The role of the PLGF in the management of pregnancies complicated with fetal microsomia.

doi:10.21203/rs.3.rs-2458747/v1

Purpose

To explore the contribution of maternal and fetal parameters in predicting the time interval between diagnosis and development of adverse events leading to delivery in singleton pregnancies complicated with fetal microsomia.

Methods

Prospective study on singleton pregnancies referred to a tertiary centre because of suspicion of fetal smallness in the third trimester. The study cohort included cases with fetal abdominal circumference (AC) ≤ 10th centile or estimated fetal weight ≤ 10th centile or umbilical artery pulsatitlity index ≥ 90th centile. Development of pre-eclampsia, fetal demise and fetal deterioration diagnosed by fetal Doppler studies or fetal heart rate monitoring and leading to delivery were considered as adverse events. Maternal demographics, obctetric history, blood pressure, serum PLGF and fetal Doppler studies were explored as predictors of the time interval between the first visit to the clinic and the diagnosis of complications.

Results

In 59 women the median incubation period from presentation to the clinic to an adverse event was 6,2 weeks, whereas half of the pregnancies (52.5%) did not develop any adverse event. PLGF was the strongest predictor of adverse events. Both PLGF in raw values and PLGF MOM had equally good predictive ability (AUC 0.82 and 0.78 respectively). Optimal cut-off points were 177.7pg/ml for PLGF raw values (sensitivity 83% and specificity 66.7%) and 0.277 MoM (sensitivity 76% and specificity 86.7%). On multiple Cox regression analysis maternal systolic blood pressure and PLGF and fetal increased umbilical artery PI and reduced CP ratio were independently associated with adverse events. Half of the pregnancies with low PLGF and only one in ten with high PLGF were delivered within two weeks after the initial visit.

Conclusion

Half of the pregnancies carrying a small fetus in the third trimester will not develop maternal or fetal complications. PLGF is a strong predictor of adverse events that can be used to customize antenatal care.

small for gestational age

pre-eclampsia

placenta

growth restriction

PLGF

The study showed that in singleton pregnancies with microsomic fetuses maternal serum PLGF can be used to customize antenatal follow up. Women with low PLGF levels are likely to develop complications soon after the diagnosis of fetal smallness and will need intense follow up.

Fetal microsomia is a common pregnancy complication usually presenting in the third trimester. The majority of the small fetuses will maintain normal growth velocity, will deliver at term without any complications and in retrospect can be classified as small for gestational age (SGA) or ‘normal small’ fetuses. However, a significant proportion of the small fetuses have or develop eventually signs of placental dysfunction and are diagnosed as growth restricted (fetal growth restriction, FGR). The main difference between the two groups is that SGA fetuses are considered not to be at increased risk for an adverse perinatal event. On the other hand, FGR fetuses, especially those under the 3rd centile for gestational age, are at increased risk of complications such as stillbirth, preterm delivery, perinatal morbidity and adverse long-term outcome, which however can be modified with timely intervention.^1,2

Fetal smallness can be diagnosed by ultrasound scan usually performed at about 32 weeks to assess estimated fetal weight (EFW). EFW and abdominal circumference (AC) are the strongest ultrasound parameters predicting fetal size.³ A large study in about 9,500 fetuses examined at 30–34 weeks found that in addition to EFW, maternal characteristics, mean arterial pressure, uterine artery Doppler studies and placental growth factor (PLGF) were significant predictors of fetal microsomia.⁴

Nevertheless, fetal smallness is only a substitute outcome because what we really need to diagnose is placental dysfunction causing fetal demise or complications precipitating delivery. As a result, it is necessary to add other parameters in order to predict whether a small fetus is at risk of an adverse event. Maternal history, maternal disease and increased resistance indices in the Doppler studies of the uterine arteries have been identified as parameters predicting placental dysfunction.⁵

The placenta releases many angiogenic factors into maternal circulation from the early gestational weeks. Angiogenesis-related factors, including sFlt-1 (soluble fms-like tyrosine kinase 1) and PLGF (placental growth factor), play an important role in placental dysfunction and altered levels are detectable several weeks before the onset of pregnancy complications. In the last few years angiogenic factors of placental origin have been correlated mainly with pre-eclampsia but also with FGR with or without pre-eclampsia. ^6–12

In the current study we investigated the contribution of PLGF in predicting the time interval from the initial visit to the occurrence of an adverse event (maternal or fetal) that requires medical attention and leads to delivery in pregnancies with microsomic fetuses.

