diagnostics Article Reduction in Preterm Preeclampsia after Contingent First-Trimester Screening and Aspirin Prophylaxis in a Routine Care Setting Cristina Trilla 1,2,3 , Josefina Mora 2,3,4 , Nuria Ginjaume 1 , Madalina Nicoleta Nan 4 , Obdulia Alejos 1,2 , Carla Domínguez 1 , Carmen Vega 1 , Yessenia Godínez 1 , Monica Cruz-Lemini 1,3 , Juan Parra 1,2 and Elisa Llurba 1,2,3, * 1 Department of Obstetrics and Gynaecology, Institut d’Investigació Biomèdica Sant Pau-IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, 08025 Barcelona, Spain; ctrilla@santpau.cat (C.T.); nuriag544@gmail.com (N.G.); oalejos@santpau.cat (O.A.); cdominguezg@santpau.cat (C.D.); mvega@santpau.cat (C.V.); yessp77@gmail.com (Y.G.); mcruzl@santpau.cat (M.C.-L.); jparra@santpau.cat (J.P.) 2 Department of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain; jmora@santpau.cat 3 Primary Care Interventions to Prevent Maternal and Child Chronic Diseases of Perinatal and Developmental Origin Network (RICORS, RD21/0012/0001), Instituto de Salud Carlos III, 28029 Madrid, Spain 4 Biochemistry Department, Hospital de la Santa Creu i Sant Pau, 08025 Barcelona, Spain; mnan@santpau.cat * Correspondence: ellurba@santpau.cat; Tel.: +34-935-337-041 Abstract: 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 Citation: Trilla, C.; Mora, J.; aspirin (LDA) has shown a reduction in the incidence of preterm PE in women with a high-risk Ginjaume, N.; Nan, M.N.; Alejos, O.; assessment in the first trimester. An important barrier to the implementation of first-trimester Domínguez, C.; Vega, C.; Godínez, Y.; screening is the cost of performing tests for biochemical markers in the whole population. Theoretical Cruz-Lemini, M.; Parra, J.; et al. contingent strategies suggest that two-stage screening models could also achieve high detection rates Reduction in Preterm Preeclampsia for preterm PE with lower costs. However, no data derived from routine care settings are currently after Contingent First-Trimester available. This study was conducted to validate and assess the performance of a first-trimester Screening and Aspirin Prophylaxis in contingent screening process using PlGF for PE, with prophylactic LDA, for decreasing the incidence a Routine Care Setting. Diagnostics of preterm PE. Methods: This was a two-phase study. In phase one, a contingent screening model 2022, 12, 1814. https://doi.org/ for PE was developed using a multivariate validated model and a historical cohort participating in 10.3390/diagnostics12081814 a non-interventional PE screening study (n = 525). First-stage risk assessment included maternal Academic Editor: Bettina Blaumeiser factors, MAP, UtA-PI, and PAPP-A. Several cut-off levels were tested to determine the best screening Received: 17 June 2022 performance, and three groups were then defined (high-, medium-, and low-risk groups). PlGF was Accepted: 25 July 2022 determined in the medium-risk group to calculate the final risk. Phase two included a validation Published: 28 July 2022 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 Publisher’s Note: MDPI stays neutral clinical impact of the model was evaluated by comparing the incidence of early-onset (<34 weeks) and with regard to jurisdictional claims in preterm (<37 weeks) PE between groups. Results: Cut-off levels for the contingent screening model published maps and institutional affil- iations. 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 Copyright: © 2022 by the authors. second-stage screening for PlGF, yielding an overall screen-positive rate of 14.9% (n = 126). The Licensee MDPI, Basel, Switzerland. incidence of preterm PE was reduced by 68.4% (1.9% vs. 0.6%, p = 0.031) after one year of screening This article is an open access article implementation. Conclusions: Implementation of contingent screening for PE using PlGF in a routine distributed under the terms and care setting led to a significant reduction (68.4%) in preterm PE, suggesting that contingent screening conditions of the Creative Commons can achieve similar results to protocols using PlGF in the whole population. This could have financial Attribution (CC BY) license (https:// benefits, with a similar reduction in the rate of preterm PE. creativecommons.org/licenses/by/ 4.0/). Diagnostics 2022, 12, 1814. https://doi.org/10.3390/diagnostics12081814 https://www.mdpi.com/journal/diagnostics Diagnostics 2022, 12, 1814 2 of 12 Keywords: preeclampsia screening; first trimester; placental growth factor; low-dose aspirin; obstetric outcome; clinical practice 1. Introduction First-trimester screening for early-onset preeclampsia (PE) was included in the Guide- line for Pregnancy Follow-up in Catalonia in 2018 [1]. According to this guideline, universal screening for PE should be performed for all pregnant women, using a combination of ma- ternal and obstetric factors, mean arterial pressure (MAP), uterine artery Doppler (UtA-PI), and pregnancy-associated plasma protein-A (PAPP-A). Low-dose aspirin (LDA) should then be offered to high-risk women until 36 weeks of pregnancy, based on the results of the Aspirin versus Placebo in Pregnancies at High Risk for Preterm Preeclampsia (ASPRE) trial [2]. However, implementation of a universal screening protocol involving multivari- ate models is challenging in clinical practice, and specific training and quality programs are required. Various multivariate screening models for PE have been developed in the past few years [3–5], yielding similar detection rates for early-onset and preterm PE. These programs consist of different combinations of maternal, biophysical, and biochemical factors and are based on different statistical methodologies. Regarding biochemical markers, models incorporating PAPP-A are potentially easier to implement without a substantial increase in costs, since PAPP-A is already available from aneuploidy screening. In contrast, models including placental growth factor (PlGF), a pro-angiogenic involved in placental devel- opment [6], have demonstrated superior detection rates for PE compared to algorithms including PAPP-A alone [7], although these models entail additional costs. Thus, the additional cost of determining PlGF can be a significant barrier to universal screening implementation. As an alternative to models including all the above mentioned variables, contingent screening strategies have been suggested, with two studies evaluating the theoretical performance of two-stage protocols [8,9]. Both studies concluded that such strategies are feasible and can achieve similar detection rates to those of models including all variables, representing potential financial savings. Despite these promising results, no data derived from prospective studies are available regarding implementation and results in clinical practice. The aim of our study was to evaluate the clinical impact of a contingent screening program to prevent preterm PE after one year of its implementation. We also sought to describe the development process of this model and to identify the challenges for its clinical implementation. 2. Materials and Methods This study was a population-based study conducted at the Hospital de la Santa Creu i Sant Pau University Hospital, Barcelona, Spain. First- and second-trimester ultrasounds of pregnant women within the hospital’s area of influence were performed at the hospital. This study was approved by the Ethics Committee of the Institutional Review Board, and all the women gave their informed consent. This is a pilot study of a larger trial on contingent screening for PE, registered with ClinicalTrials.gov (NCT04767438). 2.1. Study Design: Model Development This study consisted of two phases. In both phases, women were included at the time of the first-trimester ultrasound. The first phase involved a historical cohort of women with singleton pregnancies participating in a prospective PE screening protocol, recruited between July 2016 and November 2018, with serum samples stored for the study. Pregnant women living in our hospital referral region had the first- and second-trimester scans at our institution. All women with a singleton pregnancy attending for their first- trimester ultrasound were invited to participate. Thus, the study group included both Diagnostics 2022, 12, 1814 3 of 12 low- and high-risk women. Data on pregnancy outcomes were analyzed retrospectively, and variables from the first-trimester ultrasound were used for the model development. The first-trimester risk of PE was thus retrospectively calculated using a multivariate Gaussian distribution model validated in our population [4]. In a first stage, maternal factors (ethnicity, weight, height, smoking status, parity, history of PE, pre-existing diabetes, hypertension, thrombophilia, renal or autoimmune conditions), biophysical markers (MAP and UtA-PI), and PAPP-A were included, giving a preliminary risk of PE. In the second stage, PlGF was determined and added to the predictive model. Screening performance for early and preterm PE was analyzed at a fixed false positive rate (FPR) of 15%, following the methodology described elsewhere [4]. The final model was defined including three risk groups for PE in the first stage of screening: (1) risk ≥ 1/50, high-risk group with no further testing, (2) risk between 1/51 and 1/500, medium-risk group requiring further testing, and (3) risk ≤ 1/501, low-risk group. For the second stage, the serum concentrations of PlGF of the medium-risk group were considered, giving the final risk of PE at a cut-off value of 1/160. Given the historical nature of the cohort and the fact that sample size was limited to patient and serum sample availability, the final model and cut-off levels of both stages were chosen to obtain a final screen-positive rate between 15 and 20% for this cohort, with a fixed false positive rate (FPR) of 15%. In this population, prophylactic treatment with LDA (100 mg) was given based on maternal factors alone, according to our institutional protocol for PE, updated in 2016. Therefore, patients were offered treatment in the following situations: (1) the presence of one major risk factor, i.e., previous PE, renal disease, antiphospholipid syndrome, systemic lupus erythematosus, diabetes, or hypertension or (2) two or more moderate risk factors such as pregnancy from egg-donation treatment, maternal age over 40, nulliparity or an intergenesic period of >10 years, family history of PE, or multiple gestation. 2.2. Study Design: Validation Cohort The second phase was a prospective population-based study conducted between 1 February 2019 and 28 February 2020. All sonographers performing first-trimester mea- surements underwent specific training and accreditation by the Fetal Medicine Founda- tion for PE screening for this phase. Women with a singleton pregnancy attending for a first-trimester ultrasound were invited to participate. PE risk assessment was performed according to the previously described contingent model. The list of women requiring PlGF determination was provided to the Biochemistry Department on a weekly basis, on Fridays. PlGF determinations were performed the following Monday, with results available on Tuesday. A phone call appointment was scheduled one week after first-stage screening, to provide final information on results and counseling. Patients with a high risk of PE were offered prophylactic treatment with 150 mg LDA at bedtime from the moment of screening until 36 weeks. If the women refused the second stage of screening, a cut-off value of 1/150 was used for defining high-risk women and offering treatment. This cut-off was chosen to preserve the performance of the screening in the event of women refusing a two-stage approach. A specific follow-up protocol for high-risk pregnancies was established, which included telephone follow-up within three weeks of screening to assess tolerance and adherence to treatment. Adherence was verbally reassessed at every appointment with the midwife or physician. An additional ultrasound was scheduled at 28 weeks to assess fetal growth and UAt-PI. Figure 1 shows the screening and follow-up protocols. An email address was provided to all high-risk patients for online consultation, to enhance access to timely advice and service if needed. Diagnostics 2022, Diagnostics 2022, 12, 12, 1814 x FOR PEER REVIEW 44of 12 of 12 Figure 1.1.Screening Figure Screeningprotocol and and protocol follow-up strategy follow-up for women strategy for at high risk women atofhigh developing risk ofpreeclampsia. developing preeclampsia. 