Literature DB >> 34899048

Reducing the Risk of Preterm Preeclampsia: Comparison of Two First Trimester Screening and Treatment Strategies in a Single Centre in Switzerland.

Sofia Amylidi-Mohr1, Jakub Kubias1, Stefanie Neumann1, Daniel Surbek1, Lorenz Risch2, Luigi Raio1, Beatrice Mosimann1.   

Abstract

Introduction First trimester screening for preeclampsia (PE) is based on the combined risks model. Recent trials demonstrate that variations in multiple of the medians (MoMs) of the screening markers influence the performance of the algorithm in different populations. The aim of this study is to compare the performance of the algorithm in two cohorts with different prevention strategies. Material and Methods All first trimester screening tests performed between January 2014 and April 2020 were included. Up to June 2017 pregnancies with a risk > 1 : 200 for early-onset PE (eoPE) were considered at risk and received 100 mg of aspirin (strategy A). From July 2017 onwards, pregnancies with a risk > 1 : 100 for preterm PE (pPE) received 150 mg of aspirin (strategy B). We compared the screen positive rates (SPR) and incidence of PE between the two screening approaches. Statistical analysis were performed with Graphpad 8.0. Results 3552 pregnancies were included; 1577 pregnancies were screened according to strategy A, 1975 pregnancies according to strategy B. The screen positive rate (SPR) for strategy A and B was 8.9 and 16.9% respectively (p < 0.0001) while the incidence of PE was 1.41 and 1.84% respectively (p = ns). Conclusion With a SPR of less than 10% we achieved a remarkably low rate of PE in our population, no further reduction in PE could be achieved by an increase in the SPR and LDA-prescription during the second screening period. The cut-off to define a pregnancy at risk for PE should be tailored to keep the SPR below 10% to avoid unnecessary treatment with aspirin. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Entities:  

Keywords:  first trimester screening; implementation; preeclampsia

Year:  2021        PMID: 34899048      PMCID: PMC8654509          DOI: 10.1055/a-1332-1437

Source DB:  PubMed          Journal:  Geburtshilfe Frauenheilkd        ISSN: 0016-5751            Impact factor:   2.915


Introduction

Preeclampsia (PE) affects 1.2 – 4.5% of all pregnancies globally and is associated with severe short- and long-term consequences for both mother and child 1 ,  2 ,  3 ,  4 . Preterm PE (pPE), requiring delivery before 37 weeks of gestation, occurs in 0.7 – 2.3% of all pregnancies or around 30 – 50% of all pregnancies diagnosed with PE 5 ,  6 ,  7 ,  8 ,  9 . The decision to deliver in the late preterm period (after 34 weeks of gestation), is mostly based on local protocols trading off maternal risks against fetal benefits and not due to deterioration of maternal or fetal health, which explains the variation in the incidence of pPE 9 . Delivery is still the only treatment for PE available today, however prevention is possible in high-risk pregnancies with low-dose aspirin (LDA) started before 16 weeks of gestation 10 ,  11 ,  12 . The Fetal Medicine Foundation (FMF) London has developed a first trimester screening algorithm combining background risk factors with placental growth factor (PlGF), mean arterial pressure (MAP) and uterine artery pulsatility index (UtA PI). This allows the identification of more pregnancies at risk for pPE than the previous approach of screening by maternal risk factors alone at the same false positive rate (FPR) of 10% 6 ,  13 . The initial publications focussed on screening for early onset preeclampsia (eoPE), with delivery before 34 + 0 weeks of gestation 6 ,  12 . A cut-off of 1 : 200 for eoPE resulted in an acceptable false-positive rate (FPR) of about 10% 6 ,  14 . An international multicentre study validating the FMF screening algorithm, prior to starting the ASPRE trial, demonstrated that to achieve a FPR of 10% the cut-off had to be set at 1 : 100 for pPE 15 . Most data on combined first trimester screening for PE today originate from prospective studies, little is known about the performance of this PE-screening in a general clinical setting. We introduced screening for PE in our ultrasound department in 2014. Initially we focused on screening for eoPE as described above and prescribed 100 mg of aspirin if the risk was > 1 : 200 for eoPE (strategy A). Following the publication of the ASPRE trial in June 2017, we changed our policy and prescribed 150 mg of aspirin to all women with a risk > 1 : 100 for pPE (strategy B) 12 ,  15 . The aim of this study was to compare the two screening strategies in our population. As LDA reduced the incidence of pPE, neither the DR nor the FPR are valid parameters in our study, setting to be assessed as measures of quality control. However, the screen-positive rate (SPR) is a valuable parameter not influenced by treatment 13 .