Prospective study in singleton pregnancies referred to a tertiary hospital with suspicion of a small for gestational age (SGA) fetus. Patients were followed up in a special SGA clinic and they delivered in the same hospital.

Inclusion study criteria were: singleton pregnancy with no indication for nor any signs of imminent delivery, fetal abdominal circumference (AC) at or below the 10th centile and/or estimated fetal weight (EFW) at or below the 10th centile and/or umbilical artery pulsatility index (UA-PI) at or above the 90th centile for gestation. Women with pre-eclampsia at presentation were excluded.

In the first visit (index visit) maternal and paternal demographics were recorded (Astraia Fetal Database, Gembruch, Germany) and maternal blood was drawn for analysis. The following fetal/maternal parameters were recorded: bi-parietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), estimated fetal weight (EFW), deepest pool of amniotic fluid, umbilical artery pulsatility index (UA-PI), middle cerebral artery pulsatility index (MCA-PI), ductus venosus pulsatility index (DV-PI), mean uterine artery pulsatility index (Ut-PI), systolic and diastolic blood pressure (SBP and DBP respectively).

Fetal measurements were obtained according to the ISUOG guidelines.¹³ Maternal blood pressure was measured with an automated device (Microlife, AG). Pregnant women were seated in a relaxed position with the left arm placed comfortably at the level of the heart and the second of two consecutive measurements was recorded.

Maternal serum was stored at -4°C and analyzed in retrospect. PLGF was measured with Kryptor assay (Brahms Kryptor Compact PLUS) and PLGF results were converted to multiples of the median using the Fetal Medicine Foundation calculator of risk for pre-eclampsia (freely available form https://fetalmedicine.org). The results of PLGF were not made available to the clinicians.

Centiles were used for the analysis of the fetal parameters according to local protocols.

All pregnancies were followed up weekly. Maternal blood pressure and fetal biometry and Dopplers were recorded in every visit. In cases with signs of maternal or fetal compromise (development of hypertensive disorders and/or Doppler deterioration) fetal Doppler studies and heart rate monitoring (depending on availability) were performed more often.

We defined as adverse any event that occurred to the mother and/or the fetus that required medical attention or intervention and led to delivery. As such we classified: pre-eclampsia (defined as sustained elevated blood pressure ≥ 140/90 mmHg and significant proteinuria ≥ 300mgr in 24h urine collection or other end organ damage), fetal demise and deterioration of the fetal status (new occurrence of fetal Doppler abnormality, deterioration of fetal Doppler indices, deterioration of cardio-tocographic indices).¹⁴

The study was approved by the local ethics committee of the University of Athens Medical School and eligible women provided written informed consent.

Statistical analysis

Quantitative variables were expressed as mean (standard deviation) or as median (interquantile range). Qualitative variables were expressed as absolute and relative frequencies. ROC curves (Receiver operating characteristic curves) were used in order to estimate the predictive ability of PLGF and PLGF MoM for the adverse events. Sensitivity and specificity were calculated for optimal cut-offs. The association of each variable with adverse events was first assessed by univariate Cox regression analysis. Variables that showed significant association with the outcome were included in the multivariate Cox proportional-hazard model in a stepwise method in order to determine the independent predictors for adverse events. The assumption of proportional hazards was evaluated by testing for interaction with a continuous time variable. Hazard ratios (HR) with 95% confidence intervals (95% CI) were computed from the Cox regression analyses. All reported p values are two-tailed. Statistical significance was set at p < 0.05 and analyses were conducted using SPSS statistical software (version 22.0).

