Preeclampsia (PE) is a multisystem disease affecting 2–8% of all pregnancies [1]. The definition of PE was recently updated by the International Society for the Study of Hypertension in Pregnancy (ISSHP) [2] and subsequently endorsed by the International Federation of Gynecology and Obstetrics (FIGO) [3] as new-onset hypertension after 20 weeks of gestation accompanied by at least one of the following: proteinuria, other maternal organ dysfunction or uteroplacental dysfunction. PE was classified into early-onset (with delivery at 34 + 0 weeks of gestation), preterm (with delivery at 37 + 0 weeks of gestation), late-onset (with delivery at $\ge$34 weeks of gestation) and term (with delivery at $\ge$37 + 0 weeks of gestation) [3].

The clinical relevance of PE is related to the high maternal and perinatal morbidity and mortality. Indeed, PE may cause maternal complications such as placental abruption, HELLP syndrome, acute pulmonary oedema, respiratory distress syndrome, and acute renal failure [4]. On the fetal side, PE is associated with fetal growth restriction (FGR), intra uterine fetal death (IUFD), oligohydramnios, preterm delivery, non-reassuring fetal heart rate (FHR) during labour, risk of caesarean section or instrumental operative delivery, low Apgar scores, and need for NICU admission [5].

The risk of adverse maternal and perinatal outcomes is higher in early-onset PE than late-onset PE [6, 7].

The prediction of PE in the first trimester of pregnancy may allow the introduction of prophylactic treatments as demonstrated by the ASPRE trial [8]. This study provided major evidence that applying a combined screening test including maternal demographic characteristics and measurements of maternal biomarkers level (mean arterial pressure, uterine artery Doppler pulsatility index, serum concentrations of pregnancy associated-plasma protein A, placental growth factor) and performing in women at high-risk Aspirin prophylaxis (150 mg/day; from 11–14 weeks until 36 weeks of gestation) the risk of developing preterm PE reduced by 60% [8]. Relevant international guidelines [3], as well as the Italian association of preeclampsia (AIPE) [9], recently supported and recommended the introduction of universal screening for PE.

The aim of this study was to examine the available literature on first trimester PE screening implementation within local settings in Italy, including aspects related to peculiar characteristics of local populations and health systems, in order to identify potential critical issues hampering the diffusion of the screening program.

The systematic search yielded 432 papers. After excluding duplicates and inappropriate citations, 47 full-text articles were assessed for eligibility. Fig. 1 shows the flow chart of study selection. Thirty-eight studies were excluded for the following reasons: review, systematic review, meta-analysis, correspondence, or articles not reporting original data (n = 12), original articles of non-Italian study population (n = 18), original articles about screening for both PE and pregnancy-induced hypertension (n = 1), original articles about other PE screening strategies that excluded the first trimester (n = 6), and original articles not reporting data on screening performance (n = 1). Finally, nine articles were included in this review [11, 12, 13, 14, 15, 16, 18, 19, 20] (Fig. 1).

Fig. 1.

PRISMA 2020 flow diagram of systematic review search.

The results of this systematic review with critical points and suggested actions are summarized in Table 1.

Rizzo et al. [11] proposed the first PE screening model at 11–14 weeks in the Italian population. The authors evaluated a dichotomic detection rate (DR) of uterine artery Doppler velocimetry pulsatility index $>$95th centile and three-dimensional ultrasound placental volume 5th centile for PE on 348 nulliparous, including 16 cases of PE. The detection rate of Doppler and placental volume were 50% and 56.3% at a false positive rate of 2–5% about, which increased to 66.7% for both markers for PE requiring delivery 32 weeks. While this screening model is based exclusively on ultrasound parameters, other studies evaluated the efficacy of screening based on biochemical markers in the first trimester. D’Anna et al. [12] evaluated PAPP-A and neutrophil gelatinase-associated lipocalin (NGAL) at 9–11 weeks in 111 pregnancies, including 37 cases of PE. NGAL showed for prediction of late-onset PE a DR of 33.3%, with a false-positive rate of 6.7%.

Youssef et al. [13], in a study of 528 pregnancies including 13 late-onset PE, concluded that a combined screening model that included PlGF, sFlt-1 and NGAL has a DR for PE of 77% at a 10% FPR. Gesuita et al. [18], combining the plasma concentration of high temperature requirement factor A1 (HtrA1) at 12 weeks of gestation with pre-pregnancy BMI, obtained a DR of 40% about at a FPR of 10% (this data was extrapolated from the visual inspection of the ROC curve reported by the authors in their paper). Gestational age at delivery (with a mean of 39 weeks for both case and control groups) was also added to the model but its contribution to DR seems very low.

Di Lorenzo et al. [15], using chronic hypertension plus free-$\beta$hCG and PlGF, found a DR of 75% for early onset PE at 10% FPR. Conversely, late PE was better predicted by the use of Uterine Doppler PI uterine artery PI yielding a DR of 31% at same 10% FPR.

