Preeclampsia and Blood Pressure Trajectory during Pregnancy in Relation to Vitamin D Status

Every tenth pregnancy is affected by hypertension, one of the most common complications and leading causes of maternal death worldwide. Hypertensive disorders in pregnancy include pregnancy-induced hypertension and preeclampsia. The pathophysiology of the development of hypertension in pregnancy is unknown, but studies suggest an association with vitamin D status, measured as 25-hydroxyvitamin D (25(OH)D). The aim of this study was to investigate the association between gestational 25(OH)D concentration and preeclampsia, pregnancy-induced hypertension and blood pressure trajectory. This cohort study included 2000 women. Blood was collected at the first (T1) and third (T3) trimester (mean gestational weeks 10.8 and 33.4). Blood pressure at gestational weeks 10, 25, 32 and 37 as well as symptoms of preeclampsia and pregnancy-induced hypertension were retrieved from medical records. Serum 25(OH)D concentrations (LC-MS/MS) in T1 was not significantly associated with preeclampsia. However, both 25(OH)D in T3 and change in 25(OH)D from T1 to T3 were significantly and negatively associated with preeclampsia. Women with a change in 25(OH)D concentration of ≥30 nmol/L had an odds ratio of 0.22 (p = 0.002) for preeclampsia. T1 25(OH)D was positively related to T1 systolic (β = 0.03, p = 0.022) and T1 diastolic blood pressure (β = 0.02, p = 0.016), and to systolic (β = 0.02, p = 0.02) blood pressure trajectory during pregnancy, in adjusted analyses. There was no association between 25(OH)D and pregnancy-induced hypertension in adjusted analysis. In conclusion, an increase in 25(OH)D concentration during pregnancy of at least 30 nmol/L, regardless of vitamin D status in T1, was associated with a lower odds ratio for preeclampsia. Vitamin D status was significantly and positively associated with T1 blood pressure and gestational systolic blood pressure trajectory but not with pregnancy-induced hypertension

Disease activity trajectories in rheumatoid arthritis : a tool for prediction of outcome

Objective: Predicting treatment response and disease progression in rheumatoid arthritis (RA) remains an elusive endeavour. Identifying subgroups of patients with similar progression is essential for understanding what hinders improvement. However, this cannot be achieved with response criteria based on current versus previous Disease Activity Scores, as they lack the time component. We propose a longitudinal approach that identifies subgroups of patients while capturing their evolution across several clinical outcomes simultaneously (multi-trajectories). Method: For exploration, the RA cohort BARFOT (n = 2829) was used to identify 24 month post-diagnosis simultaneous trajectories of 28-joint Disease Activity Score and its components. Measurements were available at inclusion (0), 3, 6, 12, 24, and 60 months. Multi-trajectories were found with latent class growth modelling. For validation, the TIRA-2 cohort (n = 504) was used. Radiographic changes, assessed by the modified Sharp van der Heijde score, were correlated with trajectory membership. Results: Three multi-trajectories were identified, with 39.6% of the patients in the lowest and 18.9% in the highest (worst) trajectory. Patients in the worst trajectory had on average eight tender and six swollen joints after 24 months. Radiographic changes at 24 and 60 months were significantly increased from the lowest to the highest trajectory. Conclusion: Multi-trajectories constitute a powerful tool for identifying subgroups of RA patients and could be used in future studies searching for predictive biomarkers for disease progression. The evolution and shape of the trajectories in TIRA-2 were very similar to those in BARFOT, even though TIRA-2 is a newer cohort