Good clinical practice advice: First trimester screening and prevention of pre‐eclampsia in singleton pregnancy

Renzo, Gian Carlo Di; Gratacós, Eduard; Курцер, М. А.; Malone, Fergal D.; Nambiar, Sabnam S; Sierra, Nancy; Yang, Hui‐Li; Fuchtner, Carlos; Berghella, Vincenzo; Morales, Ernesto Castelazo; Hanson, Mark A.; Hod, Moshe; Ville, Y.; Visser, Gerhard H.; Simpson, J. L.; Adra, Abdallah; Bataeva, R.S.; Chmait, Ramen H.; Cheng, Yvonne Kwun Yue; Hyett, Jon; Giardina, Irene; Morrison, J.; Nazareth, Amala; Poon, Liona C.; Quintero, Rubén A.; Sepúlveda, Waldo; Tosto, Valentina

doi:10.1002/ijgo.12741

Cited by 13 publications

(6 citation statements)

References 38 publications

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“…Therefore, factors affecting placenta formation and endothelial function damage are the risk factors for PE [17]. Consistent with other studies [18][19][20] which may be because pregnant women with thrombotic disease tendency continued to take anticoagulant drugs such as aspirin in the fi rst trimester, effectively preventing abnormal blood fl ow status and thrombosis, reducing the risk of PE.…”

Section: Discussionsupporting

confidence: 71%

Risk prediction model of early-onset preeclampsia based on risk factors and routine laboratory indicators

Xue¹,

Yang²,

Gu³

et al. 2023

Int J Sex Reprod Health Care

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Background: 10% - 15% of maternal deaths are statistically attributable to preeclampsia. Compared with late-onset PE, the severity of early-onset PE remains greater harm, with higher morbidity and mortality. Objective: To establish an early-onset preeclampsia prediction model by clinical characteristics, risk factors and routine laboratory indicators from 6 to 10 gestational weeks of pregnant women. Methods: The clinical characteristics, risk factors and 38 routine laboratory indicators (6 - 10 weeks of gestation) including blood lipids, liver and kidney function, coagulation, blood count and other indicators of 91 early-onset preeclampsia patients and 709 normal controls without early-onset preeclampsia from January 2010 to May 2021 in Peking University Third Hospital (PUTH) were retrospectively analyzed. Logistic regression, Decision tree model and Support vector machine (SVM) model were applied for establishing prediction models, respectively. ROC curves were drawn, and the area under the curve (AUCROC), sensitivity and specificity was calculated and compared. Results: There were statistically significant differences in the rates of diabetes, Antiphospholipid Syndrome (APS), kidney disease, Obstructive Sleep Apnea (OSAHS), primipara, history of preeclampsia and Assisted Reproductive Technology (ART) (p < 0.05). Among the 38 routine laboratory indicators, there were no significant differences in the levels of PLT/LYM, NEU/LYM, TT, D-Dimer, FDP, TBA, ALP, TP, ALB, GLB, UREA, Cr, P, Cystatin C, HDL- C, Apo-A1, and Lp(a) between the two groups (p > 0.05). The levels of the rest indicators were all statistically different between the two groups (p < 0.05). If only 12 risk factors of PE were analyzed by logistic regression, decision tree model, and the Support Vector Machine (SVM), the AUCROC were 0.78, 0.74 and 0.66 respectively, while 12 risk factors of PE and 38 routine laboratory indicators were analyzed by logistic regression, decision tree model and the support vector machine(SVM), the AUCROC were 0.86, 0.77 and 0.93 respectively. Conclusion: The efficacy of clinical risk factors alone in predicting early-onset preeclampsia is not high, while the efficacy increased significantly when PE risk factors were combined with routine laboratory indicators. The SVM model was better than the logistic regression model and decision tree model in the early prediction of early-onset preeclampsia incidence.

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Section: Discussionsupporting

confidence: 71%

Risk prediction model of early-onset preeclampsia based on risk factors and routine laboratory indicators

Xue¹,

Yang²,

Gu³

et al. 2023

Int J Sex Reprod Health Care

View full text Add to dashboard Cite

show abstract

“…The performance of multivariate screening models is superior to methods based on maternal risk factors alone [ 16 , 17 ]. Recently, the FIGO Working Group on Good Clinical Practice in Maternal–Fetal Medicine endorsed first-trimester screening in singleton pregnancies, using a combination of maternal factors, UAt-PI, MAP, and PlGF at 11–13 weeks [ 18 ]. In our study, PE screening was implemented with the same software used for aneuploidy screening.…”

Section: Discussionmentioning

confidence: 99%

Reduction in Preterm Preeclampsia after Contingent First-Trimester Screening and Aspirin Prophylaxis in a Routine Care Setting