The study population consisted of 59 women. Maternal and fetal characteristics are presented in Table 1. The median incubation period from presentation to the clinic to an adverse event was 6,2 weeks. Half of the pregnancies (30 of 59 pregnancies, 52.5%) did not develop any adverse event. In the remaining 29 pregnancies 9 cases developed pre-eclampsia (15.25%), 18 cases showed deterioration on the fetal Doppler studies and/or on cardio-tocography, there was one intra-uterine death and one termination of the pregnancy. In the index visit 12 women were on low-dose aspirin, 7 on low molecular weight heparin and 2 were receiving both treatments. Figure 1 shows the Kaplan-Meier curve for the time elapsing between the first examination and the occurrence of an adverse event.

The results of the univariate analysis showed that gestational hypertension, greater systolic and diastolic blood pressure and increased PLGF (expressed either as raw values or as multiples of the median) were the maternal parameters associated with an adverse event (Table 2). Accordingly, fetal parameters related to an adverse event were low AC and EFW centile, increased UA PI and reduced CP ratio. In half of the cases (31 of the 59 cases, 52.5%) the mothers were normotensive and fetal Doppler parameters were normal in the index visit.

PLGF was the strongest predictor of adverse events. ROC analysis was performed for the prediction of adverse events by PLGF expressed in raw values and PLGF MOM (Fig. 2). PLGF raw values and PLGF MOM both had equally good predictive ability (AUC 0.82 and 0.78 respectively). Optimal cut-off points were 177.7pg/ml for PLGF raw values (sensitivity 83% and specificity 66.7%) and 0.277 MoM (sensitivity 76% and specificity 86.7%). Kaplan-Meier curves of PLGF raw values and PLGF MoM levels for the prediction of time to adverse events are shown in Fig. 3.

On multiple Cox regression analysis maternal systolic blood pressure and PLGF and fetal increased umbilical artery PI and reduced CP ratio were independently associated with adverse events (Table 3). PLGF raw values and PLGF MoM performed equally well in the analysis (hazard ratio 5.19 (95% CI: 1.69–15.9) for PLGF < 177.7pg/ml and hazard ratio 5.03 (95% CI: 1.79–14.15) for PLGF MoM).

Table 1. Maternal and fetal characteristics of the study population (N=59)

BMI=body mass index, SGA=small for gestational age, AC=fetal abdominal circumference, HC=fetal head circumference, FL= fetal femur length, EFW= estimated fetal weight, UA PI=umbilical artery pulsatility index, CP ratio=cerebro-placental ratio, SBP=systolic blood pressure, DBP=diastolic blood pressure, PLGF=placental growth factor, MoM=multiples of the median, SD=standard deviation, IQR=inter-quartile range.

Maternal and fetal parameters were recorded at the first (index) visit.

Table 2. Maternal and fetal parameters associated with adverse events by Univariate Cox regression analysis. BMI=body mass index, SGA=small for gestational age, AC=fetal abdominal circumference, HC=fetal head circumference, FL= fetal femur length, EFW= estimated fetal weight, UA PI=umbilical artery pulsatility index, CP ratio=cerebro-placental ratio, SBP=systolic blood pressure, DBP=diastolic blood pressure, PLGF=placental growth factor, MoM=multiples of the median, SD=standard deviation, IQR=inter-quartile range.