Material and Methods

Recruitment and inclusion criteria

This is an observational study with a prospective analysis of retrospective data. All women with singleton pregnancies who opted for screening for PE at the ultrasound department of the university hospital of Bern at their 11 to 14 weeks scan between January 2014 and April 2020 and agreed to further use of their data were included in this study.

Maternal characteristics and screening modality

Maternal age, height, weight, BMI, parity and ethnicity, personal history of smoking, pre-existing diabetes, pre-existing hypertension, systemic lupus erythematosus (SLE) or antiphospholipid syndrome (APS), previous pregnancy with a small for gestational age child (SGA) or previous PE and family history of PE as well as mode of conception define the background risk and were recorded in all patients. All biochemical, biophysical and ultrasound parameters were assessed according to the guidelines provided by the FMF London 16 . MAP was measured at the time of the scan between 11 and 14 weeks gestation with UEBE Visomat comfort, a pregnancy-validated device. UtA-PI was assessed by sonographers certified by the FMF London on Voluson E8 and E10 machines (GE medical systems). PlGF was measured on Kryptor Compact Plus from Brahms GmbH between 10 + 0 and 14 + 0 weeks gestation 17 ; PAPP-A was included in case it was measured for screening for trisomies, it was also assessed on Kryptor Compact Plus from Brahms GmbH between 8 + 0 and 14 + 0 weeks gestation. Multiples of the Medians (MoMs) were calculated by the software provided by Viewpoint 5.6.25.284 (GE healthcare support systems) 6 . The same software was also used to calculate the risks for eoPE, pPE and term PE (tPE) 6 . Pregnancy outcomes up to December 2018 were obtained from our clinical data system or from referring doctors and hospitals. Aspirin was prescribed according to the two different screening strategies described in the Introduction. Few women with a low risk at screening but with previous PE and/or SGA, chronic hypertension, pre-existing diabetes, SLE, APS and/or chronic kidney disease received a prescription of LDA (usually 100 mg) despite their screening result by our outpatientʼs clinic or their private gynaecologist. Compliance was not tested in this study.

PE definition

Historically PE was defined as systolic blood pressure of ≥ 140 mmHg and/or diastolic blood pressure of ≥ 90 mmHg after 20 weeks of gestation occurring together with a significant proteinuria (≥ 300 mg/24 h urine collection or ≥ 30 mg protein/mmol creatinin or ≥++ dipstick) [18]. The International Society for the Study of Hypertension in Pregnancy (ISSHP) proposed an adapted definition: Additionally to hypertension either proteinuria and/or other signs of maternal endothelial dysfunction and/or utero-placental dysfunction with intrauterine growth restriction are required for the diagnosis 18 . We considered all pregnancies without pre-existing renal disease diagnosed with hypertension and proteinuria as “classical” PE, and all cases fulfilling the new ISSHP criteria as “ISSHP-new” PE. Neonates born with a birth weight below the 5th percentile according to the birth weight charts of the FMF London are classified as FGR 14 .

Statistical analysis

Statistical analyses were performed with GraphPad version 8.0 for Windows (GraphPad Software, San Diego CA). Spearman rank correlation and linear regression were used to analyse the correlation between the individual markers and gestational age. Continuous variable were analysed using the Student t-test or Mann-Whitney U-test while proportions were evaluated utilizing the Fisherʼs exact test or χ 2 test. Statistical significance was considered achieved when p was less than 0.05. The Ethics Committee of the University of Bern approved the study.