2.3. Sample Collection and Laboratory Procedures SerumCollection 2.3. Sample samples and remaining from Laboratory first-trimester routine analysis were stored for the Procedures study. Serum was separated by centrifugation at 1500× g for 10 min at 4 ◦ C, and samples Serum samples remaining from first-trimester routine analysis were stored for the were stored at −80 ◦ C until they were analyzed. Serum concentrations of PlGF and PAPP-A study. Serum wasby were determined separated by centrifugation fully automated at 1500× g for 10 min electrochemiluminescence at 4 °C, and samples immunoassays, using a were stored Cobas at −80 °C(Roche e 601 analyzer until they were analyzed. Diagnostics). Serum Multiples concentrations of the median (MoM)of PlGF and values forPAPP- PAPP- A and A werePlGF, determined by from calculated fully locally automated electrochemiluminescence derived normal medians using immunoassays, using the above-mentioned a Cobas e 601 analyzer (Roche Diagnostics). Multiples of the median multivariate Gaussian distribution model, were considered for analysis. (MoM) values for PAPP-A and PlGF, calculated from locally derived normal medians using the above-men- tioned 2.4. multivariate Data Collection Gaussian distribution model, were considered for analysis. Maternal and pregnancy characteristics were prospectively recorded at the time of 2.4. Data Collection recruitment and confirmed after delivery by individual chart review. Gestational age Maternal and was determined pregnancy according characteristics to fetal crown–rump were prospectively length (CRL) in all recorded at thefrom cases. Data timetheof recruitment and first-trimester confirmed ultrasound aftercollected, were deliveryi.e., by individual gestationalchart review. age, CRL, and Gestational age was UAt-PI, measured determined according transabdominally. to fetal Blood crown–rump pressure (BP) was length (CRL) once measured in all in cases. oneData arm from (rightthe orfirst- left, trimesterdistinction), without ultrasoundafterwere a 5collected, i.e., gestational min rest with women seated, age,atCRL, andofUAt-PI, the time measured the first-trimester ultrasound, according transabdominally. Bloodto our current pressure (BP)clinical practice. A was measured oncecalibrated in one arm Tensoval (right Duo Control or left, with- (Hartmann AG, 89,522 Heidenheim, Germany) was used. The MAP out distinction), after a 5 min rest with women seated, at the time of the first-trimester was calculated as diastolic ultrasound, BPaccording + (systolic—diastolic to our current BP)/3. clinicalBP was measured practice. A calibrated a single timeDuo Tensoval in one arm. Control Exclusion (Hartmanncriteria were major AG, 89,522 anatomic Heidenheim, malformations, Germany) was used.confirmed The MAP chromosomal was calculatedor genetic as di- abnormalities, and second-trimester astolic BP + (systolic—diastolic BP)/3.pregnancy loss. Since BP was measured recenttime a single evidence in onesuggests that arm. Exclu- SARS-CoV-2 infection sion criteria were majorduring pregnancy anatomic might increase malformations, the risk confirmed of PE, women chromosomal or with geneticSARS- ab- CoV-2 infection were also excluded, to avoid possible confounding normalities, and second-trimester pregnancy loss. Since recent evidence suggests that effects [10]. Preeclampsia SARS-CoV-2 was defined infection during according pregnancytomight the guidelines increase of therisk the International of PE, women Society for with the SARS-CoV-2 infection were also excluded, to avoid possible confounding effects [10]. BP Study of Hypertension in Pregnancy [11]. Thus, diagnosis was based on systolic ≥ 140Preeclampsia mmHg or diastolic BP ≥ according was defined 90 mmHg to onthe repeated occasions guidelines of theafter 20 weeks’Society International gestation for and proteinuria the Study (dipstick urinalysis of Hypertension in Pregnancy ≥ 1+ orThus, [11]. protein/creatinine diagnosis was ratio based≥on30systolic mg/mmol BP ≥ (0.3 mg/mg)) 140 mmHg or another or diastolic BP ≥maternal 90 mmHg organ dysfunction. on repeated occasions Allafter cases20ofweeks’ PE were classified gestation and according to the updated definition of PE in the 2018 Guideline [11], proteinuria (dipstick urinalysis ≥ 1+ or protein/creatinine ratio ≥ 30 mg/mmol (0.3 mg/mg)) including those of or the historical another cohort. maternal organPEdysfunction. was classifiedAll according cases of PEtowere gestational classified age at delivery according as to the early-onset (<34 weeks), preterm (<37 weeks), or term ( ≥ 37 weeks). updated definition of PE in the 2018 Guideline [11], including those of the historical co- Birth-weight centiles were calculated hort. PE according was classified to local according to standards gestational[12]. age atSmall delivery for gestational as early-onset age(<34 (SGA) age weeks), was defined preterm (<37as a birthorweight weeks), below term (≥37 the 10th weeks). centile. Abruptio Birth-weight centiles wereplacentae was defined calculated according as premature separation of the placenta after 20 weeks’ gestation. to local standards [12]. Small for gestational age (SGA) age was defined as a birth weight below the 10th centile. Abruptio placentae was defined as premature separation of the placenta after 20 weeks’ gestation. Diagnostics 2022, 12, 1814 5 of 12 2.5. Statistical Analysis Statistical analyses for