Objective: NT-proBNP, a marker of ventricular dysfunction, varies by BMI outside of pregnancy. This study aimed to determine whether obesity affects NT-proBNP levels in pregnancy.
Study design: This was a prospective observational study of healthy pregnant people in the 3rd trimester and postpartum (PP). Subjects were excluded if they had significant medical comorbidities or if their fetuses had anomalies, growth restriction or aneuploidy. NT-proBNP was measured at 28 weeks (3TM), prior to delivery (PD), 1-2 days PP (IPP), and 4-6 weeks PP (DPP). LogNT-proBNP levels were analyzed using linear mixed effects models, including BMI < or ≥30, time, and time-by-BMI interactions.
Results: Fifty-five people (28 [51%] with BMI ≥ 30 and 27 [49%] with BMI < 30) were enrolled. A greater proportion of obese than non-obese subjects developed hypertensive disorders of pregnancy (50% vs 15%, p=0.010) and obese subjects had higher systolic blood pressures at all time points (p<0.05). NT-proBNP levels (median [IQR] in pg/mL) were 18 (6-28) vs 26 (17-48) at 3TM, 16 (3-38) vs 43 (21-60) at PD, 58 (20-102) vs 63 (38-155) at IPP, and 33 (27-56) vs 23 (8-42) at DPP for obese compared to non-obese subjects. In linear mixed effects models, logNT-proBNP was lower in obese subjects at 3TM (β=-0.89 [95% confidence interval -1.51, -0.26]) and PD (β=-1.05 [95% CI -1.72, -0.38]). The logNT-proBNP trends over time differed by BMI category, with higher values in obese subjects at both postpartum time points compared to the 3TM (IPP β=1.24 [95% CI 0.75, 1.73]); DPP β=1.08 [95% CI 0.52, 1.63]), but only IPP for non-obese subjects (β=0.87 [95% CI 0.36, 1.38]).
Conclusions: Obese subjects had lower NT-proBNP levels than non-obese subjects during pregnancy, but not postpartum. The prolonged postpartum elevation in NT-proBNP in obese subjects suggests that their postpartum cardiac recovery may be more prolonged.
mutation. After blinded data analysis, a PV was detected in 35 cases (BRCA1/2, BRIP1, RAD51C) and a variant of unknown significance in 6 cases (BRCA1/2, BRIP1, RAD51D). Exon deletions in BRCA1 were detected in 5 cases. The known molecular defect was identified in 46/48 (96%). Two CNVs (4%) were missed, a tandem duplication inclusing CHEK2 and loss of RAD51D. Conclusions TSO500 mutation analysis can be reliably used to detect PVs in OC predisposition genes, however, CNV analysis remains challenging. Therefore, the tumor first workflow where the tumor test is performed first to guide treatment might not identify all carriers of a germline PV. However, with Dutch nationwide implementation, this universal workflow leads to genetic testing of a higher proportion of OC patients.
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