Infertility, Infertility Treatment and Cardiovascular Disease: An Overview

Association between polycyclic aromatic hydrocarbons and infertility in U.S. women: National Health and Nutrition Examination Survey 2013-2016

Although there is a body of research indicating the potential impact of polycyclic aromatic hydrocarbons (PAHs) exposure on male infertility, the understanding of how PAH might affect female infertility is still limited. This study aimed to evaluate associations of PAHs, both individually and as a mixture, with female infertility using multiple logistic regression, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC) models based on data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. The study included 729 female participants. Multiple logistic regression results indicated that there was a significant association between the third tertile of 2-hydroxy fluorene (2-OHFLU) and female infertility, and the OR was 2.84 (95% CI: 1.24-6.53, P value = 0.015) compared with the first tertile after adjusting for the potential covariates. The BKMR model revealed a positive overall trend between mixed PAH exposure and female infertility, particularly when the mixture was at or above the 55th percentile, where 2-hydroxynaphthalene (2-OHNAP) and 1-hydroxypyrene (1-OHPYR) were the primary influences of the mixture. The univariate exposure-response function indicated positive associations between individual PAH exposure, specifically 2-OHNAP, 2-OHFLU, and 1-OHPYR, and female infertility. The QGC model also indicated a positive trend between exposure to a mixture of PAHs and female infertility, although it did not reach statistical significance (OR = 1.33, 95%CI: 0.86-2.07), with 1-OHPYR having the greatest positive effect on the outcome. This study suggested that exposure to PAHs may be associated with female infertility and further research is needed to consolidate and confirm these findings.

The risk of perinatal and cardiometabolic complications in pregnancies conceived by medically assisted reproduction

PURPOSE

To examine the impact of medically assisted fertility treatments on the risk of developing perinatal and cardiometabolic complications during pregnancy and in-hospital deliveries.

METHODS

We conducted a retrospective cohort study using medical health records of deliveries occurring in 2016-2022 at a women's specialty hospital in a southern state of the Unites States (US). Pregnancies achieved using medically assisted reproductive (MAR) techniques were compared with unassisted pregnancies using propensity score matching (PSM), based on demographic, preexisting health, and reproductive factors. Study outcomes included cesarean delivery, gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), delivery complications, and postpartum readmission. We used Poisson regression with robust standard errors to generate risk ratios (RRs) and 95% confidence intervals (CIs) for all study outcomes.

RESULTS

Among 57,354 deliveries, 586 (1.02%) pregnancies were achieved using MAR and 56,768 (98.98%) were unassisted ("non-MAR"). Compared to the non-MAR group, MAR pregnancies had significantly higher prevalence of all study outcomes, including GDM (15.9% vs. 11.2%, p < 0.001), HDP (28.2% vs. 21.1%, p < 0.001), cesarean delivery (56.1% vs. 34.6%, p < 0.001), delivery complications (10.9% vs. 6.8%, p = 0.03), and postpartum readmission (4.3% vs. 2.7%, p = 0.02). In a PSM sample of 584 MAR and 1,727 unassisted pregnancies, MAR was associated with an increased risk of cesarean delivery (RR = 1.11, 95% CI = 1.01-1.22); whereas IVF was associated with an increased risk of cesarean delivery (RR = 1.15, 95% CI = 1.03-1.28) and delivery complications (RR = 1.44, 95% CI = 1.04-2.01).

CONCLUSIONS

Women who conceived with MAR were at increased risk of cesarean deliveries, and those who conceived with IVF were additionally at risk of delivery complications.