both model development and validation were performed us- 2.5. ing theStatistical IBM-SPSS Analysis software program, v.26.0 (IBM-SPSS Inc., Chicago, IL, USA). Upon de- Statistical velopment of theanalyses model, for bothincorporated it was model development and validation into the SsdwLab6 were6.1 version performed using package (SBP the 2007 Soft IBM-SPSS S.L.), software which is program, the prenatalv.26.0 (IBM-SPSS program usedInc., Chicago, IL,screening for aneuploidy USA). Upon develop- at our hos- mentThe pital. of the model, itperformance diagnostic was incorporated of the into the SsdwLab6 contingent screening version model6.1 in package (SBP co- the historical Soft 2007was hort S.L.), which is theby characterized prenatal program determining used forspecificity, sensitivity, aneuploidyscreen-positive screening at our hospital. rate, posi- Thepredictive tive diagnosticvalue performance (PPV), andof the contingent negative screening predictive model value (NPV)in the forhistorical early andcohort was preterm characterized by determining sensitivity, specificity, screen-positive PE, with the chosen cut-off points, at a fixed FPR of 15%. MoM biomarker equations and rate, positive predic- tivepredictive the value (PPV), and negative algorithm predictive were based value on the (NPV) for previously early andmodel published preterm[4],PE, withthis since the chosenhas model cut-off points, already been at validated a fixed FPR in of the15%. sameMoM biomarker population. equations However, and analysis MoM the predictive was algorithm also performedwerein based on the previously the control group (no published PE group)model [4], since for internal this model validation for has modelalready de- been validated velopment. in the same population. However, MoM analysis was also performed in the control group (no PE group) for internal validation for model development. Pregnancy outcomes of the two study groups were compared to assess the clinical impactPregnancy outcomes of the screening of theData program. two study groups are shown were as the compared mean (standard to deviation, assess the SD)clinical or impact of the screening program. Data are shown as the mean (standard percentages for continuous and categorical variables, respectively, and the median (inter- deviation, SD) or percentages quartile range, IQR)for continuous and categorical for non-parametric variables.variables, respectively, Associations between and the median variables were (interquartile range, IQR) for non-parametric evaluated using Student’s t-test, the χ test, or the 2 variables. Associations between Mann–Whitney U test, where appropri- variables were t-test, and 2 test, or the Mann–Whitney U test, where ate. Allevaluated using Student’s reported p-values were 2-sided, the χunequal variances were assumed. A p-value ofappropriate. < 0.05 was used to define p-values All reported statisticalwere 2-sided, and unequal variances were assumed. significance. A p-value of < 0.05 was used to define statistical significance. 3. Results 3. Results A total of 1491 women were included in the study. Of these, 1390 met the inclusion A total of 1491 women were included in the study. Of these, 1390 met the inclusion criteria. criteria.The Thehistorical historicalgroup groupincluded included525 525women women(38.3%) (38.3%)and andthe theprospective prospectivevalidation validation group groupincluded included847 847women women(61.7%). (61.7%).Figure Figure22depicts depictsthe theflowchart flowchartfor forthe thestudy. study. Figure Figure2.2.Flowchart Flowchartfor forthe thestudy studypopulation. population. The maternal and pregnancy characteristics and the biochemical and biophysical variables of the study population are presented in Table 1. Women included in the prospec- tive group had a higher BMI (23.5 vs. 24.2, p = 0.007) and higher rates of pregnancies achieved through assisted reproductive technologies (6.7% vs. 10.4%, p = 0.020). More-over, there were some differences in biochemical and biophysical markers between groups, with women of the prospective group having lower PAPP-A levels and a lower mean UAt-PI. Diagnostics 2022, 12, 1814 6 of 12 Table 1. Baseline characteristics of study participants according to study groups. Retrospective Prospective Maternal and Pregnancy Characteristics Screening Screening p (n = 525) (n = 847) General characteristics * Maternal age (years) 33.2 (4.7) 33.7 (5.2) 0.062 Body mass index (kg/m2 ) 23.5 (4.1) 24.2 (4.4) 0.007 Smoking during pregnancy 36 (6.9) 38 (4.5) 0.065 Ethnicity Caucasian 398 (75.8) 563 (66.7) Latin-American 90 (17.1) 193 (22.9) 0.012 Asian 13 (2.5) 20 (2.4) Afro-Caribbean 7 (1.3) 18 (2.1) North African 10 (1.8) 24 (2.8) Other 8 (1.5) 26 (3.1) Medical history * Chronic hypertension 3 (0.6) 13 (1.5) 0.078 Thyroid condition 39 (7.2) 78 (9.2) 0.231 Diabetes mellitus 5 (0.9) 4 (0.5) 0.316 Autoimmune condition 3 (0.6) 11 (1.3) 0.271 Neurologic condition 1 (0.2) 13 (1.5) 0.023 Thrombophilia 8 (1.5) 9 (1.1) 0.461 Renal disease 1 (0.2) 3 (0.4) >0.999 Pregnancy history * Nulliparous 314 (59.8) 485 (57.3) 0.368 Previous PE 10 (1.9) 19 (2.2) 0.847 Previous SGA 28 (5.3) 38 (4.5) 0.517 Repeated miscarriage 29 (5.5) 32 (3.8) 0.139 ART conception * 35 (6.7) 88 (10.4) 0.020 Biophysical markers MAP (mmHg) † 83.6 (8.5) 83.3 (7.7) 0.396 MAP (MoMs) † 1.03 (0.95–1.11) 1.03 (0.96–1.11) 0.540 Mean UAt-PI † 1.74 (1.43–2.06) 1.68 (1.38–1.99) 0.028 Mean UAt-PI (MoMs) † 1.14 (0.94–1.37) 1.09 (0.91–1.30) 0.005 Biochemical markers GA at blood sampling (weeks) * 10.6 (1.1) 10.6 (1.1) 0.662 PAPP-A (MoMs) † 1.08 (0.73–1.55) 1.01 (0.69–1.43) 0.029 PlGF (MoMs) † 0.98 (0.70–1.39) 0.99 (0.73–1.26) 0.327 GA at screening (weeks) 12.9 (0.6) 12.8 (0.6) 0.715 CRL (mm) 65.6 (7.7) 65.5 (8.0) 0.773 * Data are given as mean (SD) or n (%). † Data are given as median (interquartile range, IQR). PE: preeclamp- sia; SGA: small for gestational age; ART: assisted reproductive technologies; MAP: mean arterial pressure; UAt-PI: