The association between hypertensive disorders during pregnancy and maternal and neonatal outcomes: a retrospective claims analysis.

BACKGROUND: Hypertensive disorders during pregnancy continue to increase in prevalence and are associated with several adverse outcomes and future cardiovascular risk for mothers. This study evaluated the association of hypertensive disorders compared to no hypertension during pregnancy with neonatal and maternal outcomes. We then evaluated risk factors associated with progression from a less to more severe hypertensive disorder during pregnancy. METHODS: We conducted a propensity-matched retrospective cohort study utilizing Medicaid claims data from a national insurer. The study population consisted of mothers with and without hypertensive disorders who delivered between 7/1/2016-12/31/2018 and their infants. Hypertensive disorders included gestational hypertension, chronic hypertension, preeclampsia, and superimposed preeclampsia. Propensity score matching was used to match mothers without to those with hypertensive disorders. Regression models were used to compare maternal and neonatal outcomes. Stepwise logistic regression was used to determine characteristics associated with the progression of gestational hypertension to preeclampsia or chronic hypertension to superimposed preeclampsia. RESULTS: We observed the highest risk of cesarean delivery (odds ratio [OR]:1.61 and 1.99) in mothers and preterm delivery (OR:2.22 and 5.37), respiratory distress syndrome (OR:2.39 and 4.19), and low birthweight (OR:3.64 and 9.61) in babies born to mothers with preeclampsia or superimposed preeclampsia compared to no hypertension, respectively (p < 0.05 for all outcomes). These outcomes were slightly higher among chronic or gestational hypertension compared to no hypertension, however, most were not statistically significant. Risk of neonatal intensive care unit utilization was higher among more severe hypertensive disorders (OR:2.41 for preeclampsia, OR:4.87 for superimposed preeclampsia). Obesity/overweight and having a history of preeclampsia during a prior pregnancy were most likely to predict progression from gestational/chronic hypertension to preeclampsia/superimposed preeclampsia. CONCLUSION: Mothers and neonates born to mothers with preeclampsia or superimposed preeclampsia experienced more adverse outcomes compared to those without hypertension. Mothers and neonates born to mothers with gestational hypertension had outcomes similar to those without hypertension. Outcomes for those with chronic hypertension fell in between gestational hypertension and preeclampsia. Obesity/overweight and having a history of preeclampsia during a prior pregnancy were strong risk factors for hypertension progression.

Multilevel space-time aggregation for bright field cell microscopy segmentation and tracking.

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called "Segmentation by Weighted Aggregation" technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant "saliency measure" is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments ("object tunnels") that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.