Change of HeART: Cardiovascular Implications of Assisted Reproductive Technology

Cardiovascular (CV) disease is the leading cause of death in women, and it may manifest differently than in men, in part related to sex-specific CV risk factors. In females, assisted reproductive technologies (ARTs) are commonly used to treat infertility, and they utilize controlled ovarian stimulation involving the administration of exogenous sex hormones. ARTs, and especially controlled ovarian stimulation, have been associated with an increased pregnancy and short-term CV risk, although the long-term CV implications of these treatments in individuals treated with ARTs and their offspring remain unclear. This review endeavors to provide a comprehensive examination of what is known about the relationship between ART and CV outcomes for females treated with ARTs, as well as their offspring, and recommendations for future research. Novel insights into female-specific CV risk factors are critical to reduce the disproportionate burden of CV disease in Canadian women. ART has revolutionized reproductive medicine, offering hope to millions of individuals with infertility worldwide, and a further understanding of the CV implications of this important sex-specific CV risk factor is warranted urgently.

History of Infertility and Midlife Cardiovascular Health in Female Individuals

Importance

Fertility status is a marker for future health, and infertility has been associated with risk for later cancer and diabetes, but associations with midlife cardiovascular health (CVH) in female individuals remain understudied.

Objective

To evaluate the association of infertility history with CVH at midlife (approximately age 50 years) among parous individuals.

Design, Setting, and Participants

Project Viva is a prospective cohort study of pregnant participants enrolled between 1999 and 2002 who delivered a singleton live birth in the greater Boston, Massachusetts, area. Infertility history was collected at a midlife visit between 2017 and 2021, approximately 18 years after enrollment. Data analysis was performed from January to June 2023.

Exposures

The primary exposure was any lifetime history of infertility identified by self-report, medical record, diagnosis, or claims for infertility treatment.

Main Outcomes and Measures

The American Heart Association's Life's Essential 8 (LE8) is a construct for ranking CVH that includes scores from 0 to 100 (higher scores denote better health status) in 4 behavioral (diet, physical activity, sleep, and smoking status) and 4 biomedical (body mass index, blood pressure, blood lipids, and glycemia) domains to form an overall assessment of CVH. Associations of a history of infertility (yes or no) with mean LE8 total, behavioral, biomedical, and blood biomarker (lipids and glycemia) scores were examined, adjusting for age at outcome (midlife visit), race and ethnicity, education, household income, age at menarche, and perceived body size at age 10 years.

Results

Of 468 included participants (mean [SD] age at the midlife visit, 50.6 [5.3] years) with exposure and outcome data, 160 (34.2%) experienced any infertility. Mean (SD) LE8 scores were 76.3 (12.2) overall, 76.5 (13.4) for the behavioral domain, 76.0 (17.5) for the biomedical domain, and 78.9 (19.2) for the blood biomarkers subdomain. In adjusted models, the estimated overall LE8 score at midlife was 2.94 points lower (95% CI, -5.13 to -0.74 points), the biomedical score was 4.07 points lower (95% CI, -7.33 to -0.78 points), and the blood subdomain score was 5.98 points lower (95% CI, -9.71 to -2.26 points) among those with vs without history of infertility. The point estimate also was lower for the behavioral domain score (β = -1.81; 95% CI, -4.28 to 0.66), although the result was not statistically significant.

Conclusions and Relevance

This cohort study of parous individuals found evidence for an association between a history of infertility and lower overall and biomedical CVH scores. Future study of enhanced cardiovascular preventive strategies among those who experience infertility is warranted.

Pregnancy Considerations in Tetralogy of Fallot

The majority of women with repaired tetralogy of Fallot are able to tolerate pregnancy with a low risk of cardiovascular events. However, proactive contraceptive advice, prepregnancy counselling, and care by a pregnancy heart team with expertise in congenital heart disease are key to ensuring a good outcome for mother and baby. Maternal and fetal risks are increased in the presence of severe valvular stenosis, poorly tolerated arrhythmia, significant ventricular dysfunction, and cyanosis. It is unusual to see cyanotic adults with tetralogy of Fallot, whether unoperated or shunt palliated; pregnancy risks are greatly reduced by completing their repair before pregnancy is undertaken. The multidisciplinary pregnancy heart team should make a risk-stratified pregnancy care plan using a combination of published scoring systems and an individualized assessment of the patient's comorbidities. Low-risk patients may have the majority of their care and give birth in local units, whereas those at high risk should be managed and give birth in a tertiary centre with high-level expertise and intensive care facilities. Age-appropriate conversations about future childbearing and safe and reliable contraception should be part of routine follow-up from teenage years, so that women with tetralogy of Fallot can control their own fertility and make informed decisions about having children.

