient-specific risks of delivery with PE at < 34 (early), < 37 (preterm) and < 41 + 3 (all) weeks' gestation were calculated using the competing-risks model and the performance of screening for PE in the training and validation datasets was assessed. We examined the predictive performance of the model by, first, its ability to discriminate between the PE and no-PE groups using the area under the receiver-operating characteristics curve (AUC) and, second, calibration, which assesses agreement between the predicted risk and observed incidence of PE. RESULTS: The incidence of early PE, preterm PE and all PE in the training and validation datasets was similar (1.8% vs 1.4%, 5.6% vs 5.6% and 7.7% vs 7.2%, respectively) and this was substantially higher than in our previous studies in singleton pregnancies. The training and validation datasets had similar AUCs for early PE (0.670 (95% CI, 0.593-0.747) vs 0.677 (95% CI, 0.594-0.760)), preterm PE (0.666 (95% CI, (0.617-0.715) vs 0.652 (95% CI, 0.609-0.694)) and all PE (0.656 (95% CI, 0.615-0.697) vs 0.644 (95% CI, 0.606-0.682)). Calibration plots of the predictive performance of the competing-risks model demonstrated that, in both the training and validation datasets, the observed incidence of PE was lower than the predicted one and such overestimation of risk was particularly marked for early PE. CONCLUSIONS: Discrimination and calibration of the competing-risks model for PE in a validation dataset are consistent with those in the training dataset. However, the model needs to be adjusted to correct the observed overestimation of risk for early PE. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Predictive performance of the competing risk model in screening for preeclampsia.

BACKGROUND: The established method of screening for preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors the patient is classified as high risk and in their absence as low risk. However, the performance of such an approach is poor. We developed a competing risks model, which allows combination of maternal factors (age, weight, height, race, parity, personal and family history of preeclampsia, chronic hypertension, diabetes mellitus, systemic lupus erythematosus or antiphospholipid syndrome, method of conception and interpregnancy interval), with biomarkers to estimate the individual patient-specific risks of preeclampsia requiring delivery before any specified gestation. The performance of this approach is by far superior to that of the risk scoring systems. OBJECTIVE: The objective of the study was to examine the predictive performance of the competing risks model in screening for preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, referred to as the triple test, in a training data set for the development of the model and 2 validation studies. STUDY DESIGN: The data for this study were derived from 3 previously reported prospective, nonintervention, multicenter screening studies for preeclampsia in singleton pregnancies at 11+0 to 13+6 weeks' gestation. In all 3 studies, there was recording of maternal factors and biomarkers and ascertainment of outcome by appropriately trained personnel. The first study of 35,948 women, which was carried out between February 2010 and July 2014, was used to develop the competing risks model for prediction of preeclampsia and is therefore considered to be the training set. The 2 validation studies were comprised of 8775 and 16,451 women, respectively, and they were carried out between February and September 2015 and between April and December 2016, respectively. Patient-specific risks of delivery with preeclampsia at <34, <37, and <41+3 weeks' gestation were calculated using the competing risks model and the performance of screening for preeclampsia by maternal factors alone and the triple test in each of the 3 data sets was assessed. We examined the predictive performance of the model by first, the ability of the model to discriminate between the preeclampsia and no-preeclampsia groups using the area under the receiver operating characteristic curve and the detection rate at fixed screen-positive rate of 10%, and second, calibration by measurements of calibration slope and calibration in the large. RESULTS: The detection rate at the screen-positive rate of 10% of early-preeclampsia, preterm-preeclampsia, and all-preeclampsia was about 90%, 75%, and 50%, respectively, and the results were consistent between the training and 2 validation data sets. The area under the receiver operating characteristic curve was >0.95, >0.90, and >0.80, respectively, demonstrating a very high discrimination between affected and unaffected pregnancies. Similarly, the calibration slopes were very close to 1.0, demonstrating a good agreement between the predicted risks and observed incidence of preeclampsia. In the prediction of early-preeclampsia and preterm-preeclampsia, the observed incidence in the training set and 1 of the validation data sets was consistent with the predicted one. In the other validation data set, which was specifically designed for evaluation of the model, the incidence was higher than predicted, presumably because of better ascertainment of outcome. The incidence of all-preeclampsia was lower than predicted in all 3 data sets because at term many pregnancies deliver for reasons other than preeclampsia, and therefore, pregnancies considered to be at high risk for preeclampsia that deliver for other reasons before they develop preeclampsia can be wrongly considered to be false positives. CONCLUSION: The competing risks model provides an effective and reproducible method for first-trimester prediction of early preeclampsia and preterm preeclampsia as long as the various components of screening are carried out by appropriately trained and audited practitioners. Early prediction of preterm preeclampsia is beneficial because treatment of the high-risk group with aspirin is highly effective in the prevention of the disease.