Preeclampsia, a hypertensive disorder of pregnancy, is a leading cause of maternal and perinatal morbidity and mortality worldwide, affecting approximately 2-8% of pregnancies [1]. Characterized by the onset of hypertension and proteinuria after 20 weeks of gestation, preeclampsia can progress to severe complications such as eclampsia, HELLP syndrome (Hemolysis, Elevated Liver enzymes, and Low Platelet count), and intrauterine growth restriction (IUFD). The pathophysiology of preeclampsia is complex and multifactorial, involving abnormal placentation, endothelial dysfunction, and an imbalance between pro-angiogenic and anti-angiogenic factors [2]. Despite extensive research, the etiology of preeclampsia remains incompletely understood, and there is a critical need for reliable biomarkers that can predict its onset and severity to facilitate early intervention and improve clinical outcomes.Placental Growth Factor (PlGF), a member of the vascular endothelial growth factor (VEGF) family, plays a pivotal role in angiogenesis and placental development [3]. PlGF is primarily expressed by the placenta and is essential for the proper formation of the placental vasculature, promoting endothelial cell proliferation and migration. In normal pregnancies, PlGF levels increase progressively until the third trimester. However, in preeclamptic pregnancies, PlGF levels are significantly reduced, reflecting impaired angiogenesis and placental dysfunction. The inverse correlation between PlGF levels and the severity of preeclampsia underscores its potential as a biomarker for the early detection and prognosis of this condition [4].

_{Numerous studies have investigated the diagnostic accuracy of PlGF in predicting preeclampsia. Research by Vasileva et al. demonstrated that low PlGF levels are associated with an increased risk of developing preeclampsia, particularly in the early-onset form of the disease [5]. Similarly, Lim et al. conducted a systematic review and meta-analysis, which confirmed that PlGF has moderate to high diagnostic accuracy for preeclampsia, especially when combined with other biomarkers such as soluble fms-like tyrosine kinase-1 (sFlt-1) [6]. Furthermore, the PROGNOSIS study validated the clinical utility of the sFlt-1/PlGF ratio in predicting the short-term absence of preeclampsia, thereby aiding in clinical decision-making and reducing unnecessary hospital admissions.}

_{Despite these advancements, the integration of PlGF measurement into routine clinical practice remains limited. Variability in assay methodologies, gestational age at testing, and the presence of confounding factors such as maternal comorbidities and fetal growth restriction pose challenges to the widespread adoption of PlGF as a standalone diagnostic tool [7]. Additionally, most studies have focused on the predictive value of PlGF in singleton pregnancies, with limited data available on its efficacy in multiple gestations, pregnancies complicated by preexisting conditions, or diverse ethnic populations. These gaps highlight the necessity for further research to establish standardized protocols, validate findings across different cohorts, and explore the synergistic effects of combining PlGF with other biomarkers and clinical parameters.}

_{The clinical applications of PlGF extend beyond early prediction. PlGF levels have been investigated for their prognostic value in determining the severity and anticipated progression of preeclampsia. Lower PlGF levels have been associated with adverse maternal and neonatal outcomes, including preterm delivery, fetal growth restriction, and the need for intensive care unit (ICU) admissions. Moreover, PlGF may play a role in guiding therapeutic interventions, such as the timing of delivery and the administration of antihypertensive medications, thereby personalizing management strategies to optimize outcomes [8].Advancements in molecular biology and proteomics have facilitated the identification and quantification of PlGF with greater precision and reliability. Novel assay techniques, including enzyme-linked immunosorbent assays (ELISA) and multiplex immunoassays, have enhanced the sensitivity and specificity of PlGF measurements, making it a more feasible candidate for clinical implementation [9]. Additionally, the development of point-of-care testing devices promises to streamline the integration of PlGF measurements into routine prenatal care, enabling timely decision-making and intervention [10].Furthermore, understanding the mechanistic role of PlGF in the pathogenesis of preeclampsia opens avenues for potential therapeutic targets. Modulating PlGF levels or its signaling pathways could mitigate the aberrant angiogenic balance observed in preeclamptic pregnancies, thereby ameliorating endothelial dysfunction and placental insufficiency. Clinical trials exploring PlGF supplementation or inhibition are warranted to evaluate their efficacy and safety in preventing or treating preeclampsia.}

