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Cardiovascular and Metabolic Health of 74 Children From Women Previously Diagnosed With Polycystic Ovary Syndrome in Comparison With a Population-Based Reference Cohort. | LitMetric

AI Article Synopsis

Article Abstract

Women with polycystic ovary syndrome (PCOS) have compromised cardiovascular health profiles and an increased risk of pregnancy complications. In order to evaluate potential consequences, we aim to compare the cardiovascular and metabolic health of the children from women with PCOS with a population-based reference cohort. We included children from women with PCOS between the age of 2.5 to 4 years (n = 42) and 6 to 8 years (n = 32). The reference groups consisted of 168 (3-4 years old) and 130 children (7-8 years old). In an extensive cardiovascular screening program, we measured anthropometrics and blood pressure (all children), heart function and vascular rigidity (young children), metabolic laboratory assessment and carotid intima thickness (old age-group). Results showed that young PCOS offspring have a significantly lower diastolic blood pressure (β = 2.3 [95% confidence interval, CI: 0.5-4.0]) and higher aortic pulse pressure (β = -1.4 [95% CI: -2.5 to -0.2]), compared to the reference population. Furthermore, a higher left ventricle internal diameter but a lower tissue Doppler imaging of the right wall in systole compared to the reference group was found. Older offspring of women with PCOS presented with a significantly lower breast and abdominal circumference, but higher triglycerides (β = -0.1 [95% CI: -0.2 to -0.1]), LDL-cholesterol (β = -0.4 [95% CI: -0.6 to -0.1]), and higher carotid intima-media thickness (β = -31.7 [95% CI: -46.6 to -16.9]) compared to the reference group. In conclusion, we observe subtle but distinct cardiovascular and metabolic abnormalities already at an early age in PCOS offspring compared to a population-based reference group, despite a lower diastolic blood pressure, breast, and abdominal circumference. These preliminary findings require confirmation in independent data sets.

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http://dx.doi.org/10.1177/1933719117749761DOI Listing

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