For millions of couples worldwide, assisted reproductive technology has turned the dream of parenthood into reality. More than three million ART cycles are now performed every year, and the indications for treatment continue to expand. But as the use of in vitro fertilization, frozen embryo transfer and oocyte donation has grown, so has evidence that pregnancies conceived through these techniques carry a nearly doubled risk of hypertensive disorders, including preeclampsia. A new systematic review published in Reproductive Sciences by researchers from Leiden University Medical Center and Erasmus Medical Center in the Netherlands has now examined whether any of the many clinical prediction models for preeclampsia can adequately capture that risk in ART pregnancies. The answer, strikingly, is no.
Preeclampsia is a pregnancy complication characterized by new-onset hypertension accompanied by proteinuria, maternal end-organ dysfunction, or uteroplacental dysfunction. When it goes unrecognized or untreated, it remains one of the leading causes of maternal mortality. The consequences extend well beyond delivery: hypertensive complications in pregnancy are linked to long-term maternal cardiovascular disease and reduced quality of life, while severe disease increases the risk of fetal growth restriction and preterm birth through underlying placental insufficiency. Timely identification of women at risk is therefore a central goal of modern obstetric medicine, and a growing library of prediction models has been developed to flag high-risk pregnancies before symptoms appear.
Why would ART pregnancies be more vulnerable in the first place? The review outlines several converging explanations. The need for ART itself may reflect underlying reproductive characteristics associated with elevated preeclampsia risk, including advanced maternal age, nulliparity after prolonged infertility, and specific infertility diagnoses. More provocatively, recent evidence suggests that certain ART-related factors may causally contribute to risk. Programmed frozen embryo transfer cycles, for example, lack a corpus luteum and its vasoactive products, and multiple embryo transfers can produce multiple gestations, both of which are associated with hypertensive complications. Altered maternal-fetal immune interactions, particularly evident in oocyte donation pregnancies, have also been hypothesized to play a role in the development of the disease.
Despite this well-established link, the researchers found that preeclampsia prediction models almost never account for how a pregnancy was conceived. The team, led by Géraldine Lafeber, systematically searched MEDLINE for studies published between January 2017 and July 2023, updating a previous systematic review from 2019. Out of 15,305 records initially identified, 161 articles were assessed in full text, ultimately yielding fifteen eligible studies; eleven more were added from the earlier review, for a total of twenty-six articles describing models that included ART as a predictor. Remarkably, across the roughly 231 prediction models identified in the literature, not a single one had been developed specifically for the ART population.
The included studies spanned 2009 to 2023 and collectively involved 625,001 participants, of whom 20,142 developed preeclampsia. Most were conducted in Europe, with six studies from Asia and one from North America. The models fell into two broad statistical families. Frequentist models estimate parameters based on observations alone, using metrics such as confidence intervals and p-values, while Bayesian models incorporate prior knowledge, updating beliefs as new data become available to produce probability distributions for model parameters. Some studies even applied machine learning approaches, including random forest, XGBoost and support vector machines. Predictors typically combined clinical parameters with biomarkers such as the uterine artery pulsatility index, mean arterial pressure, placental growth factor and pregnancy-associated plasma protein A.
Performance varied enormously. Discrimination, measured by the area under the receiver operating characteristic curve, ranged from a nearly useless 0.58 to an almost perfect 0.99. A value of 0.5 indicates performance no better than random guessing, while 1.0 indicates perfect discrimination. Bayesian models consistently improved when biomarkers were added to maternal factors alone. Yet the headline numbers conceal deeper problems: calibration, which assesses whether predicted probabilities actually match observed outcome frequencies, was rarely reported. Only seven of the twenty-six models had ever been externally validated in an independent population, a step widely considered essential before any prediction model is used in clinical practice.
The methodological quality assessment, conducted with the PROBAST tool, revealed that risk of bias was unclear in most studies, twenty-one of the twenty-six, largely due to analytical issues. Some studies excluded patients with missing outcome data without justification, and many reported too few events per variable, raising the risk of model overfitting. Outcome definitions of preeclampsia varied widely across studies, drawing on different guidelines published over decades, which complicates comparability and generalizability. Reporting quality, assessed against the TRIPOD checklist, ranged from 41 to 89 percent of applicable items met. Only seven studies described their variable selection and model building process in detail, and just three published their full models with individual coefficients, making independent reproduction effectively impossible.