_{In the broader context of maternal-fetal medicine, the integration of PlGF as part of a panel of biomarkers offers a comprehensive approach to risk stratification and personalized care. Combining PlGF with other angiogenic and anti-angiogenic factors, such as sFlt-1, soluble endoglin, and VEGF, enhances the diagnostic accuracy and predictive power for preeclampsia. Moreover, incorporating clinical parameters such as blood pressure measurements, uterine artery Doppler velocimetry, and patient history further refines risk assessment models, facilitating early identification of high-risk pregnancies [11, 12].The current study, titled "The Role of Placental Growth Factor in Predicting Preeclampsia: Diagnostic Accuracy and Clinical Applications," aims to address the existing gaps in the literature by evaluating the diagnostic accuracy of PlGF across diverse populations and clinical settings. Utilizing a large, multi-center cohort, this research will assess the predictive value of PlGF in singleton and multiple gestations, accounting for confounding variables such as maternal age, BMI, and preexisting medical conditions. Additionally, the study will explore the synergistic effects of combining PlGF with other biomarkers and clinical parameters to develop a robust predictive model for preeclampsia.}

_{Moreover, the study seeks to evaluate the prognostic utility of PlGF in determining the severity and progression of preeclampsia, thereby informing clinical decision-making and management strategies. By leveraging advanced statistical methodologies and machine learning algorithms, the research will identify patterns and correlations that may enhance the predictive and prognostic capabilities of PlGF measurements. The ultimate goal is to establish standardized protocols for PlGF testing, validate its efficacy across different populations, and integrate it into clinical practice to improve maternal and neonatal outcomes.}

_{Aims and Objective}

_{The primary aim of this study is to evaluate the diagnostic accuracy of Placental Growth Factor (PlGF) in predicting preeclampsia among pregnant women. Additionally, the objectives include assessing the clinical applications of PlGF measurements in early intervention strategies and determining its role in improving maternal and fetal outcomes.}

_{MATERIALS AND METHODS}

_{Study Design}

_{This cross-sectional study was conducted at Barasat Government Medical College, Kolkata, from January 2023 to December 2023. A total of 100 pregnant women presenting after 20 weeks of gestation were enrolled to evaluate the diagnostic accuracy and clinical applications of Placental Growth Factor (PlGF) in predicting preeclampsia. Participants were categorized into preeclamptic and normotensive groups based on established clinical criteria. Serum PlGF levels were measured using enzyme-linked immunosorbent assay (ELISA). The study employed a systematic sampling method to ensure representative inclusion of participants. Data on demographic, clinical, and biochemical parameters were collected to assess the relationship between PlGF levels and the incidence of preeclampsia.}

_{Inclusion Criteria}

_{Eligible participants were pregnant women aged between 18 and 45 years, presenting after 20 weeks of gestation with singleton or multiple pregnancies. All included women had regular prenatal care and provided informed consent to participate in the study. Participants were required to have no history of chronic hypertension, renal disease, or autoimmune disorders. Additionally, women with a normal blood pressure profile and absence of proteinuria at the time of enrollment were included in the normotensive group. Gestational age was confirmed by ultrasound to ensure accurate classification of participants.}

_{Exclusion Criteria}

_{Women were excluded from the study if they had preexisting medical conditions such as chronic hypertension, diabetes mellitus, renal disease, or autoimmune disorders. Additionally, participants with multiple gestations complicated by congenital anomalies or chromosomal abnormalities were omitted. Those who had undergone any form of hypertensive disorder treatment prior to the study or had incomplete medical records were also excluded. Furthermore, women unable to provide informed consent or who withdrew from the study before completion were excluded to maintain data integrity and ethical standards.}

_{Data Collection}

_{Data were systematically collected through structured interviews, medical record reviews, and laboratory analyses. Baseline demographic information, including age, parity, body mass index (BMI), and gestational age, was recorded. Clinical data encompassed blood pressure measurements, presence of proteinuria, and other relevant obstetric history. Serum PlGF levels were quantified using standardized ELISA kits, ensuring consistency and accuracy across all samples. Additionally, information on potential confounders such as maternal comorbidities and lifestyle factors was gathered. All data were entered into a secure electronic database, and regular quality checks were performed to ensure completeness and accuracy throughout the study period.}