		Adverse event
		No (N=30; 50.8%)	Yes (N=29; 49.2%)
		N (%)	N (%)	HR (95% CI)+	P
Maternal age, mean (SD)		31.3 (5.8)	32.4 (5.2)	1.02 (0.95 - 1.08)	0.617
Maternal BMI, mean (SD)		24.1 (5.2)	24.3 (5.4)	1.02 (0.95 - 1.09)	0.646
BMI	Underweight/ Normal	20 (54.1)	17 (45.9)
BMI	Overweight/ Obese	10 (45.5)	12 (54.5)	1.36 (0.65 - 2.86)	0,415
Weight gain (up to first visit) , mean (SD)		8.6 (6.4)	8.5 (4.8)	1.00 (0.93 - 1.08)	0.968
Smoking	No	22 (47.8)	24 (52.2)
Smoking	Yes	8 (61.5)	5 (38.5)	0.67 (0.26 - 1.77)	0.423
Parity	0	15 (40.5)	22 (59.5)
Parity	>=1	15 (68.2)	7 (31.8)	0.50 (0.21 - 1.17)	0.111
Previous SGA	No	25 (49)	26 (51)
Previous SGA	Yes	5 (62.5)	3 (37.5)	0.70 (0.21 - 2.33)	0.563
Gestational hypertension	No	29 (53.7)	25 (46.3)
Gestational hypertension	Yes	1 (20)	4 (80)	4.08 (1.37 - 12.10)	0.011
Gestational diabetes	No	26 (50)	26 (50)
Gestational diabetes	Yes	4 (57.1)	3 (42.9)	1.16 (0.35 - 3.89)	0.805
Gestational age at SGA diagnosis, mean (SD)		31.7 (2.8)	30.3 (4)	0.98 (0.87 - 1.09)	0.698
AC centile, median (IQR)		8.4 (4.8 ─ 12.1)	2 (0.4 ─ 4.4)	0.85 (0.76 - 0.94)	0.002
HC centile, median (IQR)		10.3 (2.7 ─ 21.2)	3.5 (0.5 ─ 8.6)	0.97 (0.94 - 1.00)	0.057
FL centile, median (IQR)		11.2 (1.4 ─ 21.3)	3.8 (0.8 ─ 8.4)	0.97 (0.93 - 1.01)	0.093
EFW centile, median (IQR)		6.4 (3.5 ─ 10)	2.2 (0.7 ─ 4.5)	0.82 (0.72 - 0.93)	0.002
UA PI≥90^th	No	28 (60.9)	18 (39.1)
UA PI≥90^th	Yes	2 (15.4)	11 (84.6)	3.91 (1.81 - 8.45)	0.001
CP ratio≤10^th	No	24 (61.5)	15 (38.5)
CP ratio≤10^th	Yes	6 (30)	14 (70)	3.32 (1.57 - 7.03)	0.002
UT PI centile, median (IQR)		87 (61.1 ─ 99.3)	96.7 (79.7 ─ 100)	1.02 (1.00 - 1.03)	0.073
SBP, mean (SD)		109.8 (13.2)	124.5 (20.3)	1.03 (1.02 - 1.05)	<0.001
DBP, mean (SD)		71.3 (9.6)	81.9 (15.8)	1.05 (1.02 - 1.08)	0.001
PLGF (pg/ml), median (IQR)		211.2 (119.2 ─ 389.8)	55.4 (34.7 ─ 118.4)	0.59 (0.41 - 0.84)	0.003
PLGF (pg/ml) ≥177.7		20 (80.0)	5 (20.0)
<177.7		10 (29.4)	24 (70.6)	6.19 (2.33 – 16.43)	<0.001
PLGF MoM, median (IQR)		0.57 (0.3 ─ 0.86)	0.13 (0.06 ─ 0.28)	0.22 (0.07 - 0.73)	0.013

Table 3. Multivariate Cox regression analysis for the prediction of adverse events in the study population. UA-PI≥90=umbilical artery pulsatility index≥90^th centile, CP ratio≤10= cerebro-placental ratio ≤10^th centile, SBP=systolic blood pressure, PLGF=placental growth factor, MoM=multiples of the median

		HR (95% CI)+	P
UA PI≥90	No (reference)
UA PI≥90	Yes	2.48 (1.03 ─ 5.95)	0.042
CP ratio≤10	No (reference)
CP ratio≤10	Yes	2.73 (1.10 ─ 6.79)	0.030

SBP		1.03 (1.01-1.06)	0.005
PLGF MoM	>0.277 (reference)
	≤0.277	5.03 (1.79 - 14.15)	0.002

+Hazard Ratio (95% Confidence Interval)

Main findings

The study investigated the role of maternal and fetal parameters in predicting the time elapsing between the first (index) visit and the occurrence of an adverse event to the mother or the fetus that the clinician should act upon. The rationale was to customize the antenatal appointments according to the specific needs of each patient.

We found that half of the mother/fetus pairs did not have any symptoms of placental dysfunction at the index visit apart from fetal smallness, although median uterine artery PI centile was increased (Table 1). In addition, in half of the pregnancies no complications developed until the birth.

