The retrospective cohort study, led by Reweiguli Aihaiti and colleagues at Ruijin Hospital, affiliated with the Shanghai Jiao Tong University School of Medicine, drew on 3,285 patients who underwent frozen embryo transfer at the hospital’s Reproductive Medical Center between January 2015 and December 2022. After applying strict exclusion criteria, the team analyzed 2,543 women who delivered singleton live births and had complete pre-pregnancy menstrual cycle data. Participants were divided into four groups according to cycle length: 27 days or fewer, 28 to 31 days, 32 to 35 days, and 36 days or more. The reference category, encompassing roughly 71 percent of the cohort, was the conventional 28-to-31-day cycle, long considered the physiological gold standard.

The statistical architecture of the study was deliberately conservative. The investigators used multivariable logistic regression to estimate adjusted odds ratios for gestational diabetes and gestational hypertension, controlling for an unusually broad set of potential confounders: maternal age, body mass index, parity, causes and duration of infertility, fertilization method, ovarian stimulation protocol, number of transferable embryos, endometrial preparation method, embryo stage, and the number of embryos transferred. Patients with comorbidities known to disrupt both menstruation and pregnancy outcomes were excluded outright, and none of the participants had used oral contraceptives in the three months preceding their transfer, removing another potential source of distortion.

The results were striking in their consistency. Women with prolonged cycles of 36 days or longer had a 54 percent higher adjusted odds of developing gestational diabetes compared with women in the reference group, with an adjusted odds ratio of 1.54 and a 95 percent confidence interval of 1.14 to 2.09. Their adjusted odds of gestational hypertension were 60 percent higher, at 1.60. Perhaps more unexpectedly, cycles of 32 to 35 days, only modestly longer than normal, were also associated with a 59 percent increase in the odds of gestational hypertension. The raw incidence rates told the same story: gestational diabetes affected 25.6 percent of women with prolonged cycles, and gestational hypertension reached 12.2 percent in that group, both the highest figures across the four cycle-length categories.

Shorter cycles told the opposite story. Women whose cycles ran 27 days or fewer had roughly half the adjusted odds of developing gestational diabetes, with an adjusted odds ratio of 0.49, compared with the reference group. This protective association, the authors note, had been hinted at in earlier population-based research but had never been demonstrated in an IVF population free of polycystic ovary syndrome. The dose-response-like gradient, in which risk rises as cycle length lengthens and falls as it shortens, strengthens the biological plausibility of the association and argues against a statistical fluke.

What could a longer menstrual cycle possibly have to do with the way a placenta handles glucose or a maternal vasculature tolerates the hemodynamic load of pregnancy? The authors point to a chain of endocrine mechanisms documented in prior literature. Prolonged cycles are associated with hyperinsulinemia, and chronically elevated insulin suppresses hepatic production of sex hormone-binding globulin, which in turn raises levels of free circulating testosterone. Both insulin resistance and androgen excess are established risk factors for gestational diabetes. Longer cycles have also been linked to abnormalities in lipid metabolism and broader metabolic disturbance, conditions that independently predispose women to impaired glucose tolerance during pregnancy.

The connection to gestational hypertension may run through related but distinct physiology. Gestational glucose intolerance has previously been tied to hypertensive disorders of pregnancy, independent of obesity and blood glucose levels, in part because insulin resistance drives both inflammatory dysregulation and vascular dysfunction. The new study adds a novel piece of evidence by linking prolonged menstrual cycles, a marker of long-term endocrine milieu, to hypertension risk specifically in the absence of polycystic ovary syndrome. The finding dovetails with large epidemiological studies showing that women with long or irregular cycles face elevated lifetime risks of cardiovascular disease, ischemic heart disease, heart failure, hypertension, and type 2 diabetes. In a nationwide UK cohort of more than 700,000 women, cycle irregularity predicted a cluster of cardiometabolic outcomes years later.

The clinical implications are immediate for the fertility field. Frozen embryo transfer is performed under tightly controlled hormonal conditions, with endometrial preparation through natural cycles or hormone replacement protocols and progesterone support timed to precise endometrial thresholds. Yet even within this engineered environment, the underlying metabolic predisposition of the patient appears to assert itself. The authors argue that menstrual cycle length should be treated as a risk factor warranting screening before IVF treatment begins, and that combining cycle characteristics with body mass index in routine pre-treatment evaluations could identify women who would benefit from early glucose monitoring, blood pressure surveillance, and preventive intervention during pregnancy.

The study is not without limitations, and the authors are candid about them. The retrospective design precluded measurement of baseline insulin and lipid profiles, so the proposed mechanisms remain inferential rather than directly demonstrated. The cohort was restricted to frozen embryo transfer cycles, leaving open the question of whether the same associations hold for fresh transfers, where supraphysiological estradiol levels add their own metabolic noise. Supplementary analyses stratifying the population more finely showed that women with extraordinarily long cycles of 60 days or more had numerically elevated risks of both complications, with adjusted odds ratios of 2.06 for gestational diabetes and 1.88 for gestational hypertension, but the sample in that subgroup was too small for the results to reach statistical significance.

Even so, the study represents a first. No previous investigation had examined the relationship between menstrual cycle length and pregnancy complications in women without polycystic ovary syndrome undergoing IVF with frozen embryo transfer, a population that continues to grow as freeze-all strategies become standard practice in clinics worldwide. The message for patients is not alarm but attention: a menstrual cycle that reliably stretches beyond five weeks is not merely a fertility inconvenience or an aesthetic quirk of biology. It may be a visible readout of an invisible metabolic state, one that shapes pregnancy outcomes and, according to a growing body of evidence, long-term cardiovascular health. Larger prospective studies will be needed to confirm the findings and to test whether early intervention, from lifestyle modification to pharmacologic glucose management, can convert this new risk marker into a preventable outcome.

Subject of Research: The association between pre-pregnancy menstrual cycle length and the risk of gestational diabetes mellitus and gestational hypertension in women without PCOS undergoing frozen embryo transfer.

Article Title: Associations of menstrual cycle length with GDM and gestational hypertension in frozen embryo transfer

Article References: Aihaiti, R., Zhu, Z., Wu, X., Shen, Z., & Niu, Z. (2026). Associations of menstrual cycle length with GDM and gestational hypertension in frozen embryo transfer. Journal of Ovarian Research, 19(1), Article 277. https://doi.org/10.1186/s13048-026-02168-w

Image Credits: AI Generated

DOI: 10.1186/s13048-026-02168-w

Keywords: menstrual cycle length, gestational diabetes mellitus, gestational hypertension, frozen embryo transfer, in vitro fertilization, polycystic ovary syndrome, insulin resistance, pregnancy complications, reproductive medicine, cardiometabolic risk, IVF outcomes, retrospective cohort study

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