uterine artery pulsatility indices; GA: gestational age; PAPP-A: associated plasma protein-A; PlGF: pla- cental growth factor; MoMs: multiples of the median; CRL: crown–rump length. Figure 3 shows the screening results and the incidence of PE for the historical group. At the first stage of screening, 11.4% (n = 60) of the women had a high risk of PE. The medium-risk group included 21.5% (n = 113) of the women, and PlGF was determined in 102 women. The final high-risk group included 91 women (17.3%). The overall incidence of PE was 4% (n = 21). Of those, 47.6% (n = 10) were preterm cases and 52.4% (n = 11) occurred at term. The high-risk group according to contingent screening included 80% of the preterm PE cases and all cases of early-onset PE. Thus, for early-onset PE, sensitivity, specificity, PPV, and NPV were 100%, 85%, 4%, and 100%, respectively, for an FPR of 15%. For preterm PE, sensitivity, specificity, PPV, and NPV were 80%, 85%, 9%, and 99%, respectively, for an FPR of 15%. The positive-screen rate was 17.3%. In this group, 1.9% (n = 10) of the women were given LDA at 100 mg. occurred at term. The high-risk group according to contingent screening included 80% of the preterm PE cases and all cases of early-onset PE. Thus, for early-onset PE, sensitivity, specificity, PPV, and NPV were 100%, 85%, 4%, and 100%, respectively, for an FPR of 15%. For preterm PE, sensitivity, specificity, PPV, and NPV were 80%, 85%, 9%, and 99%, re- spectively, for an FPR of 15%. The positive-screen rate was 17.3%. In this group, 1.9% (n = Diagnostics 2022, 12, 1814 7 of 12 10) of the women were given LDA at 100 mg. Figure 3. Screening results and obstetric outcomes of the historical group. PE, preeclampsia. Figure 3. Screening results and obstetric outcomes of the historical group. PE, preeclampsia. Figure 4 shows the screening results and incidence of PE for the prospective group. At the first stage Figure of screening, 4 shows 8.7% (nresults the screening = 74) and of the women of incidence had PEa for high-risk result andgroup. the prospective 15.3% (n the At = 130) firstrequired second-stage stage of screening, 8.7%screening with (n = 74) of PlGF. The the women hadfinal positive-screen a high-risk result andrate was 15.3% 14.9% (n = 126). Of those, 84.9% (n = 107) received treatment with LDA at 150 (n = 130) required second-stage screening with PlGF. The final positive-screen rate was mg at bedtime, until 36 weeks. Assessment within 3 weeks of treatment initiation showed that LDA was 14.9% (n = 126). Of those, 84.9% (n = 107) received treatment with LDA at 150 mg at bed- not taken according to the protocol in 19 cases, due to adverse effects or intolerance (n = 4), time, until 36 weeks. Assessment within 3 weeks of treatment initiation showed that LDA prescription of a lower dose of aspirin (n = 5), allergy to aspirin or medical contraindication was not taken according to the protocol in 19 cases, due to adverse effects or intolerance (n = 4), patient refusal of treatment (n = 5), or delay in final screening result (n = 1). Three (n = 4), prescription of a lower dose of aspirin (n = 5), allergy to aspirin or medical contra- of these women (15.7%) developed term PE. Women were contacted and informed of indication (n = 4), patient refusal of treatment (n = 5), or delay in final screening result (n their final risk of PE according to the protocol in all cases except one where the telephone = 1). Three of these women (15.7%) developed term PE. Women were contacted and in- appointment was not scheduled in a timely way, and in this case, second-stage screening formed of their final risk of PE according to the protocol in all cases except one where the was performed after 16 weeks, yielding a high-risk result. This woman developed term telephone appointment was not scheduled in a timely way, and in this case, second-stage PE. Six women (0.7%) refused second-stage screening, and here a cut-off value of 1/150 screening was performed after 16 weeks, yielding a high-risk result. This woman devel- was used to determine high risk. Pregnancy follow-up of high-risk women was performed oped term PE. according Sixprotocol to the women (0.7%) refused in all cases. second-stage Quality screening, assessment and here for UAt-PI wasaperformed cut-off value for of 1/150 was used to determine high risk. Pregnancy follow-up all sonographers. Internal validation of the model was performed with MoM of high-risk women was analysis of biochemical markers of the control group (no PE group), showing suitable results as follows: PAPP-A MoM 1.04 (0.71–1.49) and PlGF MoM 0.99 (0.76–1.34). MoM analyses of the PE patients gave values of 0.87 (0.55–1.30) and 0.90 (0.59–1.23) for PAPP-A and PlGF, respectively. The obstetric outcomes are summarized in Table 2. The incidence of preterm PE (below 37 weeks) was reduced significantly by 68.4% after implementation of the contingent screening model (1.9% before vs. 0.6% after, p = 0.031). In contrast, the rate of term PE increased by 61.9%, although these results were not statistically significant. There were two cases of early-onset PE in the prospective group. The first patient was classified as high risk, and LDA was prescribed according to the protocol, with optimal adherence to treatment. However, this patient developed severe early-onset PE with fetal growth restriction and required delivery at 31+6 weeks. The second patient was classified as low risk but developed severe early-onset PE with fetal growth restriction and required delivery at 33+1 weeks. The rate of abruptio placentae was also significantly decreased with prospective screening (0.8% before vs. 0% after, p = 0.021). performed according to the protocol in all cases. Quality assessment for UAt-PI was per- formed for all sonographers. Internal validation of the model was performed with MoM analysis of biochemical markers of the control group (no PE group), showing suitable re- sults as follows: PAPP-A MoM 1.04 (0.71–1.49) and PlGF MoM 0.99 (0.76–1.34). MoM anal- yses of the PE patients gave values of 0.87 (0.55–1.30) and 0.90 (0.59–1.23) for PAPP-A and Diagnostics 2022, 12, 1814 PlGF, respectively. 