Results

During the study period, 3552 pregnancies were included. 1577 screening tests were performed up to June 2017 (strategy A) and 1975 between July 2017 and April 2020 (strategy B). The background risk factors and screening parameters of both screening periods are depicted in Table 1 . The various outcome parameters are shown in Table 2 . The incidence of classical PE and pPE respectively was 1.58% (38/2407) and 0.62% (15/2407) of all live births while the incidence of ISSHP-new PE and pPE was 2.04% (49/2407) and 0.75% (18/2407).

Table 1  Maternal characteristics, personal history and screening parameters grouped according to the two strategies applied.

Strategy A (n = 1577)Strategy B (n = 1975)p
Figures in parentheses are percentages; figures in brackets are interquartile ranges. SLE: systemic lupus erythematosus; APS: antiphospholipid syndrome. Comparisons between each outcome group and unaffected controls: Fisherʼs exact test for categorical variables and Mann-Whitney test for continuous variables. p < 0.05 is considered significant.
Median maternal age, years31.0 [27.0 – 35.0]33.0 [29.0 – 36.0]p < 0.0001
Median maternal weight, kg62.6 [56.0 – 71.6]64.4 [58.0 – 74.0]p < 0.0001
Median maternal height, cm165.0 [160.0 – 169.0]165.0 [160.0 – 169.7]ns
Median maternal BMI at 12 weeks, kg/m 2 22.8 [20.6 – 26.1]23.7 [21.4 – 27.0]p < 0.0001
Median fetal CRL, mm [IQR]64.7 [59.6 – 70.6]65.0 [59.9 – 70.2]ns
Gestational age, weeks [IQR]12.7 [12.3 – 13.0]12.6 [12.3 – 13.0]ns
Ethnicity:

Caucasian

1184 (75.1)1670 (84.6)p < 0.0001

Black

199 (12.6)113 (5.7)p < 0.0001

South asian

82 (5.2)79 (4.0)ns

East asian

70 (4.4)48 (2.4)p = 0.0013

Mixed

40 (2.5)65 (3.3)ns
Parity:

Nulliparous

805 (50.9)1028 (52.1)ns

Parous without previous PE

725 (46.2)860 (43.5)ns

Parous with previous PE

47 (2.9)87 (4.4)p = 0.027
Cigarette smoker138 (8.8)128 (6.5)p = 0.012
Family history of PE23 (1.5)26 (1.3)ns
Mode of conception:

Spontaneous

1434 (90.9)1776 (89.9)ns

Ovulation induction

60 (3.8)77 (3.9)ns

IVF

83 (5.3)122 (6.2)ns
Chronic hypertension34 (2.2)51 (2.6)ns
Preexisting diabetes mellitus9 (0.6)19 (1.0)ns
SLE or APS10 (0.6)21 (1.1)ns
Median MAP84.8 [80.4 – 89.9]85.5 [80.8 – 90.6]0.017
Median MAP-MoM1.003 [0.953 – 1.060]1.004 [0.953 – 1.064]ns
Median UtA1.51 [1.22 – 1.87]1.50 [1.20 – 1.88]ns
Median UtA-MoM0.946 [0.764 – 1.160]0.935 [0.761 – 1.168]ns
Median PlGF38.1 [29.4 – 51.0]38.6 [29.0 – 52.0]ns
Median PlGF-MoM0.971 [0.766 – 1.231]0.986 [0.751 – 1.268]ns

Table 2  Pregnancy outcomes.

Strategy A (n = 1507/1577 [95.6%])Strategy B (n = 942/983 [95.8%])p
Figures in parentheses are percentages; figures in brackets are interquartile ranges. Comparisons between each outcome group and unaffected controls: Fisherʼs exact test for categorical variables and Mann-Whitney test for continuous variables. p < 0.05 is considered significant.
Misscarriages/TOP (%)21 (1.4)18 (1.9)ns
IUFD after 24 weeks (%)3 (0.2)0 (0.0)ns
Live birth (%)1483 (98.4)924 (98.1)ns
Gestational age [IQR]39.6 [38.4 – 40.4]39.4 [38.4 – 40.3]ns