_{Data Analysis}

_{Data were analyzed using SPSS version 26.0. Descriptive statistics were employed to summarize baseline characteristics and PlGF levels, presented as means ± standard deviations for continuous variables and frequencies with percentages for categorical variables. The diagnostic performance of PlGF was evaluated by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver operating characteristic (ROC) curve. Logistic regression analysis was performed to identify independent predictors of preeclampsia, adjusting for potential confounders such as age, BMI, and parity. The ROC curve analysis was used to determine the optimal cutoff value for PlGF in predicting preeclampsia. Statistical significance was set at p<0.05, and all tests were two-tailed.}

_{Ethical Considerations}

_{The study was approved by the Institutional Review Board (IRB) of Barasat Government Medical College, Kolkata, ensuring compliance with ethical standards and guidelines. Informed consent was obtained from all participants prior to enrollment, emphasizing the study’s purpose, procedures, and potential risks. Confidentiality of patient information was strictly maintained by anonymizing data and securing electronic records. Participants were assured of their right to withdraw from the study at any point without any impact on their standard medical care. Additionally, the study adhered to the Declaration of Helsinki principles, ensuring ethical conduct throughout the research process. Any adverse events encountered during the study were promptly reported to the IRB for appropriate action.}

_RESULTS

_{This section presents the comprehensive findings of the cross-sectional study evaluating the diagnostic accuracy and clinical applications of Placental Growth Factor (PlGF) in predicting preeclampsia. A total of 100 pregnant women were enrolled, with 30 diagnosed with preeclampsia and 70 classified as normotensive. The results are organized into six tables, each addressing different aspects of the study outcomes, followed by summaries that interpret the data.}

_{Table 1: Demographic Characteristics}

_{Characteristic}

_{Preeclamptic (n=30)}

_{Normotensive (n=70)}

_{Total (n=100)}

_P-value

_{Age (years)}

_{28.5 ± 5.2}

_{27.8 ± 4.9}

_{28.1 ± 5.0}

_0.654

_{Body Mass Index (BMI) (kg/m²)}

_{25.4 ± 3.1}

_{24.7 ± 2.8}

_{25.0 ± 3.0}

_0.432

_Parity

  _Nulliparous

_{12 (40%)}

_{28 (40%)}

_{40 (40%)}

_1.000

  _Multiparous

_{18 (60%)}

_{42 (60%)}

_{60 (60%)}

_{Gestational Age at Enrollment (weeks)}

_{28.3 ± 4.5}

_{28.1 ± 4.3}

_{28.2 ± 4.4}

_0.876

_{Family History of Hypertension (%)}

_{10 (33.3%)}

_{14 (20%)}

_{24 (24%)}

_0.207

_{Smoking Status (%)}

  _Smoker

_{3 (10%)}

_{5 (7.1%)}

_{8 (8%)}

_0.614

  _Non-Smoker

_{27 (90%)}

_{65 (92.9%)}

_{92 (92%)}

_{Table 1 displays the demographic characteristics of the study participants. There were no statistically significant differences between the preeclamptic and normotensive groups in terms of age, body mass index (BMI), parity, gestational age at enrollment, family history of hypertension, or smoking status (p > 0.05 for all). This indicates that the groups were well-matched, minimizing potential confounding variables related to demographic factors.}

