Journal of Korean medical science
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J. Korean Med. Sci. · Feb 2024
The Risk of Hypertension and Diabetes Mellitus According to Offspring's Birthweight in Women With Normal Body Mass Index: A Nationwide Population-Based Study.
Maladaptation to vascular, metabolic, and physiological changes during pregnancy can lead to fetal growth disorders. Moreover, adverse outcomes during pregnancy can further increase the risk of cardiovascular and metabolic diseases in mothers. Delivering a large-for-gestational-age (LGA) baby may indicate a pre-existing metabolic dysfunction, whereas delivering a small-for-gestational-age (SGA) baby may indicate a pre-existing vascular dysfunction. This study aims to assess the risk of hypertension (HTN) and diabetes mellitus (DM) in women with normal body mass index (BMI) scores who did not experience gestational DM or hypertensive disorders during pregnancy based on the offspring's birthweight. ⋯ These findings provide a novel support for the use of the offspring's birthweight as a predictor of future maternal diseases such as HTN and DM.
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J. Korean Med. Sci. · Feb 2024
Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.
The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more practical approach to arrhythmia detection. Using artificial intelligence for atrial fibrillation (AF) identification enhances screening efficiency. However, the potential of single-lead ECG for AF identification during normal sinus rhythm (NSR) remains under-explored. This study introduces a method to identify AF using single-lead mobile ECG during NSR. ⋯ The deep learning model using single-lead mobile ECG during NSR effectively identified AF at risk in future. However, further research is needed to enhance the performance of deep learning models for clinical application.