PTB < 34 weeks (%)

18 (1.2)17 (1.8)ns

PTB 34 – 37 weeks (%)

72 (4.9)50 (5.4)ns

Term birth (%)

1393 (93.9)857 (92.7)ns
Mode of delivery

Spontaneous

750 (50.6)488 (52.8)ns

Vaginal operative

181 (12.2)82 (8.9)p = 0.011

CS

550 (37.1)354 (38.3)ns

Unknown

2 (0.1)0 (0.0)ns
Gender

Male

749 (50.5)459 (49.7)ns

Female

734 (49.5)465 (50.3)ns
Birth weight g [IQR]3313 [2990 – 3600]3260 [2965 – 3589]ns

< 5%ile (%) FMF

100/1476 (6.8)64/916 (7.0)ns

< 10%ile (%) FMF

183/1476 (12.4)113/916 (12.3)ns
Classic PE21 (1.41)17 (1.84)ns

eoPE

5 (0.34)4 (0.43)ns

pPE

7 (0.47)8 (0.87)ns

tPE

14 (0.94)9 (0.97)ns
New definition PE29 (1.96)20 (2.16)ns

eoPE

5 (0.34)4 (0.43)ns

pPE

9 (0.61)9 (0.97)ns

tPE

20 (1.35)11 (1.19)ns
Screen positive pPE, negative eoPE

pPE with LDA

1/90 (1.1)2/80 (2.5)ns
Table 1  Maternal characteristics, personal history and screening parameters grouped according to the two strategies applied. Caucasian Black South asian East asian Mixed Nulliparous Parous without previous PE Parous with previous PE Spontaneous Ovulation induction IVF Table 2  Pregnancy outcomes. PTB < 34 weeks (%) PTB 34 – 37 weeks (%) Term birth (%) Spontaneous Vaginal operative CS Unknown Male Female < 5%ile (%) FMF < 10%ile (%) FMF eoPE pPE tPE eoPE pPE tPE pPE with LDA

Performance of the screening parameters

Over the total study period median MAP was significantly higher in women who developed pPE compared to uneventful pregnancies (94.1 mmHg [81.5 – 104.5] vs. 84.8 mmHg [80.4 – 89.8] (p < 0.05). Median PlGF was significantly lower (17.4 ng/ml [13.7 – 27.3] vs. 38.1 ng/ml [29.2 – 51.8] (p < 0.001) and UtA-PI significantly higher (1.99 [1.71 – 2.10] vs. 1.50 [1.20 – 1.86] (p < 0.001) in pregnancies with pPE. Throughout the whole study period, the median MAP-MoM was 1.003 [0.953 – 1.062], the median PlGF-MoM was 0.981 [0.757 – 1.247], and the median UtA-PI MoM measured 0.940 [0.761 – 1.164]. In comparison to the study population included in the ASPRE trial, in our cohort the background risk is significantly higher in regard to obstetrical risk factors, chronic hypertension, SLE and APS as well as a higher prevalence of pregnancies conceived by assisted reproductive technologies (ART). The ethnic background is similar in both populations, only the family history for PE was lower in our cohort ( Table 3 ) 15 .

Table 3  Comparison of our population to the population investigated by OʼGorman et al prior to starting the ASPRE trial 13 .

Bern (n = 3552)OʼGorman (n = 8775)p
Figures in parentheses are percentages; figures in brackets are interquartile ranges. ART: assisted reproductive technology; SLE: systemic lupus erythematosus; APS: antiphospholipid syndrome. Comparisons between each outcome group and unaffected controls: Fisherʼs exact test for categorical variables and Mann-Whitney test for continuous variables. p < 0.05 is considered significant.
Median maternal age, years32.0 [28.0 – 35.0]31.5
Median maternal weight, kg63.4 [57.0 – 73.0]66.4
Median maternal height, cm165.0 [160.0 – 169.0]165.0
Median BMI at 12 weeks, kg/m 2 23.4 [21.0 – 26.7]24.6
Gestational age (weeks)12.6 [12.3 – 13.0]12.7
Ethnicity:

White

2854 (80.3)6883 (78.4)p = 0.0191

Black

312 (8.8)1090 (12.4)p < 0.0001

South asian

161 (4.5)462 (5.3)ns

East asian

118 (3.3)154 (1.8)p < 0.0001

Mixed

107 (3.0)186 (2.1)p = 0.004
Parity:

Nulliparous

1833 (51.6)4127 (47.0)p < 0.0001

Parous without previous PE

1585 (44.6)4459 (50.8)p < 0.0001

Parous with previous PE

134 (3.8)189 (2.2)p < 0.0001
Cigarette smoker266 (7.5)732 (8.3)ns
Family history of PE49 (1.8)458 (5.2)p < 0.0001
Conception:

Spontaneous

3210 (90.4)8484 (96.7)p < 0.0001

ART

342 (9.6)291 (3.3)p < 0.0001
Chronic hypertension85 (2.4)100 (1.1)p < 0.0001
Preexisting diabetes mellitus28 (0.8)68 (0.8)ns
SLE or APS31 (0.9)32 (0.4)p = 0.0007
Table 3  Comparison of our population to the population investigated by OʼGorman et al prior to starting the ASPRE trial 13 . White Black South asian East asian Mixed Nulliparous Parous without previous PE Parous with previous PE Spontaneous ART

Comparison of the two different screening strategies

In regard of the background risk, women assessed during the second screening period (strategy B) were significantly older and had a higher BMI. The ethnicity changed to more Caucasian women and instead less black women attending for screening during strategy B. The screening parameters performed similarly, only the median MAP was significantly higher in the second screening period ( Table 1 ), a finding that did not reflect significantly on the calculated median MAP-MoMs. The SPR during the first study period (strategy A) was much lower with 8.9% (141/1577) compared to the SPR during the second study period (strategy B) with 16.9% (334/1975) (p < 0.0001). This resulted in a much higher LDA-prescription rate during the second screening period. In both study periods all women with a risk for eoPE > 1 : 200 also had a risk for pPE > 1 : 100. During strategy A 99 (6.2%) of all women had an increased risk for pPE > 1 : 100 but no increased risk for eoPE > 1 : 200; during strategy B 149 (7.5%) were in this intermediate risk group. The incidence of PE did not vary significantly between the two screening strategies (1.41% in strategy A vs. 1.84% in strategy B [p = ns]) ( Table 2 ). In addition, no significant difference in the incidence of pPE, eoPE, or any PE according to the new ISSHP-definition could be demonstrated. Finally no difference of pPE was found in the women with a risk for pPE > 1 : 100 but not for eoPE > 1 : 200 (1.1% [1/90] vs. 2.5% [2/80], p = ns) despite a much lower rate of LDA-prescription during strategy A compared to B (25.3 vs. 86.6%, p < 0.0001).

Screening positive rate

Considering the whole study population the SPR is 9.2% if the cut-off > 1 : 200 for eoPE is chosen and 16.2% if the cut-off > 1 : 100 for pPE is used. Vice versa, in our population a SPR of 10 – 11% is achieved using a cut-off for pPE set at 1 : 60 (SPR of 10% at 1 : 57, SPR of 11% at 1 : 64).