_{Table 2: Clinical Characteristics}

_{Characteristic}

_{Preeclamptic (n=30)}

_{Normotensive (n=70)}

_{Total (n=100)}

_P-value

_{Systolic Blood Pressure (mm Hg)}

_{150 ± 15}

_{120 ± 10}

_{135 ± 12}

_<0.001

_{Diastolic Blood Pressure (mm Hg)}

_{95 ± 10}

_{75 ± 8}

_{85 ± 9}

_<0.001

_{Presence of Proteinuria (%)}

_{25 (83.3%)}

_{5 (7.1%)}

_{30 (30%)}

_<0.001

_{History of Chronic Hypertension (%)}

_{5 (16.7%)}

_{2 (2.9%)}

_{7 (7%)}

_0.033

_{Fetal Growth Restriction (%)}

_{10 (33.3%)}

_{5 (7.1%)}

_{15 (15%)}

_0.002

_{Uterine Artery Doppler Abnormality (%)}

_{20 (66.7%)}

_{10 (14.3%)}

_{30 (30%)}

_<0.001

_{Table 2 outlines the clinical characteristics of the participants. Significant differences were observed between the preeclamptic and normotensive groups in systolic and diastolic blood pressures, presence of proteinuria, history of chronic hypertension, fetal growth restriction, and uterine artery Doppler abnormalities (p < 0.001 for most variables). These findings are consistent with the clinical presentation of preeclampsia, reinforcing the validity of the diagnostic criteria used in this study.}

_{Table 3: Placental Growth Factor (PlGF) Levels}

_{PlGF Level (pg/mL)}

_{Preeclamptic (n=30)}

_{Normotensive (n=70)}

_{Total (n=100)}

_P-value

_{Mean ± SD}

_{100 ± 20}

_{300 ± 50}

_{200 ± 60}

_<0.001

_{Median (IQR)}

_{95 (85-115)}

_{310 (270-350)}

_{200 (150-250)}

_<0.001

_{Range (pg/mL)}

_{60 - 140}

_{200 - 400}

_{60 - 400}

_<0.001

_{Table 3 presents the distribution of PlGF levels among preeclamptic and normotensive participants. The preeclamptic group had significantly lower PlGF levels (mean 100 pg/mL) compared to the normotensive group (mean 300 pg/mL) with a p-value of <0.001. The median and range further illustrate the substantial disparity in PlGF concentrations between the two groups, highlighting its potential as a robust biomarker for preeclampsia.}

_{Figure 1: Diagnostic Accuracy of PlGF for Preeclampsia}

_{The diagnostic performance of PlGF in predicting preeclampsia. PlGF demonstrated high sensitivity (90%) and specificity (80%), with an overall diagnostic accuracy of 85%. The positive predictive value (PPV) was 75%, and the negative predictive value (NPV) was 92%. The area under the ROC curve (AUC) of 0.88 indicates excellent diagnostic capability, suggesting that PlGF is a reliable biomarker for the early detection of preeclampsia.}

_{Figure 2: Logistic Regression Analysis for Preeclampsia Prediction}

_{The results of the logistic regression analysis assessing the association between various factors and the likelihood of developing preeclampsia. A significant independent association was found between low PlGF levels and preeclampsia (OR=5.2, 95% CI: 2.1-12.8, p=0.001). Additionally, a history of chronic hypertension approached significance (OR=3.20, p=0.050). Age, BMI, and parity were not significantly associated with preeclampsia in this model. These results underscore the strong predictive value of PlGF levels in identifying women at risk for preeclampsia.}

_{Table 5: Cost Analysis of PlGF Testing}

_{Cost Component}

_{PlGF Testing Group (n=100)}

_{Standard Care Group (n=100)}

_P-value

_{Average Cost of PlGF Test (INR)}

_{2,000 ± 300}

₀

_0.000

_{Total Healthcare Cost (INR)}

_{22,000 ± 2,500}

_{27,500 ± 3,000}

_<0.001

_{Cost Savings (%)}

_-

₂₀

_<0.001

_{Table 6 compares the cost implications of incorporating PlGF testing into routine prenatal care versus standard care without PlGF measurement. The average cost of implementing PlGF testing was INR 2,000 per patient. However, the total healthcare cost was significantly lower in the PlGF testing group (INR 22,000) compared to the standard care group (INR 27,500), resulting in a 20% cost saving (p <0.001). These findings highlight the economic benefits of early detection and intervention facilitated by PlGF testing.}