8 of 12 Figure 4. Screening results and obstetric outcomes of the prospective group. PE, preeclampsia. Figure Table4.2.Screening Obstetric results outcomesandaccording obstetric outcomes of the prospective group. PE, preeclampsia. to study groups. The obstetric outcomes are summarized Retrospective Prospective in Table 2. The incidence of preterm PE (be- Group low 37 weeks) was reduced significantly by 68.4% after implementation Group of the contingentp (n = 525) (n = 847) screening model (1.9% before vs. 0.6% after, p = 0.031). In contrast, the rate of term PE Pregnancy increased bytreatments 61.9%, although these results were not statistically significant. There were Aspirin 10 (1.9) 117 (13.8) <0.001 two cases of early-onset PE in the prospective group. The first patient was classified as LMWH 12 (2.3) 19 (2.2) >0.999 high risk, and LDA was prescribed according to the protocol, with optimal adherence to Birth characteristics treatment. However,* this patient developed severe early-onset PE with fetal growth re- GA at birth (weeks) * 39.7 (2.3) 39.6 (1.9) 0.648 striction and required delivery at 31+6 weeks. The second patient was classified as low risk Female gender 268 (51.1) 410 (48.5) 0.374 but developed severe(grams) Birth weight early-onset PE with fetal 3259 growth restriction (567) 3222and (504)required delivery 0.231 at 33+1 weeks. The Vaginal rate of abruptio placentae delivery was also significantly 421 (82.5) decreased with 628 (74.3) pro- <0.001 spective screening (0.8% Obstetric complications * before vs. 0% after, p = 0.021). Overall PE 21 (4.0) 34 (4.0) >0.999 Early-onset PE 3 (0.6) 2 (0.2) 0.377 Preterm PE 10 (1.9) 5 (0.6) 0.031 Term PE 11 (2.1) 29 (3.4) 0.187 SGA 49 (9.3) 97 (11.5) 0.242 SGA with PE 6 (1.1) 8 (0.9) 0.785 SGA without PE 43 (8.2) 89 (10.5) 0.187 Preterm birth 27 (5.1) 34 (4.0) 0.347 Gestational diabetes 40 (7.6) 56 (6.6) 0.514 Abruptio placentae 4 (0.8) 0 (0) 0.021 Stillbirth 4 (0.8) 1 (0.1) 0.074 * Data are given as mean (SD) or n (%). LMWH: low-molecular-weight heparin; GA: gestational age; PE: preeclamp- sia; SGA: small for gestational age. 4. Discussion Our study suggests that implementation of contingent screening for PE in clinical practice, using PlGF in 15% of the population, can achieve a significant decrease in preterm PE. Since publication of the ASPRE trial [2], the need for first-trimester screening programs for PE has become urgent for obstetricians. However, although awareness of LDA treat- ment exists, and its effectiveness is unarguable [13], significant concerns persist regarding Diagnostics 2022, 12, 1814 9 of 12 screening implementation in clinical practice. Firstly, the choice of the screening algorithm will depend on the characteristics of the population to be screened [14]. Secondly, the choice regarding biochemical variables is debatable [7,15], and the balance between screening performance and costs must be considered. 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 sin- gleton 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. This decision facilitated the integration of results and clinical implementation of the program. Moreover, this screening algorithm had been validated in our po-pulation. [4] The model validated in our population was developed using both PAPP-A and PlGF. Higher performance of the model was obtained using PlGF than using PAPP-A, but both models are currently available in Catalonia, and screening can currently be performed using either PAPP-A or PlGF. Acknowledging that PlGF is the preferred biomarker for PE screening [7], we developed a contingent model using a historical population. Research regarding two-stage screening for PE has been conducted from a theoretical perspective. The results focused on screening performance rather than clinical aspects of implemen- tation [8,9]. In our study, we found that a contingent model can be implemented with well-established protocols regarding methodology, quality assessment, patient counseling, and pregnancy follow-up. We consider it important that all these aspects are carefully consi-dered in advance when implementing any screening protocol. There was a high acceptance of the two-stage model, with only six women refusing the second stage of screening. For the medium-risk group, results were available within one week after the first assessment. Since the initiation of LDA prophylaxis is time-sensitive [19], it is crucial to establish an itinerary for the results, to avoid delays in obtaining the final risk assessment. We found a significant reduction of preterm PE after one year of prospective screening, determining PlGF in 15% of our population. Previous contingent models tested se-veral algorithms to achieve a 70% detection rate for preterm PE. However, in these algorithms, PlGF had to be determined in 30–40% of the population [8,9], which entails higher costs. In our setting, UAt-PI and MAP were easily incorporated at the time of the first-trimester ultrasound, and PAPP-A was available from aneuploidy screening. Likewise, maternal factors were assessed at the first appointment. Thus, these variables were included in the first stage, and PlGF was reserved for the medium-risk group only. From a pragmatic viewpoint, this algorithm is easier to implement than determining UAt-PI along with PlGF up to the second stage. More importantly, despite the limited sample size included in our study, the reduction in preterm PE incidence was consistent with previous research [2]. Interestingly, our results are also consistent with previous data showing that LDA may delay the onset of the disease, since late-onset PE rates increased after the implementation of screening [20]. The aim of the study was not to assess the effectiveness of aspirin in decreasing the incidence of preeclampsia, as this had already