Assisted reproductive technology: what are the cardiovascular risks for women?

INTRODUCTION

Infertility affects 15% of women of reproductive age in the United States. The use of assisted reproductive technology (ART) has been rising globally, as well as a growing recognition of reproductive factors that increase risk for cardiovascular disease (CVD).

AREAS COVERED

Women with infertility who use ART are more likely to have established CVD risk factors, such as obesity, dyslipidemia, hypertension, and diabetes. They are also more likely to experience adverse pregnancy outcomes, which are associated with both peripartum and long-term cardiovascular complications. ART may lead to increased cardiometabolic demands due to ovarian stimulation, pregnancy itself, and higher rates of multifetal gestation. Preeclampsia risk appears greater with frozen rather than fresh embryo transfers.

EXPERT OPINION

The use of ART and its association with long term CVD has not been well-studied. Future prospective and mechanistic studies investigating the association of ART and CVD risk may help determine causality. Nevertheless, CVD risk screening is critical pre-pregnancy and during pregnancy to reduce pregnancy complications that elevate future CVD risk. This also offers a window of opportunity to connect patients to longitudinal care for early management of cardiometabolic risk profile and initiation of preventive lifestyle and pharmacotherapy interventions tailored toward patient-specific risk factors.

Associations of single and multiple organophosphate pesticide exposure with female infertility in the USA: data from the 2015-2018 National Health and Nutrition Examination Survey

Substantial evidence has shown that organophosphate pesticide (OPP) exposure altered the reproductive system functions, such as prolonged menstrual cycles, sexual hormone imbalance, and changes in ovarian weight. However, the association of OPP exposure with female infertility is unclear. We explored the relationships of four single OPP metabolites and their mixed exposure with self-reported infertility among women aged 20-50 in the USA using the data from two cycles (2015-2016 and 2017-2018) of the National Health and Nutrition Examination Survey (NHANES) by multiple logistic regression, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC). Eventually, 659 females were included in our study. Among these females, 77 participants were ever infertile. Multiple logistic regression showed that the odds ratios (ORs) in the second and third tertiles of dimethylphosphate (DMP) for female infertility were 2.53 (95% confidence interval (95%CI): 1.20-5.32, P value = 0.016) and 2.96 (95%CI: 1.18-7.47, P value = 0.023) compared to the lowest tertile after adjusting for all covariates (P for trend = 0.022). A significantly positive association between the mixed OPP metabolites and infertility was observed in the BKMR model, in which DMP had the highest posterior inclusion probability (PIP = 0.741). The QGC model showed similar results, in which OPP metabolite mixtures increased the risk of female infertility, with DMP as a significantly positive contributor to the outcome. This study revealed the potential harm of OPP mixtures for female infertility in the USA, and DMP played the most critical role in female infertility risk among all OPP metabolites.

Long-term cardiovascular mortality in women with twin pregnancies by lifetime reproductive history

BACKGROUND

Women with one lifetime singleton pregnancy have increased risk of cardiovascular disease (CVD) mortality compared with women who continue reproduction particularly if the pregnancy had complications. Women with twins have higher risk of pregnancy complications, but CVD mortality risk in women with twin pregnancies has not been fully described.

OBJECTIVES

We estimated risk of long-term CVD mortality in women with naturally conceived twins compared to women with singleton pregnancies, accounting for lifetime number of pregnancies and pregnancy complications.

