No abstract available.
Embolism, Air ; Magnetic Resonance Imaging

A 48-year-old woman presented with a 1-day history of aggressive behavior. Hashimoto encephalopathy was first suspected based on elevated levels of serum anti-thyroid peroxidase antibody. Her clinical symptoms did not improve despite treatment with intravenous corticosteroid. Abdominal computed tomography revealed liver cirrhosis, and brain T2-weighted magnetic resonance imaging revealed midbrain hyperintensity, and she was finally diagnosed with Wilson’s disease. The Wilson’s disease should be considered in the differential diagnosis in adults presenting with unexplained hepatic, neurological, or psychiatric abnormalities.

Obstructive sleep apnea (OSA), characterized by nocturnal airway obstruction, hypoxia, and arousal, is a significant risk factor for cardiovascular diseases, including arrhythmia. This case report describes the association between OSA and nocturnal sinus tachycardia in a 58-year-old woman who presented with sleep maintenance difficulties and recurrent nocturnal tachycardia. Polysomnography confirmed a direct correlation among the apnea/hypopnea episodes, tachycardia, and sleep maintenance difficulties. Continuous positive airway pressure therapy effectively resolved tachycardia and sleep maintenance difficulties, reducing the number of medications required to alleviate the symptoms. This report highlights the importance of considering OSA as a possible cause of unexplained nocturnal tachycardia.

Obstructive sleep apnea (OSA), characterized by nocturnal airway obstruction, hypoxia, and arousal, is a significant risk factor for cardiovascular diseases, including arrhythmia. This case report describes the association between OSA and nocturnal sinus tachycardia in a 58-year-old woman who presented with sleep maintenance difficulties and recurrent nocturnal tachycardia. Polysomnography confirmed a direct correlation among the apnea/hypopnea episodes, tachycardia, and sleep maintenance difficulties. Continuous positive airway pressure therapy effectively resolved tachycardia and sleep maintenance difficulties, reducing the number of medications required to alleviate the symptoms. This report highlights the importance of considering OSA as a possible cause of unexplained nocturnal tachycardia.

Obstructive sleep apnea (OSA), characterized by nocturnal airway obstruction, hypoxia, and arousal, is a significant risk factor for cardiovascular diseases, including arrhythmia. This case report describes the association between OSA and nocturnal sinus tachycardia in a 58-year-old woman who presented with sleep maintenance difficulties and recurrent nocturnal tachycardia. Polysomnography confirmed a direct correlation among the apnea/hypopnea episodes, tachycardia, and sleep maintenance difficulties. Continuous positive airway pressure therapy effectively resolved tachycardia and sleep maintenance difficulties, reducing the number of medications required to alleviate the symptoms. This report highlights the importance of considering OSA as a possible cause of unexplained nocturnal tachycardia.

No abstract available.
Astrocytoma* ; Encephalitis, Herpes Simplex* ; Herpes Simplex*

Objectives: The objective of this study was to develop models for predicting obstructive sleep apnea (OSA) based on easily obtainable clinical information of patients using various machine learning techniques. Methods: We used a data set that included the records of 1,368 patients, in which 1,074 patients were male (78.5 %), and 294 patients were female (21.5 %). We randomly divided the data into a training set (1,000) and test set (368). Five machine learning methods, i.e., support vector machine model, lasso logit model, naïve bayes, discriminant analysis, and K-nearest neighbor (KNN), with a 10-cross fold technique were used with the proposed model to predict OSA. We evaluated the accuracy, sensitivity, specificity, and precision of each model for three thresholds [Apnea-Hypopnea Index (AHI)≥5, AHI≥15, and AHI≥30]. Results: Among the machine learning techniques, KNN showed the best results compared to the other techniques. The accuracy, sensitivity, specificity, and precision of OSA prediction were 87.0%, 91.0%, 74.4%, and 91.9%, respectively, based on AHI≥5. When the threshold of OSA was AHI≥15 or AHI≥30, KNN provided lower accuracy (79.6% each) and precision (79.0% and 68.7%), which were still higher than those of the other techniques. Conclusions The model derived from the KNN technique exhibited the best performance based on its highest level of accuracy. We demonstrate that this model is a useful tool for predicting OSA.