As expected, fetal Doppler abnormality and raised maternal blood pressure were associated with adverse events (Table 3). It is interesting that although our population comprised of very small fetuses, only abnormal fetal Doppler parameters and maternal systolic blood pressure and not EFW predicted the development of complications. Similarly, uterine Doppler indices did not have a contribution in the prediction. Indeed, the strongest predictor was maternal serum PLGF with optimal cut-off points at about 178pg/ml or 0.28MoM. In comparing using raw values to using MoM and we found no statistically significant difference (Fig. 2).

We observed that about 40% of the population will deliver because of complications in the first two weeks after the index visit and another 10% in the next two weeks, so by the end of the four weeks about half of the population will remain undelivered (Fig. 1). After that the slope of the curve flattens.

Using PLGF to study the time elapsing to an adverse event we observed that in pregnancies with low PLGF values more than half will be delivered in the first two weeks and by the end of the fourth week only about 30% will be still pregnant (Fig. 3). In contrast nine out of ten pregnancies with higher PLGF values will be undelivered in two weeks and about eight out of ten in four weeks after the initial visit.

Strengths and limitations

Our study examined prospectively a well-defined population of SGA fetuses and its design reflects the clinical problems arising in pregnancies referred with suspected fetal microsomia. The population is not restricted to the early onset disease but included fetuses at any gestation thus being more representative of the late SGA. In addition, the clinicians were unaware of the PLGF results and therefore this information did not alter the management.

The findings aid the clinician in counselling the mother on the prognosis using data available in the first visit as well as in planning further follow up. This is very helpful in directing the hospital resources to the pregnancies that will benefit more but also to keep out of the hospital the pregnant women that are likely to carry a ‘normal small’ fetus.

The main limitation of the study is the relatively small number of cases included. It may be that a larger sample would identify additional prognostic parameters as significant such as history of previous SGA birth, or strengthen the contribution of the existing parameters by using them as categorical variables, such as the PLGF. Because of restricted funding we were able to measure PLGF only, whereas other angiogenic factors, more notably sFlT 1, have been found to be informative on placental dysfunction.

Interpretation

PLGF and other angiogenic factors have mainly been studied as predictors of pre-eclampsia in all trimesters of pregnancy.^6,15,16 Furthermore PLGF and sFlT 1 levels have been shown to predict clinical deterioration and time to delivery in pre-eclamptic women.¹⁷

Τhe studies assessing the contribution of angiogenic/anti-angiogenic factors in predicting the outcome after the diagnosis of SGA are few. Chaiworapongsa et al examined 314 singleton pregnancies complicated with SGA before 34 weeks and found that abnormal plasma levels of angiogenic/anti-angiogenic factors increased the risk of pre-eclampsia up to 13 times and of iatrogenic preterm delivery up to 22 times.⁶ They report that adding biochemical markers increased the detection rate in cases with normal and abnormal umbilical Doppler studies, but the benefit was more pronounced in the first group. In the subgroup with raised uterine artery PI the additional gain of measuring biochemical factors was small. They propose a triage system based on first measuring uterine artery PI and subsequently biochemical markers in the pregnancies with normal uterine indices only.

In a small group of 16 SGA fetuses examined after 19 weeks Cretin et al observed the association of low PLGF levels with early delivery and highlighted that all cases with PLGF > 100pg/ml delivered at term.¹⁸

Quezada et al studied 120 early onset growth-restricted fetuses with increased umbilical artery PI and found that sFlT 1/PLGF < 85 identified a group with more favorable prognosis and longer latency period.⁹ Their results are actually very similar to ours as in the group with sFlT 1/PLGF ≥ 85 delivery within about 2 weeks occurred in about half of the pregnancies compared to only 7% if sFlT 1/PLGF < 85. These figures are identical to the ones reported in our study at the cut off of about 0.28 MoM, although we used PLGF alone.