METHODS

Using linked data from the Medical Birth Registry of Norway and the Norwegian Cause of Death Registry, we identified 974,892 women with first pregnancy registered between 1967 and 2013, followed to 2020. Adjusted hazard ratios (aHR) with 95% confidence intervals (CI) for maternal CVD mortality were estimated by Cox regression for various reproductive history (exposure categories): (1) Only one twin pregnancy, (2) Only one singleton pregnancy, (3) Only two singleton pregnancies, (4) A first twin pregnancy and continued reproduction, (5) A first singleton pregnancy and twins in later reproduction and (6) Three singleton pregnancies (the referent group). Exposure categories were also stratified by pregnancy complications (pre-eclampsia, preterm delivery or perinatal loss).

RESULTS

Women with one lifetime pregnancy, twin or singleton, had increased risk of CVD mortality (adjusted hazard [HR] 1.72, 95% confidence interval [CI] 1.21, 2.43 and aHR 1.92, 95% CI 1.78, 2.07, respectively), compared with the referent of three singleton pregnancies. The hazard ratios for CVD mortality among women with one lifetime pregnancy with any complication were 2.36 (95% CI 1.49, 3.71) and 3.56 (95% CI 3.12, 4.06) for twins and singletons, respectively.

CONCLUSIONS

Women with only one pregnancy, twin or singleton, had increased long-term CVD mortality, however highest in women with singletons. In addition, twin mothers who continued reproduction had similar CVD mortality compared to women with three singleton pregnancies.

Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization

Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. In vitro fertilization (IVF) is one of those assisted reproduction methods in which the sperm and eggs are combined outside the human body in a specialized environment and kept for growth. Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. The morphology of the embryological components is highly related to the success of the assisted reproduction procedure. In approximately 3-5 days, the embryo transforms into the blastocyst. To prevent the multiple-birth risk and to increase the chance of pregnancy the embryologist manually analyzes the blastocyst components and selects valuable embryos to transfer to the women's uterus. The manual microscopic analysis of blastocyst components, such as trophectoderm, zona pellucida, blastocoel, and inner cell mass, is time-consuming and requires keen expertise to select a viable embryo. Artificial intelligence is easing medical procedures by the successful implementation of deep learning algorithms that mimic the medical doctor's knowledge to provide a better diagnostic procedure that helps in reducing the diagnostic burden. The deep learning-based automatic detection of these blastocyst components can help to analyze the morphological properties to select viable embryos. This research presents a deep learning-based embryo component segmentation network (ECS-Net) that accurately detects trophectoderm, zona pellucida, blastocoel, and inner cell mass for embryological analysis. The proposed method (ECS-Net) is based on a shallow deep segmentation network that uses two separate streams produced by a base convolutional block and a depth-wise separable convolutional block. Both streams are densely concatenated in combination with two dense skip paths to produce powerful features before and after upsampling. The proposed ECS-Net is evaluated on a publicly available microscopic blastocyst image dataset, the experimental segmentation results confirm the efficacy of the proposed method. The proposed ECS-Net is providing a mean Jaccard Index (Mean JI) of 85.93% for embryological analysis.

Machine Learning Methods in Predicting Patients with Suspected Myocardial Infarction Based on Short-Time HRV Data

Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world's population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and introduction of personalized medicine in healthcare institutions, including at the individual level when designing smart houses. Therefore, this study aims to analyze short 10-s electrocardiogram measurements taken from 12 leads. In addition, the task is to classify patients with suspected myocardial infarction using machine learning methods. We have developed four models based on the k-nearest neighbor classifier, radial basis function, decision tree, and random forest to do this. An analysis of time parameters showed that the most significant parameters for diagnosing myocardial infraction are SDNN, BPM, and IBI. An experimental investigation was conducted on the data of the open PTB-XL dataset for patients with suspected myocardial infarction. The results showed that, according to the parameters of the short ECG, it is possible to classify patients with a suspected myocardial infraction as sick and healthy with high accuracy. The optimized Random Forest model showed the best performance with an accuracy of 99.63%, and a root mean absolute error is less than 0.004. The proposed novel approach can be used for patients who do not have other indicators of heart attacks.