Objective: Genetic and environmental factors may contribute to the etiology of the juvenile idiopathic inflammatory myopathies (IIMs), which are systemic autoimmune diseases that are characterized by muscle and skin inflammation. We undertook this study to investigate the association between ultraviolet radiation (UVR) exposure and the clinical and autoantibody expression of juvenile IIM.Methods: The relationship between UVR exposure in the month before symptom onset and the prevalence of juvenile dermatomyositis (DM), compared to juvenile polymyositis (PM), was assessed in 298 juvenile IIM patients. Among the patients with juvenile DM, the association between UVR exposure and presence of myositis autoantibodies was assessed. Regression models were stratified by sex and race. The association between the regional UV index in US geoclimatic zones and the clinical and autoantibody subgroups was examined by weighted least squares regression analysis.Results: Among girls in this population, the odds of having juvenile DM, compared to juvenile PM, increased per unit increase in the patients' highest UV index in the month before symptom onset (odds ratio [OR] 1.18, 95% confidence interval 1.00–1.40). Moreover, both the mean and highest UV indices were associated with increasing odds of having anti‐p155/140 autoantibodies, with the strongest odds in white males (ORs of 1.30 and 1.23, respectively). No association was observed between the UV index and presence of anti‐MJ autoantibodies or lack of any myositis autoantibodies. Across all 9 US geoclimatic regions, the mean UV index was associated with increasing odds of having juvenile DM and anti‐p155/140 autoantibodies, but decreasing odds of having anti‐MJ autoantibodies.Conclusion: Short‐term UVR exposure prior to illness onset may have a role in the clinical and serologic expression of juvenile myositis. Further research examining the mechanisms of action of UVR in the pathogenesis of juvenile IIM is suggested from these findings.

OBJECTIVE: To evaluate whether pregnancy-associated hypertension (gestational hypertension and preeclampsia) was associated with the cardiometabolic health of young offspring. METHODS: This was a prospective observational follow-up study from 2012 to 2013 of children born to women previously enrolled in a mild gestational diabetes mellitus treatment trial or nongestational diabetes mellitus observational study. At 5–10 years after birth, children were examined and fasting blood samples obtained to determine the following cardiometabolic risk factors: blood pressure (BP), high-density lipoprotein cholesterol, triglycerides, glucose, homeostatic model assessment of insulin resistance, waist circumference, and body mass index (BMI). RESULTS: This analysis included 979 children evaluated at a median 7 years of age. Twenty-three (2%) were born preterm from a hypertensive pregnancy, 73 (7%) were born at term from a hypertensive pregnancy, 58 (6%) were born preterm from a normotensive pregnancy, and 825 (84%) were born at term from a normotensive pregnancy (reference group). After adjusting for confounding factors, mean adjusted systolic BP was significantly higher in the children who were born at term to mothers who experienced pregnancy-associated hypertension compared with those born at term to normotensive mothers (systolic BP of 104 mm Hg, 95% CI 101–106 vs systolic BP of 99 mm Hg, 95% CI 99–100, P=.001). No other significant differences were observed. CONCLUSION: Pregnancy-associated hypertension in women who deliver at term was associated with higher systolic BP in the offspring, but not with their measures of diastolic BP, BMI, waist circumference, homeostatic model assessment of insulin resistance, glucose, or lipids. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT00069576.