Discussion

The introduction of first trimester combined screening for PE into routine practice with prescription of LDA to women considered at risk resulted in a remarkably low rate of classical PE of 1.58% and preterm classical PE of 0.62% in our population compared to the incidence of 2.31% previously stated in Switzerland or 3.8% in Europe 2 ,  19 . The increase in SPR from 8.9 to 16.9% by changing the cut-off between the two study periods resulted in no further reduction of PE or pPE, despite the higher rate of LDA-prescriptions and even an increased dosage of LDA in the second screening period after the publication of the ASPRE trial 12 . The importance of a certified assessment of the different screening parameters has been stressed in many publications, more recently, it was demonstrated that multiple of the medians especially of PlGF differ for example in the Asian population. As a result adaption is necessary for an optimal performance of PE-screening 7 ,  20 . In our population, the screening parameters perform as previously described: MAP and the UtA-PI are higher, while PlGF is lower in women who later develop PE 21 , 22 , 23 . MAP performs according to expectations with a median MAP-MoM of 1.003 and remains at a very stable level independent of the algorithm used to calculate MoMs. UtA-PI and PlGF are both parameters that are more variable. The most operator-dependant marker is the uterine artery pulsatility index (UtA-PI). Our results demonstrate that the median UtA-PI-MoMs are below 1.0 throughout the whole study period but also that they are significantly different when compared by the different calculators applied. Several studies demonstrated that training and regular feedback improve the performance 24 ,  25 , and eventually also changing to transverse scanning through the cervix instead of the sagittal approach might improve the results 26 . However, in our population despite regular feedback, we find no significant change over the years in the median UtA-PI MoM. These findings might contradict the assumption that in general practice a very good performance of UtA-PI is achievable. On the other hand, the stable results over the years could also signify that UtA-PIs are generally lower in our population and an adjustment of the MoMs could be considered. Median PlGF-MoMs, unlike in the Asian population, are within the expected range in our cohort ( Fig. 1 ) 7 ,  20 .
Fig. 1

 PlGF MoM distributions of the first 500 patients by alphabetical calculated by Viewpoint 5.6.25.824. The measurements are within 0.1 SD from the expected 6 ,  16 .

PlGF MoM distributions of the first 500 patients by alphabetical calculated by Viewpoint 5.6.25.824. The measurements are within 0.1 SD from the expected 6 ,  16 . In the development of the PE-screening algorithm, a fixed false-positive rate (FPR) was used to calculate the detection rate (DR). Ideally a high DR is achieved at a low FPR, generally a FPR of 5 – 10% is accepted 5 ,  6 ,  15 ,  27 ,  28 ,  29 ,  30 . Given that the incidence of pPE is about 1% in a general population without intervention, the FPR of 10% is comparable to a SPR of 11%. In the ASPRE trial, a cut-off of 1 : 100 for pPE was used, however in our population that cut-off resulted in a SPR of 16.2%, much higher than expected 15 . An explanation for the high SPR could be a higher background risk in our population, as MAP and PlGF perform according to expectations and the UtA-PIs are lower than expected, reducing rather than increasing the SPR 12 ,  15 ,  31 . In the original publication of the FMF London, a FPR of 10% for pPE was achieved using a cut-off in screening for pPE of 1 : 67 6 . In our population, we found a SPR of 11% at a cut-off of 1 : 64 for pPE, which is very consistent with the finding of Akolekar et al. 6 . Therefore another explanation for the high SPR could be that the cut-off proposed by the ASPRE trial group is simply too high. One might argue that a high FPR also increases the overall DR, however the safety of LDA in lower-risk populations has not been proven so far and our results demonstrate no further reduction in PE despite the significant increase in LDA-prescription during the second study period 32 . Especially in the group of women with an intermediate risk (> 1 : 100 for pPE but < 1 : 200 for eoPE) there was no higher incidence of pPE despite the much lower rate of LDA-prescription during the first study period. It seems therefore safe to withhold LDA in those pregnancies.

Conclusion

Overall, this study demonstrates a good performance of first trimester combined screening for PE in our population using the FMF algorithm. While previous studies focused on improving the performance of individual screening parameters and adjusting MoMs, our results further demonstrate the importance of defining an ideal cut-off to consider a pregnancy at risk. By applying the cut-off of 1 : 100 for pPE proposed by the ASPRE trial we nearly doubled the SPR compared to our previous screening approach without any further reduction of the incidence of PE. These results prompt us to reconsider the cut-off for defining a pregnancy at risk for pPE and for treating with aspirin to 1 : 60.
  31 in total

1.  Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation.