et al. 2022

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Objectives: Several multivariate algorithms for preeclampsia (PE) screening in the first trimester have been developed over the past few years. These models include maternal factors, mean arterial pressure (MAP), uterine artery Doppler (UtA-PI), and biochemical markers (pregnancy-associated plasma protein-A (PAPP-A) or placental growth factor (PlGF)). Treatment with low-dose aspirin (LDA) has shown a reduction in the incidence of preterm PE in women with a high-risk assessment in the first trimester. An important barrier to the implementation of first-trimester screening is the cost of performing tests for biochemical markers in the whole population. Theoretical contingent strategies suggest that two-stage screening models could also achieve high detection rates for preterm PE with lower costs. However, no data derived from routine care settings are currently available. This study was conducted to validate and assess the performance of a first-trimester contingent screening process using PlGF for PE, with prophylactic LDA, for decreasing the incidence of preterm PE. Methods: This was a two-phase study. In phase one, a contingent screening model for PE was developed using a multivariate validated model and a historical cohort participating in a non-interventional PE screening study (n = 525). First-stage risk assessment included maternal factors, MAP, UtA-PI, and PAPP-A. Several cut-off levels were tested to determine the best screening performance, and three groups were then defined (high-, medium-, and low-risk groups). PlGF was determined in the medium-risk group to calculate the final risk. Phase two included a validation cohort of 847 singleton pregnancies prospectively undergoing first-trimester PE screening using this approach. Women at high risk of PE received prophylactic treatment with 150 mg of LDA. The clinical impact of the model was evaluated by comparing the incidence of early-onset (<34 weeks) and preterm (<37 weeks) PE between groups. Results: Cut-off levels for the contingent screening model were chosen in the first and second stages of screening to achieve a performance with sensitivities of 100% and 80% for early-onset and preterm PE detection, respectively, with a 15% false positive rate. In the development phase, 21.5% (n = 113) of the women had a medium risk of PE and required second-stage screening. In the prospective validation phase, 15.3% (n = 130) of the women required second-stage screening for PlGF, yielding an overall screen-positive rate of 14.9% (n = 126). The incidence of preterm PE was reduced by 68.4% (1.9% vs. 0.6%, p = 0.031) after one year of screening implementation. Conclusions: Implementation of contingent screening for PE using PlGF in a routine care setting led to a significant reduction (68.4%) in preterm PE, suggesting that contingent screening can achieve similar results to protocols using PlGF in the whole population. This could have financial benefits, with a similar reduction in the rate of preterm PE.

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“…Therefore, factors affecting placenta formation and endothelial function damage are the risk factors for PE [ 16 ]. Consistent with other studies [ 17 , 18 , 19 ], previous history of preeclampsia, diabetes mellitus, thrombotic disease, systemic lupus erythematosus (SLE), antiphospholipid syndrome (APS), kidney disease, assisted reproductive technology, obstructive sleep apnea hypopnea syndrome (OSAHS), BMI > 30 kg/m 2 , age over 35, multiple pregnancies, and primipara were included as risk factors in the model. In this study, there was no thrombotic disease in the PE group, which may be because pregnant women with thrombotic disease tendency continued to take anticoagulant drugs, such as aspirin in the first trimester, effectively preventing abnormal blood flow status and thrombosis and reducing the risk of PE.…”

Section: Discussionmentioning

confidence: 95%

Risk Prediction Model of Early-Onset Preeclampsia Based on Risk Factors and Routine Laboratory Indicators

Xue

Yang

et al. 2023

Life

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Background: Globally, 10–15% of maternal deaths are statistically attributable to preeclampsia. Compared with late-onset PE, the severity of early-onset PE remains more harmful with higher morbidity and mortality. Objective: To establish an early-onset preeclampsia prediction model by clinical characteristics, risk factors and routine laboratory indicators were investigated from pregnant women at 6 to 10 gestational weeks. Methods: The clinical characteristics, risk factors, and 38 routine laboratory indicators (6–10 weeks of gestation) including blood lipids, liver and kidney function, coagulation, blood count, and other indicators of 91 early-onset preeclampsia patients and 709 normal controls without early-onset preeclampsia from January 2010 to May 2021 in Peking University Third Hospital (PUTH) were retrospectively analyzed. A logistic regression, decision tree model, and support vector machine (SVM) model were applied for establishing prediction models, respectively. ROC curves were drawn; area under curve (AUCROC), sensitivity, and specificity were calculated and compared. Results: There were statistically significant differences in the rates of diabetes, antiphospholipid syndrome (APS), kidney disease, obstructive sleep apnea (OSAHS), primipara, history of preeclampsia, and assisted reproductive technology (ART) (p < 0.05). Among the 38 routine laboratory indicators, there were no significant differences in the levels of PLT/LYM, NEU/LYM, TT, D-Dimer, FDP, TBA, ALP, TP, ALB, GLB, UREA, Cr, P, Cystatin C, HDL-C, Apo-A1, and Lp(a) between the two groups (p > 0.05). The levels of the rest indicators were all statistically different between the two groups (p < 0.05). If only 12 risk factors of PE were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.78, 0.74, and 0.66, respectively, while 12 risk factors of PE and 38 routine laboratory indicators were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.86, 0.77, and 0.93, respectively. Conclusions: The efficacy of clinical risk factors alone in predicting early-onset preeclampsia is not high while the efficacy increased significantly when PE risk factors combined with routine laboratory indicators. The SVM model was better than logistic regression model and decision tree model in early prediction of early-onset preeclampsia incidence.

show abstract

Good clinical practice advice: First trimester screening and prevention of pre‐eclampsia in singleton pregnancy

Cited by 13 publications

References 38 publications

Risk prediction model of early-onset preeclampsia based on risk factors and routine laboratory indicators

Risk prediction model of early-onset preeclampsia based on risk factors and routine laboratory indicators

Reduction in Preterm Preeclampsia after Contingent First-Trimester Screening and Aspirin Prophylaxis in a Routine Care Setting

Risk Prediction Model of Early-Onset Preeclampsia Based on Risk Factors and Routine Laboratory Indicators

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