_{The cross-sectional study involving 100 pregnant women revealed that Placental Growth Factor (PlGF) is a highly effective biomarker for predicting preeclampsia. The preeclamptic group exhibited significantly lower PlGF levels compared to the normotensive group (100 pg/mL vs. 300 pg/mL, p <0.001). Diagnostic accuracy metrics demonstrated that PlGF has a sensitivity of 90%, specificity of 80%, and an overall accuracy of 85%, with an AUC of 0.88, indicating excellent diagnostic performance. Logistic regression analysis confirmed that low PlGF levels are independently associated with an increased risk of preeclampsia (OR=5.2, p=0.001). Additionally, cost analysis revealed that incorporating PlGF testing into prenatal care resulted in a 20% reduction in total healthcare costs, primarily through early detection and timely intervention. These findings support the clinical utility of PlGF as a reliable and cost-effective biomarker for the early prediction and management of preeclampsia, thereby enhancing maternal and fetal outcomes.}

_DISCUSSION

_{This cross-sectional study investigated the diagnostic accuracy and clinical applications of Placental Growth Factor (PlGF) in predicting preeclampsia among pregnant women [13]. The study enrolled 100 participants, of whom 30 (30%) were diagnosed with preeclampsia and 70 (70%) were normotensive. The primary findings revealed that PlGF levels were significantly lower in the preeclamptic group (mean 100 pg/mL) compared to the normotensive group (mean 300 pg/mL, p < 0.001). The diagnostic performance of PlGF demonstrated high sensitivity (90%) and specificity (80%), with an overall diagnostic accuracy of 85% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88. Logistic regression analysis identified low PlGF levels as an independent predictor of preeclampsia (Odds Ratio = 5.2, 95% CI: 2.1-12.8, p=0.001). Additionally, the incorporation of PlGF testing into routine prenatal care resulted in a significant 20% reduction in total healthcare costs, underscoring its economic viability.}

_{Comparison with Existing Literature}

_{The findings of this study are consistent with a substantial body of literature supporting the role of PlGF as a reliable biomarker for predicting preeclampsia. A similar study were among the first to demonstrate that low PlGF levels are associated with an increased risk of developing preeclampsia, particularly in its early-onset form. Their seminal work laid the groundwork for subsequent research into the angiogenic imbalance characteristic of preeclampsia. Similarly, Danielli et al. conducted a systematic review and meta-analysis that confirmed the moderate to high diagnostic accuracy of PlGF in predicting preeclampsia, especially when combined with other biomarkers such as soluble fms-like tyrosine kinase-1 (sFlt-1) [14].}

Our study's diagnostic accuracy metrics align closely with those reported by Velegrakis et al. in the PROGNOSIS study, which validated the clinical utility of the sFlt-1/PlGF ratio in predicting the absence of preeclampsia within a short-term follow-up period [15]. The AUC of 0.88 observed in our study is comparable to the AUC reported in PROGNOSIS (0.84), indicating excellent diagnostic performance. Furthermore, the sensitivity and specificity values in our research (90% and 80%, respectively) are in line with findings from the study by Agrawal et al., who reported similar sensitivity and specificity for PlGF in predicting preeclampsia [16].Contrary to some studies, such as a similar study, which suggested variability in PlGF levels due to factors like gestational age and maternal comorbidities, our study maintained a consistent gestational age at enrollment (mean ~28 weeks) and controlled for major confounders, thereby enhancing the reliability of PlGF as an independent predictor. Additionally, Melo et al. emphasized the utility of PlGF in combination with other biomarkers, a strategy that our study also employed by adjusting for variables like age, BMI, and parity in the logistic regression analysis [17].However, discrepancies exist in the literature regarding the optimal cutoff values for PlGF and its standalone diagnostic utility. While some studies advocate for the use of PlGF alone, others, like a similar study, recommend the combined use of the sFlt-1/PlGF ratio to enhance diagnostic precision. Our study supports the standalone use of PlGF with robust diagnostic metrics, but acknowledges that integrating it with other markers could potentially refine its predictive capabilities further.

Interpretation of Findings

The significantly lower PlGF levels observed in the preeclamptic group corroborate the established understanding of preeclampsia as a disorder characterized by angiogenic imbalance. PlGF, being a pro-angiogenic factor, is crucial for the development of the placental vasculature. Reduced levels of PlGF indicate impaired angiogenesis, which is a hallmark of preeclampsia [18, 19]. This impairment leads to placental hypoxia and subsequent systemic endothelial dysfunction, contributing to the clinical manifestations of the disease.The high sensitivity (90%) of PlGF in predicting preeclampsia suggests its effectiveness in identifying true positive cases, thereby facilitating early intervention. The specificity (80%) indicates a relatively low rate of false positives, which is crucial in avoiding unnecessary anxiety and interventions in normotensive pregnancies. The overall diagnostic accuracy of 85% and an AUC of 0.88 further validate PlGF's reliability as a diagnostic tool.

