Reproductive risk factors for angiographic obstructive coronary artery disease among postmenopausal women

Gestational diabetes mellitus and development of intergenerational overall and subtypes of cardiovascular diseases: a systematic review and meta-analysis

OBJECTIVE

We aimed to summarize the association between gestational diabetes mellitus (GDM) and its intergenerational cardiovascular diseases (CVDs) impacts in both mothers and offspring post-delivery in existing literature.

METHODS

PubMed, Embase, Web of Science, and Scopus were utilized for searching publications between January 1980 and June 2024, with data extraction and meta-analysis continuing until 31 July 2024. Based on a predefined PROSPERO protocol, studies published as full-length, English-language journal articles that reported the presence of GDM during pregnancy and its association with any CVD development post-delivery were selected. All studies were evaluated using the Newcastle-Ottawa Scale. Maximally adjusted risk estimates were pooled using random-effects meta-analysis to assess the risk ratio (RR) of GDM, and overall and subtypes of CVDs in both mothers and offspring post-delivery.

RESULTS

The meta-analysis was based on 38 studies with a total of 77,678,684 participants. The results showed a 46% increased risk (RR 1.46, 95% CI 1.34-1.59) for mothers and a 23% increased risk (1.23, 1.05-1.45) for offspring of developing overall CVDs after delivery, following a GDM-complicated pregnancy. Our subgroup analysis revealed that mothers with a history of GDM faced various risks (20% to 2-fold) of developing different subtypes of CVDs, including cerebrovascular disease, coronary artery disease, heart failure, and venous thromboembolism.

CONCLUSIONS

These findings underscore the heightened risk of developing various CVDs for mothers and offspring affected by GDM, emphasizing the importance of preventive measures even right after birth to mitigate the burden of CVDs in these populations.

Differences in coronary angiographic findings and outcomes between men and postmenopausal women with stable chest pain

BACKGROUND

Despite the significant increase in cardiovascular events in women after menopause, studies comparing postmenopausal women and men are scarce.

METHODS

We analyzed data from a nationwide, multicenter, prospective registry and enrolled 2412 patients with stable chest pain who underwent elective coronary angiography. Binary coronary artery disease (b-CAD) was defined as the ≥50% stenosis of epicardial coronary arteries, including the left main coronary artery.

RESULTS

Compared with the men, postmenopausal women were older (66.6 ± 8.5 vs. 59.5 ± 11.4 years) and had higher high-density lipoprotein cholesterol levels (49.0 ± 12.8 vs. 43.6 ± 11.6 mg/dl, P  < 0.01). The prevalence of diabetes did not differ significantly ( P  = 0.40), and smoking was more common in men than in postmenopausal women ( P  ≤ 0.01). At enrollment, b-CAD and revascularization were more common in men than in postmenopausal women (50.3% vs. 41.0% and 14.4% vs. 9.7%, respectively; both P  < 0.01). However, multivariate analyses revealed that revascularization [odds ratio (OR): 0.72; 95% confidence interval (CI): 0.49-1.08] was not significantly related to sex and a similar result was found in age propensity-matched population (OR: 0.80; 95% CI: 0.52-1.24). During the follow-up period, the secondary composite cardiovascular outcomes were lower in postmenopausal women than in men (OR: 0.55; 95% CI: 0.31-0.98), also consistent with the result using the age propensity-mated population (OR: 0.33; 95% CI: 0.13-0.85).

CONCLUSION

Postmenopausal women experienced coronary revascularization comparable to those in men at enrollment, despite the average age of postmenopausal women was 7 years older than that of men.Postmenopausal women exhibit better clinical outcomes than those of men if optimal treatment is provided.

Use of Race, Ethnicity, and National Origin in Studies Assessing Cardiovascular Risk in Women With a History of Hypertensive Disorders of Pregnancy

Women with a history of hyperBtensive disorders of pregnancy (HDP) are at particularly high risk for cardiovascular disease (CVD) and CVD-related death, and certain racial and ethnic subpopulations are disproportionately affected by these conditions. We examined the use of race, ethnicity, and national origin in observational studies assessing CVD morbidity and mortality in women with a history of HDP. A total of 124 studies, published between 1976 and 2021, were reviewed. We found that white women were heavily overrepresented, encompassing 53% of all participants with HDP. There was limited and heterogeneous reporting of race and ethnicity information across studies and only 27 studies reported including race and/or ethnicity variables in at least 1 statistical analysis. Only 2 studies mentioned the use of these variables as a strength; several others (k = 18) reported a lack of diversity among participants as a study limitation. Just over half of included articles (k = 68) reported at least 1 sociodemographic variable other than race and ethnicity (eg, marital status and income); however, none investigated how they might have worked synergistically or antagonistically with race and/or ethnicity to influence participants' risk of CVD. These findings highlight significant areas for improvement in cardiovascular obstetrics research, including the need for more robust and standardized methods for collecting, reporting, and using sociodemographic information. Future studies of CVD risk in women with a history of HDP should explicitly examine racial and ethnic differences and use an intersectional approach.

Segmentation and Classification of Heart Angiographic Images Using Machine Learning Techniques

Heart angiography is a test in which the concerned medical specialist identifies the abnormality in heart vessels. This type of diagnosis takes a lot of time by the concerned physician. In our proposed method, we segmented the interested regions of heart vessels and then classified. Segmentation and classification of heart angiography provides significant information for the physician as well as patient. Contradictorily, in the mention domain of heart angiography, the charge is prone to error, phase overwhelming, and thought-provoking task for the physician (heart specialist). An automatic segmentation and classification of heart blood vessels descriptions can improve the truthfulness and speed up the finding of heart illnesses. In this work, we recommend a computer-assisted conclusion arrangement for the localization of human heart blood vessels within heart angiographic imageries by using multiclass ensemble classification mechanism. In the proposed work, the heart blood vessels will be first segmented, and the various features according to accuracy have been extracted. Low-level features such as texture, statistical, and geometrical features were extracted in human heart blood vessels. At last, in the proposed framework, heart blood vessels have been categorized in their four respective classes including normal, block, narrow, and blood flow-reduced vessels. The proposed approach has achieved best result which provides very useful, easy, accurate, and time-saving environment to cardiologists for the diagnosis of heart-related diseases.