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April 15, 2026International Journal of Molecular SciencesOpen Access

Rethinking Risk Prediction in Preeclampsia: From Biomarkers to Mechanistic Phenotypes and Longitudinal Models

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Authors

SESalvador Espino‐y‐SosaEMElsa Romelia Moreno‐VerduzcoIMIrma Eloisa Monroy-Muñoz

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Overview

Narrative review shows integrating biological variability enhances risk prediction in preeclampsia, suggesting new clinical approaches.

Key Points

  • This review aims to improve risk prediction strategies for preeclampsia by addressing biological heterogeneity and integrating temporal dynamics.
  • Synthesis of existing evidence on biomarkers and predictive modeling approaches
  • Examination of mechanistic phenotypes and their contributions across pregnancy
  • Discussion of classical statistical and machine learning techniques for risk prediction
  • Highlights the inadequacy of static thresholds for risk prediction in preeclampsia
  • Emphasizes the importance of longitudinal risk trajectories rather than binary classification
  • Identifies key research priorities for future predictive studies including dynamic updates and clinical decision linkage

Cite This Study

Espino‐y‐Sosa et al. (2026) studied this question.

synapsesocial.com/papers/69df2cb9e4eeef8a2a6b1f84https://doi.org/10.3390/ijms27083480
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Predictive Power of Biomarkers in Preeclampsia in Singleton Pregnancies: A Comprehensive Review of Current Evidence and Future Directions2025 · 1 citations
  2. 2Molecular Subtypes of Preeclampsia and the Emergence of Precision Obstetric Phenotyping: A Systematic Review of Transcriptomic, Multiomic, and Clinical Integration Frameworks2026
  3. 3Phenotype-stratified Targeted Therapy for Preeclampsia: A Biomarker-guided, Mechanism-driven Systematic Review Integrating Oxidative Stress, Metabolic Dysfunction, Immune Injury, and Placental Vasculopathy2026
  4. 4A comprehensive first-trimester predictive model for preeclampsia based on multi-indicators and machine learning: A retrospective single-center study2025 · 6 citations
  5. 5Preeclampsia: Contemporary Concepts in Pathophysiology, Risk Stratification, Prevention and Monitoring2026 · 4 citations