Background: Current postpartum hemorrhage (PPH) risk stratification is based on traditional statistical models or expert opinion. Machine learning could optimize PPH prediction by allowing for more complex modeling. Objective: We sought to improve PPH prediction and compare machine learning and traditional statistical methods. Methods: We developed models using the Consortium for Safe Labor data set (2002-2008) from 12 US hospitals. The primary outcome was a transfusion of blood products or PPH (estimated blood loss of ≥1000 mL). The secondary outcome was a transfusion of any blood product. Fifty antepartum and intrapartum characteristics and hospital characteristics were included. Logistic regression, support vector machines, multilayer perceptron, random forest, and gradient boosting (GB) were used to generate prediction models. The area under the receiver operating characteristic curve (ROC-AUC) and area under the precision/recall curve (PR-AUC) were used to compare performance. Results: Among 228,438 births, 5760 (3.1%) women had a postpartum hemorrhage, 5170 (2.8%) had a transfusion, and 10,344 (5.6%) met the criteria for the transfusion-PPH composite. Models predicting the transfusion-PPH composite using antepartum and intrapartum features had the best positive predictive values, with the GB machine learning model performing best overall (ROC-AUC=0.833, 95% CI 0.828-0.838; PR-AUC=0.210, 95% CI 0.201-0.220). The most predictive features in the GB model predicting the transfusion-PPH composite were the mode of delivery, oxytocin incremental dose for labor (mU/minute), intrapartum tocolytic use, presence of anesthesia nurse, and hospital type. Conclusions: Machine learning offers higher discriminability than logistic regression in predicting PPH. The Consortium for Safe Labor data set may not be optimal for analyzing risk due to strong subgroup effects, which decreases accuracy and limits generalizability.

OBJECTIVE: To evaluate whether pregnancy-associated hypertension (preeclampsia or gestational hypertension) among women with varying degrees of glucose intolerance during pregnancy is associated with maternal metabolic syndrome 5–10 years later. METHODS: This was an observational cohort study of women previously enrolled in a treatment trial of mild gestational diabetes mellitus or an observational study of lesser degrees of glucose intolerance evaluated 5–10 years after their index pregnancy. At follow-up, women underwent anthropometric and blood pressure measurements and analysis of fasting glucose and serum lipids. RESULTS: A total of 825 women (47% of eligible women from the original study) were included in this analysis and evaluated at a median 7 years after their index pregnancy at a median age of 35 years. Overall, 239 (29%) had subsequent metabolic syndrome. The frequency of metabolic syndrome and its components was highest in the women who had pregnancy-associated hypertension and delivered preterm. After adjusting for confounding factors, pregnancy-associated hypertension in women who delivered preterm was associated with subsequent hypertension (130/85 mm Hg or greater; relative risk 3.06, 95% confidence interval [CI] 1.95–4.80, P<.001), high triglycerides (150 mg/dL or greater; relative risk 1.82, 95% CI 1.06–3.14, P=.03), and metabolic syndrome (per the American Heart Association and National Heart Lung and Blood Institute Scientific Statement; relative risk 1.78, 95% CI 1.14–2.78, P=.01) compared with women who remained normotensive throughout their index pregnancy and were delivered at term. CONCLUSION: Women with varying degrees of glucose intolerance who experienced pregnancy-associated hypertension and then delivered preterm had a higher frequency of subsequent hypertension, high triglycerides, and metabolic syndrome 5–10 years later.

Myotonic dystrophy type 1 and type 2 (DM1/DM2) are multisystemic disorders that may affect heart function in addition to the progressive skeletal muscle weakness and myotonia that occur. There are limited population-based studies on the prevalence and risks associated with cardiac symptoms in DM1 and DM2. Cardiac data were abstracted from the medical records of 429 individuals with DM1 and DM2 with a health care encounter between 2008 and 2019. The frequencies of cardiac arrhythmias and of cardiomyopathy were assessed along with relationships to demographic data and age at onset. A total of 429 individuals from MD STARnet were included in the analyses, with 82.3% having DM1. Overall, cardiac arrhythmias were observed in 44.5% and cardiomyopathy in 9.1%. The risk of developing a cardiac arrhythmia was much higher in DM1 than in DM2. Repeat length was not a risk factor for the development of a cardiac arrhythmia. Developing DM1 in childhood or adulthood as opposed to congenital onset was a risk factor of both cardiac arrhythmia and cardiomyopathy in multivariable analysis. This study confirms the increased risk of cardiac arrhythmias in individuals with DM and DM2 and identifies the development of cardiomyopathy as a low-frequency event. Notably, the risk of cardiac arrhythmias is particularly elevated in DM1. The study reaffirms the need for serial cardiac monitoring in individuals with DM1/DM2.