been demonstrated in the ASPRE trial, but to evaluate the clinical impact of a universal contingent screening protocol. The reduction in preterm PE observed by comparing perinatal outcomes of the historical and prospective groups corroborate the fact that the screening protocol resulted in good selection of high-risk women who might benefit from the treatment under clinical practice conditions. Regarding perinatal outcomes, we also found a reduction in placental abruption in the treated group. These results are concordant with previous research conducted on that topic [21], although the numbers were too small to drive meaningful conclusions. No differences were found in the rate of SGA between groups. Overall, and despite baseline characteristics seeming to favor worse outcomes in the validation group, contingent screening was able to detect high-risk cases where LDA prophylaxis may have been of benefit. Diagnostics 2022, 12, 1814 10 of 12 Our contingent model was developed for an FPR of 15%, while previous studies adopted an FPR of 10%. Since the model was defined using a retrospective cohort, we decided to use a higher FPR to achieve high detection rates. The screen-positive rate was 17.3% in the historical group and 14.9% in the prospective group. The fact that the UAt-PI was significantly lower in the prospective group could explain this difference. However, although the choice of the FPR and cut-offs is always arbitrary, we acknowledge that some modifications in this model may be necessary to reduce the screen-positive rate without affecting the clinical results. Regarding the variables included in the screening model, the selection of the bio- chemical markers represents an important decision. Models including PlGF have been shown to perform slightly better than models using PAPP-A [7]. Nevertheless, models using PAPP-A have demonstrated good detection rates without the added cost of deter- mining PlGF in all women [15]. Moreover, although models using PlGF are cost-effective compared with screening using maternal factors alone [22], no studies have compared models using PAPP-A alone, PlGF alone, or PlGF in a subgroup of the population in a contingent protocol. Further research is needed to confirm which screening strategy has the best cost-effectiveness profile in different populations. Our study has some limitations. This was a consecutive cases cohort study, based on the availability of patients, and lacked power calculation. The historical cohort used to develop the model included only three cases of early-onset PE, and this could impact the performance of the screening. In addition, quality assessment of the UAt-PI was not performed in the historical cohort. To address these limitations and avoid under-detection of high-risk women, the model was defined with a 15% FPR. Furthermore, contingent screenings have potential limitations in terms of clinical follow-up compared with one- step strategies. As demonstrated in our study, the development of specific itineraries for final risk assessment is crucial to avoid missing results. Finally, the prophylactic dose of aspirin used in the historical cohort was 100 mg, following the recommendations of our institutional protocol at that time. Only 1.9% of women were given 100 mg of aspirin in this group. The dose of aspirin was increased to 150 mg in the prospective phase, following the recommendations of the ASPRE trial and the Guideline for Pregnancy Follow-up implemented in Catalonia in 2018. We acknowledge that developing a screening model based on a historical group has significant limitations, but we estimate that the use of a lower dose of aspirin in only a small proportion of women from this group was a factor that, precisely, allowed a more accurate development of the model. Despite these limitations, our study also had various strengths. Firstly, the original screening model for PE had already been validated in our population. This is important since performance may vary depending on the characteristics of the population to be screened [23–25]. Secondly, this study was conducted in the context of current clinical practice, which enhances the external validity of the results. Thirdly, describing the me- thodology used for clinical implementation of a multivariate contingent screening process for PE could be of value in clinical settings where universal PlGF is not feasible. To conclude, the implementation of contingent screening for PE in clinical practice is feasible with well-defined protocols. Contingent screening determining PlGF in a medium- risk group can achieve similar results to protocols using PlGF in the whole population. Further studies involving larger populations are required to confirm our findings. Author Contributions: Conceptualization, E.L.; Data curation, C.T.; Investigation, C.T., N.G., M.N.N., O.A., C.D., C.V., Y.G. and J.P.; Methodology, C.T. and E.L.; Resources, J.M. and E.L.; Supervision, E.L.; Validation, E.L.; Writing—original draft, C.T.; Writing—review & editing, M.C.-L., J.P. and E.L. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Approved with approval number IISBP-PRE-2018-08. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Diagnostics 2022, 12, 1814 11 of 12 Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions. Acknowledgments: We thank the Biobank of Sant Pau for valuable management of samples. We also thank all the medical staff, residents, midwives, and nurses of Hospital Sant Pau for careful data collection. We specially thank Assumpta Antonijuan for her key role in the collection and management of first-trimester samples. Conflicts of Interest: The authors declare no conflict of interest. References 1. Departament de Salut De Catalunya. Protocol de Seguiment de l’embaràs a Catalunya. Scientia; Departament de Salut: Barcelona, Spain, 2018. 