One of the most intriguing findings concerns how ART itself was handled. In most frequentist models, ART was reduced to a simple yes-or-no variable, and in some Bayesian models the method of conception was buried within unspecified maternal factors, requiring the reviewers to contact study authors for clarification. Almost no model distinguished between IVF, ICSI, frozen or thawed embryo transfer and oocyte donation, despite substantial variation in preeclampsia risk across these treatment modalities. The risk of hypertensive complications in oocyte donation is more than double that seen with conventional IVF and ICSI, and embryo or double donation may carry an even higher risk. Treating ART as a single homogeneous category, the authors argue, may seriously compromise risk assessment for the very patients who need it most.
There was also a telling inverse relationship between apparent performance and transparency. The models reporting the highest discrimination had the lowest reporting scores, leaving it unclear whether outcome and predictor assessment were blinded, how predictions were calculated, how missing data were handled, or how the model should be used. None of the studies presented their models as online calculators for clinicians or patients. The reviewers note that despite the publication of the TRIPOD statement in 2015, which was designed to improve exactly these shortcomings, reporting quality does not appear to have improved over time.
The review does have limitations the authors acknowledge, including reliance on a single database, MEDLINE, and a gap between the July 2023 search end date and manuscript completion. Nonetheless, its conclusion is unambiguous: no existing prediction model can be endorsed for clinical use in ART pregnancies. The team argues that future research should prioritize developing a high-quality model that incorporates ART, ideally disaggregated by treatment type, and that such a model should be developed and validated within ART populations specifically. Better risk assessment could support periconceptional counselling, improve early recognition of disease, deepen understanding of preeclampsia pathophysiology, and even help minimize donor exposure to the risks associated with oocyte retrieval. The researchers themselves are already working toward a dedicated prediction model for hypertensive complications in oocyte and double donation pregnancies, following PROBAST and TRIPOD guidelines. For the growing population of families conceived through reproductive technology, that work cannot come soon enough.
Subject of Research: Prediction models for preeclampsia risk in assisted reproductive technology pregnancies
Article Title: Assisted Reproductive Technology as Predictor for Preeclampsia: A Systematic Review of Current Clinical Prediction Models
Article References: Lafeber, G. C. M., van der Hoorn, M.-L. P., le Cessie, S., & Lashley, E. E. L. O. (2026). Assisted Reproductive Technology as Predictor for Preeclampsia: A Systematic Review of Current Clinical Prediction Models. Reproductive Sciences. https://doi.org/10.1007/s43032-026-02168-7
Image Credits: AI Generated
DOI: 10.1007/s43032-026-02168-7
Keywords: assisted reproductive technology, preeclampsia, prediction models, IVF, oocyte donation, systematic review, PROBAST, TRIPOD, hypertensive disorders, maternal health, reproductive medicine, external validation
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Harold Sullivan. (October 1, 2026). IVF Pregnancies Face Higher Preeclampsia Risk, Yet No Reliable Prediction Model Exists. Scienmag. https://scienmag.com/ivf-pregnancies-face-higher-preeclampsia-risk-yet-no-reliable-prediction-model-exists/
Harold Sullivan. “IVF Pregnancies Face Higher Preeclampsia Risk, Yet No Reliable Prediction Model Exists.” Scienmag, 1 October 2026, https://scienmag.com/ivf-pregnancies-face-higher-preeclampsia-risk-yet-no-reliable-prediction-model-exists/. Accessed 1 October 2026.
Harold Sullivan. “IVF Pregnancies Face Higher Preeclampsia Risk, Yet No Reliable Prediction Model Exists.” Scienmag. October 1, 2026. https://scienmag.com/ivf-pregnancies-face-higher-preeclampsia-risk-yet-no-reliable-prediction-model-exists/
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Tags: ART and maternal healthassisted reproductive technologyclinical prediction challenges in pregnancyexternal validationhypertensive disordershypertensive disorders in pregnancyin vitro fertilization and preeclampsiaIVFIVF pregnancy riskslong-term maternal cardiovascular risksmaternal and fetal health risksMaternal healthoocyte donationplacental dysfunction in ART pregnanciesprediction modelspreeclampsiapreeclampsia prediction modelspregnancy complications in IVFPROBASTreproductive medicinesystematic reviewsystematic review of preeclampsia risk factorsTRIPOD