In a retrospective study of 52 SGA fetuses Andrikos et al confirmed the negative correlation of sFlT 1/PLGF ratio with the time interval to delivery. Additionally, they reported that the estimated daily increase of the sFlT/PLGF ratio was more pronounced in the cases with shorter time to delivery.¹¹

However, the contribution of angiogenic/anti-angiogenic factors in predicting the outcome of SGA fetuses is not universally supported in the literature. Lobmaier et al in a population of 198 SGA fetuses diagnosed after 30 weeks found that the PLGF, sFlT and the sFlT 1/PLGF ratio did not increase the detection rates for predicting pre-eclampsia and fetal distress in labor over and above what can be achieved by maternal and fetal Doppler studies.¹⁹

The finding that once uterine artery PI is increased there is no additional benefit from measuring the biochemical markers is reported in the two largest cohorts examined. In our study this factor did not contribute to the prediction model, possibly because we included the measurement of maternal blood pressure which is a strong predictor of pre-eclampsia.

We showed PLGF is an important predictor of the time interval between diagnosis and development of complications in pregnancies with SGA fetuses. Half of the women with low PLGF levels deliver within a fortnight and almost 80% within a month of the diagnosis. In contrast about 90% of women with high PLGF levels remain pregnant four weeks after diagnosis. This data can be used to tailor antenatal visits according to PLGF levels. We propose that in the cases with low PLGF surveillance should be intense with at least twice weekly visits even in the absence of abnormal fetal Doppler studies, whereas when PLGF levels are high a repeat ultrasound examination in two weeks plus home monitoring of the blood pressure and fetal movements is adequate.

Funding

The authors received no financial support for the research, authorship and publication of this article.

Conflict of interest

The authors declare that they have no relevant financial or non-financial interests to disclose.

Author Contributions

Athena Souka: Project development, data collection, data analysis, manuscript writing.

Maria Ioanna Chatziioannou: Data collection, data analysis

Afrodite Pegkou: Data collection, data analysis

Panagiotis Antsaklis: Data analysis, manuscript writing.

George Daskalakis: Data analysis, manuscript writing.

Ethics approval / Consent to participate

The measurements used in the study were collected as part of the routine anomaly scan protocol in each unit, data were completely anonymized and not patient specific.

The unit approved the retrospective use of the data and ethics committee approval was not deemed necessary.