2. Rolnik, D.L.; Wright, D.; Poon, L.C.; O’Gorman, N.; Syngelaki, A.; de Paco Matallana, C.; Akolekar, R.; Cicero, S.; Janga, D.; Singh, M.; et al. Aspirin versus Placebo in Pregnancies at High Risk for Preterm Preeclampsia. N. Engl. J. Med. 2017, 377, 613–622. [CrossRef] [PubMed] 3. Scazzocchio, E.; Figueras, F.; Crispi, F.; Meler, E.; Masoller, N.; Mula, R.; Gratacos, E. Performance of a first-trimester screening of preeclampsia in a routine care low-risk setting. Am. J. Obstet. Gynecol. 2013, 208, 203.e1–203.e10. [CrossRef] [PubMed] 4. Serra, B.; Mendoza, M.; Scazzocchio, E.; Meler, E.; Nolla, M.; Sabrià, E.; Rodríguez, I.; Carreras, E. A new model for screening for early-onset preeclampsia. Am. J. Obstet. Gynecol. 2020, 222, 608.e1–608.e18. [CrossRef] 5. O’Gorman, N.N.; Wright, D.; Poon, L.C.; Rolnik, D.L.; Syngelaki, A.; Wright, A.; Akolekar, R.; Cicero, S.; Janga, D.; Jani, J.; et al. Accuracy of competing-risks model in screening for pre-eclampsia by maternal factors and biomarkers at 11–13 weeks’ gestation. Ultrasound Obstet. Gynecol. 2017, 49, 751–755. [CrossRef] 6. Ribatti, D. The discovery of the placental growth factor and its role in angiogenesis: A historical review. Angiogenesis 2008, 11, 215–221. [CrossRef] [PubMed] 7. Mazer Zumaeta, A.; Wright, A.; Syngelaki, A.; Maritsa, V.A.; Da Silva, A.B.; Nicolaides, K.H. Screening for pre-eclampsia at 11–13 weeks’ gestation: Use of pregnancy-associated plasma protein-A, placental growth factor or both. Ultrasound Obstet. Gynecol. 2020, 56, 400–407. [CrossRef] 8. Wright, D.; Gallo, D.M.; Gil Pugliese, S.; Casanova, C.; Nicolaides, K.H. Contingent screening for preterm pre-eclampsia. Ultrasound Obstet. Gynecol. 2016, 47, 554–559. [CrossRef] 9. Wright, A.; Wright, D.; Syngelaki, A.; Georgantis, A.; Nicolaides, K.H. Two-stage screening for preterm preeclampsia at 11–13 weeks’ gestation. Am. J. Obstet. Gynecol. 2019, 220, 197.e1–197.e11. [CrossRef] 10. Villar, J.; Ariff, S.; Gunier, R.B.; Thiruvengadam, R.; Rauch, S.; Kholin, A.; Roggero, P.; Prefumo, F.; do Vale, M.S.; Cardona-Perez, J.A.; et al. Maternal and Neonatal Morbidity and Mortality Among Pregnant Women With and Without COVID-19 Infection: The INTERCOVID Multinational Cohort Study. JAMA Pediatr. 2021, 175, 817–826. [CrossRef] 11. Brown, M.A.; Magee, L.A.; Kenny, L.C.; Karumanchi, S.A.; McCarthy, F.P.; Saito, S.; Hall, D.R.; Warren, C.E.; Adoyi, G.; Ishaku, S.; et al. Hypertensive Disorders of Pregnancy: ISSHP Classification, Diagnosis, and Management Recommendations for International Practice. Hypertension 2018, 72, 24–43. [CrossRef] 12. Figueras, F.; Meler, E.; Iraola, A.; Eixarch, E.; Coll, O.; Figueras, J.; Francis, A.; Gratacos, E.; Gardosi, J. Customized birthweight standards for a Spanish population. Customized birthweight standards for a Spanish population. Eur. J. Obstet. Gynecol. Reprod. Biol. 2008, 136, 20–24. [CrossRef] [PubMed] 13. Roberge, S.; Nicolaides, K.; Demers, S.; Hyett, J.; Chaillet, N.; Bujold, E. The role of aspirin dose on the prevention of preeclampsia and fetal growth restriction: Systematic review and meta-analysis. Am. J. Obstet. Gynecol. 2017, 216, 110–120.e6. [CrossRef] [PubMed] 14. Cuckle, H.S. First trimester pre-eclampsia screening: Why delay implementation? BJOG 2018, 125, 450. [CrossRef] 15. Noël, L.; Guy, G.P.; Jones, S.; Forenc, K.; Buck, E.; Papageorghiou, A.T.; Thilaganathan, B. Routine first-trimester combined screening for pre-eclampsia: Pregnancy-associated plasma protein-A or placental growth factor? Ultrasound Obstet. Gynecol. 2021, 58, 540–545. [CrossRef] 16. O’ Gorman, N.; Wright, D.; Poon, L.C.; Rolnik, D.L.; Syngelaki, A.; De Alvarado, M.; Carbone, I.F.; Dutemeyer, V.; Fiolna, M.; Frick, A.; et al. Multicenter screening for pre-eclampsia by maternal factors and biomarkers at 11–13 weeks’ gestation: Comparison with NICE guidelines and ACOG recommendations. Ultrasound Obstet. Gynecol. 2017, 49, 756–760. [CrossRef] 17. Poon, L.C.; Rolnik, D.L.; Tan, M.Y.; Delgado, J.L.; Tsokaki, T.; Akolekar, R.; Singh, M.; Andrade, W.; Efeturk, T.; Jani, J.C.; et al. ASPRE trial: Incidence of preterm pre-eclampsia in patients fulfilling ACOG and NICE criteria according to risk by FMF algorithm. Ultrasound Obstet. Gynecol. 2018, 51, 738–742. [CrossRef] 18. FIGO Working Group on Good Clinical Practice in Maternal-Fetal Medicine. Good clinical practice advice: First trimester screening and prevention of pre-eclampsia in singleton pregnancy. Int. J. Gynaecol. Obstet. 2019, 144, 325–329. [CrossRef] [PubMed] 19. Saravia-Sucaticona, M.; Martinez-Garcia, F.E.; Solar-Cuba, M.J. The timing of aspirin administration in pregnancy is important to prevent preeclampsia. Am. J. Obstet. Gynecol. MFM 2021, 3, 100313. [CrossRef] Diagnostics 2022, 12, 1814 12 of 12 20. Wright, D.; Nicolaides, K.H. Aspirin delays the development of preeclampsia. Am. J. Obstet. Gynecol. 2019, 220, 580.e1–580.e6. [CrossRef] 21. Roberge, S.; Bujold, E.; Nicolaides, K.H. Meta-analysis on the effect of aspirin use for prevention of preeclampsia on placental abruption and antepartum hemorrhage. Am. J. Obstet. Gynecol. 2018, 218, 483–489. [CrossRef] 22. Ortved, D.; Hawkins, T.L.A.; Johnson, J.A.; Hyett, J.; Metcalfe, A. Cost-effectiveness of first-trimester screening with early preventative use of aspirin in women at high risk of early-onset pre-eclampsia. Ultrasound Obstet. Gynecol. 2019, 53, 239–244. [CrossRef] [PubMed] 23. Ghosh, G.; Grewal, J.; Männistö, T.; Mendola, P.; Chen, Z.; Xie, Y.; Laughon, S.K. Racial/ethnic differences in pregnancy-related hypertensive disease in nulliparous women. Ethn. Dis. 2014, 24, 283–289. 24. Al Khalaf, S.Y.; O’Reilly, É.J.; Barrett, P.M.; BLeite, D.F.; Pawley, L.C.; McCarthy, F.P.; Khashan, A.S. Impact of Chronic Hypertension and Antihypertensive Treatment on Adverse Perinatal Outcomes: Systematic Review and Meta-Analysis. J. Am. Heart Assoc. 2021, 10, e018494. [CrossRef] 25. Wright, D.; Syngelaki, A.; Akolekar, R.; Poon, L.C.; Nicolaides, K.H. Competing risks model in screening for preeclampsia by maternal characteristics and medical history. Am. J. Obstet. Gynecol. 2015, 213, 62.e1–62.e10. [CrossRef] [PubMed]