Authors:  Neil O'Gorman; David Wright; Argyro Syngelaki; Ranjit Akolekar; Alan Wright; Leona C Poon; Kypros H Nicolaides
Journal:  Am J Obstet Gynecol       Date:  2015-08-19       Impact factor: 8.661

2.  Influence of sampling site on uterine artery Doppler indices at 11-13⁺⁶ weeks gestation.

Authors:  Gus Ridding; Philip J Schluter; Jon A Hyett; Andrew C McLennan
Journal:  Fetal Diagn Ther       Date:  2015-02-21       Impact factor: 2.587

3.  Quality assessment of uterine artery Doppler measurement in first-trimester combined screening for pre-eclampsia.

Authors:  D L Rolnik; F da Silva Costa; D Sahota; J Hyett; A McLennan
Journal:  Ultrasound Obstet Gynecol       Date:  2019-01-11       Impact factor: 7.299

4.  Combined screening for preeclampsia and small for gestational age at 11-13 weeks.

Authors:  Leona C Y Poon; Argyro Syngelaki; Ranjit Akolekar; Jonathan Lai; Kypros H Nicolaides
Journal:  Fetal Diagn Ther       Date:  2012-09-13       Impact factor: 2.587

5.  Multicenter screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation: comparison with NICE guidelines and ACOG recommendations.

Authors:  N O'Gorman; D Wright; L C Poon; D L Rolnik; A Syngelaki; M de Alvarado; I F Carbone; V Dutemeyer; M Fiolna; A Frick; N Karagiotis; S Mastrodima; C de Paco Matallana; G Papaioannou; A Pazos; W Plasencia; K H Nicolaides
Journal:  Ultrasound Obstet Gynecol       Date:  2017-06       Impact factor: 7.299

6.  First-trimester screening for early and late preeclampsia using maternal characteristics, biomarkers, and estimated placental volume.

Authors:  Jiri Sonek; David Krantz; Jon Carmichael; Cathy Downing; Karen Jessup; Ziad Haidar; Shannon Ho; Terrence Hallahan; Harvey J Kliman; David McKenna
Journal:  Am J Obstet Gynecol       Date:  2017-10-31       Impact factor: 8.661

7.  Screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation.

Authors:  M Y Tan; A Syngelaki; L C Poon; D L Rolnik; N O'Gorman; J L Delgado; R Akolekar; L Konstantinidou; M Tsavdaridou; S Galeva; U Ajdacka; F S Molina; N Persico; J C Jani; W Plasencia; E Greco; G Papaioannou; A Wright; D Wright; K H Nicolaides
Journal:  Ultrasound Obstet Gynecol       Date:  2018-07-11       Impact factor: 7.299

8.  Mean arterial pressure at 11(+0) to 13(+6) weeks in the prediction of preeclampsia.

Authors:  Leona C Y Poon; Nikos A Kametas; Ivilina Pandeva; Catalina Valencia; Kypros H Nicolaides
Journal:  Hypertension       Date:  2008-02-07       Impact factor: 10.190

Review 9.  Low-Dose Aspirin for Preventing Preeclampsia and Its Complications: A Meta-Analysis.

Authors:  Ting-ting Xu; Fan Zhou; Chun-yan Deng; Gui-qiong Huang; Jin-ke Li; Xiao-dong Wang
Journal:  J Clin Hypertens (Greenwich)       Date:  2015-04-02       Impact factor: 3.738

10.  First-trimester pre-eclampsia biomarker profiles in Asian population: multicenter cohort study.

Authors:  P Chaemsaithong; D Sahota; R K Pooh; M Zheng; R Ma; N Chaiyasit; K Koide; S W Shaw; S Seshadri; M Choolani; T Panchalee; P Yapan; W S Sim; A Sekizawa; Y Hu; A Shiozaki; S Saito; T Y Leung; L C Poon
Journal:  Ultrasound Obstet Gynecol       Date:  2020-07-10       Impact factor: 7.299

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  1 in total

1.  Integrating Combined First Trimester Screening for Preeclampsia into Routine Ultrasound Examination.

Authors:  Fabienne Trottmann; Anne Elena Mollet; Sofia Amylidi-Mohr; Daniel Surbek; Luigi Raio; Beatrice Mosimann
Journal:  Geburtshilfe Frauenheilkd       Date:  2022-03-03       Impact factor: 2.915

  1 in total

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