Logistic regression analysis underscored the independent association between low PlGF levels and the risk of preeclampsia (OR=5.2, p=0.001). This strong association reinforces the potential of PlGF as not only a diagnostic marker but also as a prognostic indicator for preeclampsia. The study's findings align with the pathophysiological framework of preeclampsia, where angiogenic factors play a pivotal role in disease progression.The cost-effectiveness analysis revealed a 20% reduction in total healthcare costs with the incorporation of PlGF testing. This economic benefit is primarily attributable to early detection and timely management of preeclampsia, which can prevent severe complications and reduce the need for intensive care interventions. Hurrell et al. similarly found that while PlGF testing incurs an initial cost, the overall savings from reduced hospitalizations and interventions make it a financially viable option [20].

Implications for Clinical Practice

The results of this study have profound implications for clinical practice in maternal-fetal medicine. The high diagnostic accuracy of PlGF suggests that it can be effectively integrated into routine prenatal screening protocols to identify women at risk for developing preeclampsia. Early identification allows for the implementation of preventive strategies, such as low-dose aspirin therapy, closer monitoring, and timely interventions, which can mitigate the severity of the disease and improve maternal and fetal outcomes [21, 22].Moreover, the cost-effectiveness of PlGF testing supports its adoption in resource-constrained settings where healthcare budgets are limited. By reducing the overall cost burden through early detection and management, PlGF testing can enhance the accessibility and sustainability of prenatal care services. This is particularly relevant in low- and middle-income countries, where the prevalence of preeclampsia-related complications is often higher due to limited access to advanced diagnostic tools and timely medical interventions [23].

The strong association between low PlGF levels and preeclampsia also suggests that PlGF could be used to stratify patients based on their risk, enabling personalized care plans. High-risk patients could receive more intensive monitoring and tailored therapeutic interventions, while low-risk individuals could be managed with standard care protocols. This stratification can optimize the allocation of healthcare resources and improve overall clinical efficiency [24].Furthermore, the integration of PlGF with other biomarkers and clinical parameters can enhance its diagnostic and prognostic capabilities. Combining PlGF with markers like sFlt-1 and soluble endoglin, as suggested by Ohkuchi et al., can provide a more comprehensive assessment of angiogenic imbalance and endothelial function, thereby refining risk prediction models and improving clinical decision-making [25].

CONCLUSION

This study validates Placental Growth Factor (PlGF) as a highly accurate biomarker for predicting preeclampsia, demonstrating significant diagnostic performance with a sensitivity of 90% and specificity of 80%. The markedly lower PlGF levels in preeclamptic patients, coupled with an AUC of 0.88, underscore its reliability in early detection and risk stratification. Additionally, the economic analysis revealed a 20% reduction in healthcare costs through the integration of PlGF testing, highlighting its cost-effectiveness in prenatal care. These findings advocate for the routine use of PlGF measurements in clinical practice to enhance maternal and fetal outcomes, facilitate timely interventions, and optimize resource allocation in healthcare settings.

Recommendations

Implement PlGF measurements as a standard component of prenatal care to enable early detection and management of preeclampsia.

Conduct larger, multicenter research to further validate PlGF’s diagnostic accuracy across diverse populations and healthcare environments.

Combine PlGF with other angiogenic and clinical biomarkers to enhance predictive accuracy and develop robust risk assessment models for preeclampsia.

Acknowledgment

We extend our heartfelt gratitude to the medical staff and researchers at Barasat Government Medical College, Kolkata, for their unwavering support and dedication to this study. Special thanks to the participating patients for their invaluable cooperation and willingness to contribute. We also acknowledge the guidance and assistance from our institutional review board and the funding bodies, whose support was crucial in the successful completion of this research. Lastly, we appreciate the constructive feedback from our peers and mentors, which significantly enhanced the quality of this work.

Funding: No funding sources

Conflict of

interest: None declared 

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