Lindqvist PG, Molin J. Does antenatal identification of small-for-gestational age fetuses significantly improve their outcome? Ultrasound Obstet Gynecol. 2005;25(3):258-64.
Sharp A, Jackson R, Cornforth C, Harrold J, Turner MA, Kenny L, Baker PN, Johnstone ED, Khalil A, von Dadelszen P, Papageorghiou AT, Alfirevic Z. A prediction model for short-term neonatal outcomes in severe early-onset fetal growth restriction. Eur J Obstet Gynecol Reprod Biol. 2019;241:109-118.
Papastefanou I, Pilalis A, Chrelias C, Kassanos D, Souka AP. Screening for birth weight deviations by second and third trimester ultrasound scan. Prenat Diagn. 2014 ;34(8):759-64.
Bakalis S, Peeva G, Gonzalez R, Poon LC, Nicolaides KH. Prediction of small-for-gestational-age neonates: screening by biophysical and biochemical markers at 30-34 weeks. Ultrasound Obstet Gynecol 2015; 46(4):446-51.
Tan MY, Syngelaki A, Poon LC, Rolnik DL, O'Gorman N, Delgado JL, Akolekar R, Konstantinidou L, Tsavdaridou M, Galeva S, Ajdacka U, Molina FS, Persico N, Jani JC, Plasencia W, Greco E, Papaioannou G, Wright A, Wright D, Nicolaides KH. Screening for pre-eclampsia by maternal factors and biomarkers at 11-13 weeks' gestation. Ultrasound Obstet Gynecol. 2018;52(2):186-195.
Chaiworapongsa T, Romero R, Whitten AE, Korzeniewski SJ, Chaemsaithong P, Hernandez-Andrade E, Yeo L, Hassan SS. The use of angiogenic biomarkers in maternal blood to identify which SGA fetuses will require a preterm delivery and mothers who will develop pre-eclampsia. J Matern Fetal Neonatal Med. 2016;29(8):1214-28.
Valiño N, Giunta G, Gallo DM, Akolekar R, Nicolaides KH. Biophysical and biochemical markers at 35-37 weeks' gestation in the prediction of adverse perinatal outcome. Ultrasound Obstet Gynecol. 2016 Feb;47(2):203-9.
Miranda J, Triunfo S, Rodriguez-Lopez M, Sairanen M, Kouru H, Parra-Saavedra, M, Crovetto F, Figueras F, Crispi F, Gratacós E. Performance of third-trimester combined screening model for prediction of adverse perinatal outcome. Ultrasound Obstet Gynecol. 2017;50(3):353-360.
Quezada MS, Rodriguez-Calvo J, Villalain C, Gomez-Arriaga PI, Galindo A, Herraiz I. sFlt-1/PlGF ratio and timing of delivery in early-onset fetal growth restriction with antegrade umbilical artery flow. Ultrasound Obstet Gynecol 2020; 56: 549–556.
Shim SH, Jeon HJ, Ryu HJ, Kim SH, Min SG, Kang MK, Park HJ, Cha DH. Prenatal serum sFlt-1/PlGF ratio predicts the adverse neonatal outcomes among small-for-gestational-age fetuses in normotensive pregnant women: A prospective cohort study. Medicine (Baltimore). 2021 Feb 26;100(8):e24681.
Andrikos A , Andrikos D, Schmidt B, Birdir C, Kimmig R, Gellhaus A, Köninger A. Course of the sFlt‑1/PlGF ratio in fetal growth restriction and correlation with biometric measurements, feto‑maternal Doppler parameters and time to delivery. Archives of Gynecology and Obstetrics 2022; 305:597–605.
Sherrell H, Dunn L, Clifton V, Kumar S. Systematic review of maternal Placental Growth Factor levels in late pregnancy as a predictor of adverse intrapartum and perinatal outcomes. Eur J Obstet Gynecol Reprod Biol. 2018;225:26-34.
ISUOG Practice Guidelines: ultrasound assessment of fetal biometry and growth. Ultrasound Obstet Gynecol 2019; 53: 715-723.
American College of Obstetricians and Gynecologists; Task Force on Hypertension in Pregnancy: Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists’ Task Force on Hypertension in Pregnancy. Obstet Gynecol 122: 1122–1131, 2013.
Wright D, Gallo DM, Gil Pugliese S, Casanova C, Nicolaides KH. Contingent screening for preterm pre-eclampsia. Ultrasound Obstet Gynecol 2016; 47: 554–559.
Agrawal S, Shinar S, Cerdeira AS, Redman C, Vatish M. Predictive performance of PlGF (Placental Growth Factor) for screening preeclampsia in asymptomatic women: a systematic review and meta-analysis. Hypertension. 2019;74(5):1124-1135.
Rana S, Powe CE, Salahuddin S, Verlohren S, Perschel FH, Levine RJ, Lim KH, Wenger JB, Thadhani R, Karumanchi SA. Angiogenic factors and the risk of adverse outcomes in women with suspected preeclampsia. Circulation 2012; 125: 911–919. 13.
Cetin I,Mazzocco MI, Giardini V, Cardellicchio M, Calabrese S, Algeri P, Martinelli A, Todyrenchuk L, Vergani P. PLGF in a clinical setting of pregnancies at risk of Preeclampsia and/or Intrauterine Growth Restriction. J Matern Fetal Neonatal Med 2017;30(2):144-149.
Lobmaier SM, Figueras F, Mercade I, Perello M, Peguero A, Crovetto F, Ortiz JU, Crispi F, Gratacos E. Angiogenic factors vs Doppler surveillance in the prediction of adverse outcome among late-pregnancy small-forgestational-age fetuses Ultrasound Obstet Gynecol 2014; 43: 533–540.

Figure 2 and 3 are not available with this version.

The role of the PLGF in the management of pregnancies complicated with fetal microsomia.

Status:

Journal Publication

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

What Does This Study Add To The Clinical Work

Introduction

Methods

Statistical analysis

Results

Discussion

Main findings

Strengths and limitations

Interpretation

Conclusion

Declarations

References

Figure 2 and 3

Status:

Journal Publication

Version 1