Following various experiences in other countries, models combining these parameters were evaluated in Italy as well. Farina et al. [14] first used screening models that combined maternal characteristics, biophysical and biochemical parameters. The authors applied eight different logistic regression models and compared their DR with that of the original studies. The models proposed by Onwudiwe [21] and Poon [22] showed the best DRs in the study population, respectively of 74.4% and 84.6% at a FPR of 10%.

Di Martino et al. [16] compared the performance of the a priori risk algorithms proposed by FMF [23] in 2012 and BCNatal [17] in an Italian population of 11,632 singleton pregnancies, including 67 cases of early PE and 211 cases of late PE. At a 10% FPR, the DR was 58.2% vs. 41.8% for early PE and 44.1% vs 38% for late PE for the FMF and the BCNatal algorithms, respectively. Therefore, the FMF algorithm showed better performance in this study population. Furthermore, the authors highlighted that the number of observed PE cases was higher than predicted with both algorithms, demonstrating that both algorithms underestimated the risk of early PE.

Brunelli et al. [20] assessed the optimal screening tool for PE in an Italian population considering maternal characteristics in nulliparous pregnant women. The study included 73 preterm PE cases and 7546 controls (including 101 term PE). The authors carried out an external validation study of the simple risk score developed by Sovio and Smith [24] and based on maternal characteristics, whose regression coefficients was derived from the algorithm used by the FMF. This approach showed a low performance on the Italian population of the study, with a DR of 32.9 at a FPR of 8.8% (approximately 40%, lower as compared to the population in Sovio and Smith’s paper). Furthermore, by applying the Sovio and Smith risk score and the FMF algorithm to the same population of the study, the latter showed better performance in predicting PE, with an SDR of 50% about a FPR of 10%.

Traditionally, the National Institute for Health and Clinical Excellence (NICE) [25] and the American College of Obstetricians and Gynaecologists (ACOG) [26, 27] recommended to assess the risk of PE based exclusively upon maternal risk factor. The Fetal Medicine Foundation (FMF) proposed an alternative screening tool that allows to estimate individual patient-specific risk through the use of Bayes theorem, which combines a priori risk (determined by maternal characteristics and medical history) with mean arterial pressure (MAP), mean uterine artery pulsatility index (UtA-PI) and two first-trimester biochemical markers, placental growth factor (PlGF) and pregnancy-associated plasma protein A (PAPP-A) [28, 29].

A prospective multicentre validation study confirmed that FMF’s algorithm detection rates are superior: 100%, 75% and 43%, at a FPR of 10.0% for delivery with PE 32, 37 and $\ge$37 weeks’ gestation, respectively [30]. Moreover, the SPREE study compared diagnostic accuracy of early screening of PE based upon the NICE guidelines with that of the FMF. The NICE method showed poor performance and low compliance. The performance of screening was substantially improved by a method combining maternal factors with biomarkers [31].

Based on the evidence above, the International Federation of Gynecology and Obstetrics (FIGO) endorsed FMF’s algorithm and recommended its use for preterm PE screening in the first trimester [3]. However, where resources are limited, FIGO recommends screening by maternal factors and MAP in all pregnancies and subsequent measurements of PlGF and UtA-PI for the subgroup at risk.

While the Italian Association of PE (AIPE) suggests PE screening proposed by the FMF in centres with adequate professional, laboratory skills and resources [9], we are not aware of clear endorsements of this method by other Italian scientific societies. Unfortunately, despite robust scientific evidence in support of PE screening, the test is not widely adopted within the first trimester.

Validation studies are required before the introduction into clinical practice of new predictive risk models. In fact, their performance can be affected by various factors including differences in statistic models, healthcare systems, methods of measurement and patient characteristics [32].

Our systematic review showed lack of evidence concerning the topic of PE screening within the Italian local setting. We found only a few studies, which unfortunately enrolled a relative small number of cases. Overall, statistics is quite rudimentary if compared to the FMF algorithm, and no custom applications of such algorithm to Italian population are available. While it is already established that PE screening should be clinically implemented at a global level, this review shows the importance of identifying optimal implementation methods for specific clinical settings, and adjusting algorithms for local population characteristics. Specific issues related to populations and health system characteristics will suggest specific strategies to optimize implementation of the screening process. Although the competing risk model proposed by the FMF showed high quality evidence to promote implementation of PE screening globally, research studies on specific local populations are still desirable to focus on subtle details capable of maximizing screening uptake and performance at a local level. This will likely consolidate the effectiveness of screening, whilst also contributing to improve pregnancy outcome and to save valuable health-care system resources.

AF and PIC designed the research study and carried out critical revision. SA and GB performed the literature search, data extraction and qualitative analysis, drafted the paper. AS performed critical revision for important intellectual content and text editing including English language. All authors contributed to writing, editing and revising the manuscript. All authors read and approved the final manuscript.

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This study received no external funding.

The authors declare no conflict of interest.