Background: Various disease prediction models have been developed, capitalizing on the wide use of electronic health records, but environmental factors that are important in the development of noncommunicable diseases are rarely included in the prediction models. Hypertensive disorders of pregnancy are leading causes of maternal morbidity and mortality and are known to cause several serious complications later in life.
Objective: This study aims to develop early hypertensive disorders of pregnancy prediction models using comprehensive environmental factors based on self-report questionnaires in early pregnancy.
Study Design: We developed machine learning and artificial intelligence models for the early prediction of hypertensive disorders of pregnancy using early pregnancy data from approximately 23,000 pregnancies in the Tohoku Medical Megabank Birth and Three Generation Cohort Study. We clarified the important features for prediction based on regression coefficients or Gini coefficients of the interpretable artificial intelligence models (i.e., logistic regression, random forest and XGBoost models) among our developed models.
Results: The performance of the early hypertensive disorders of pregnancy prediction models reached an area under the receiver operating characteristic curve of 0.93, demonstrating that the early hypertensive disorders of pregnancy prediction models developed in this study retain sufficient performance in hypertensive disorders of pregnancy prediction. Among the early prediction models, the best performing model was based on self-reported questionnaire data in early pregnancy (mean of 20.2 gestational weeks at filling) which consist of comprehensive lifestyles. The interpretation of the models reveals that both eating habits were dominantly important for prediction.
Conclusion: We have developed high-performance models for early hypertensive disorders of pregnancy prediction using large-scale cohort data from the Tohoku Medical Megabank project. Our study clearly revealed that the use of comprehensive lifestyles from self-report questionnaires led us to predict hypertensive disorders of pregnancy risk at the early stages of pregnancy, which will aid early intervention to reduce the risk of hypertensive disorders of pregnancy.
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http://dx.doi.org/10.1016/j.xagr.2024.100383 | DOI Listing |
J Echocardiogr
December 2024
Division of Cardiology, Department of Internal Medicine, Tokai University School of Medicine, Shimokasuya 143, Isehara-shi, Kanagawa, 259-1193, Japan.
Purpose: Few investigational reports have evaluated the status of cardiovascular manifestations of coronavirus disease 2019 (COVID-19) during the Omicron dominance period. In this study, we aimed to investigate the cardiac function parameters and clinical outcomes of patients with COVID-19 before and after the Omicron variant (OV) propagation.
Methods: We retrospectively analyzed the data of 88 adult patients with COVID-19 who underwent clinically indicated standard transthoracic echocardiography (TTE) in intensive care wards.
Gut Microbes
December 2025
Hypertension Research Laboratory, School of Biological Sciences, Faculty of Science, Monash, Clayton, Australia.
The gut microbiota is a crucial link between diet and cardiovascular disease (CVD). Using fecal metaproteomics, a method that concurrently captures human gut and microbiome proteins, we determined the crosstalk between gut microbiome, diet, gut health, and CVD. Traditional CVD risk factors (age, BMI, sex, blood pressure) explained < 10% of the proteome variance.
View Article and Find Full Text PDFCardiovasc Diabetol
December 2024
INSERMU1138-Centre de Recherche Des Cordeliers, Paris Cite University, Sorbonne University, 75006, Paris, France.
Hypertension, cardiovascular disease and kidney failure are associated with persistent hyperglycaemia and the subsequent development of nephropathy in people with diabetes. Diabetic nephropathy is associated with widespread vascular disease affecting both the kidney and the heart from an early stage. However, the risk of diabetic nephropathy in people with type 1 diabetes is strongly genetically determined, as documented in familial transmission studies.
View Article and Find Full Text PDFBMC Cardiovasc Disord
December 2024
Heart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People's Republic of China.
Background: Familial hypercholesterolemia (FH) is a genetically inherited disorder caused by monogenic mutations or polygenic deleterious variants. Patients with FH innate with significantly elevated risks for coronary heart disease (CHD). FH prevalence based on genetic testing in Chinese CHD patients is missing.
View Article and Find Full Text PDFArthroscopy
December 2024
Department of Orthopedic Surgery, University of California San Francisco, San Francisco, CA. Electronic address:
Purpose: To determine if pre-operative infection with COVID-19 increased risk for post-operative venous thromboembolism (VTE) in patients undergoing arthroscopic knee surgery..
Methods: PearlDiver Mariner 165 database was queried for patients undergoing knee arthroscopy between 2010 through October, 2022.
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