Medicine
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Machine learning (ML) models for predicting 72-hour unscheduled return visits (URVs) for patients with abdominal pain in the emergency department (ED) were developed in a previous study. This study refined the data to adjust previous prediction models and evaluated the model performance in future data validation during the COVID-19 era. We aimed to evaluate the practicality of the ML models and compare the URVs before and during the COVID-19 pandemic. ⋯ Among these models, the VC model showed the most favorable, balanced, and comprehensive performance. Despite the promising results, the study illuminated challenges in predictive modeling, such as the unforeseen influences of global events, such as the COVID-19 pandemic. These findings not only highlight the significant potential of machine learning in augmenting emergency care but also underline the importance of iterative refinement in response to changing real-world conditions.
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Pulmonary artery sarcoma (PAS) is a rare malignant tumor primarily originating from the pulmonary artery's intima or subintima. Approximately one-third of cases are classified as undifferentiated type. Its clinical manifestations lack specificity, dyspnea is the main symptom but can also present with chest pain, cough, hemoptysis, and other discomforts, making it prone to misdiagnosis as pulmonary embolism (PE). ⋯ PAS can be easily misdiagnosed as PE. If a diagnosis of PE is made, but anticoagulation or even thrombolytic therapy proves ineffective, and there is no presence of PE causative factors such as deep vein thrombosis in the lower extremities, or D-dimer levels are not high, one should be cautious and consider the possibility of PAS.
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This study uses machine learning and population data to analyze major determinants of blood transfusion among patients with hip arthroplasty. Retrospective cohort data came from Korea National Health Insurance Service claims data for 19,110 patients aged 65 years or more with hip arthroplasty in 2019. The dependent variable was blood transfusion (yes vs no) in 2019 and its 31 predictors were included. ⋯ For example, the inclusion of anemia, age, tranexamic acid or spinal anesthesia into the random forest will increase the probability of blood transfusion among patients with hip arthroplasty by 9%, 7%, 9% or 5%. Machine learning is an effective prediction model for blood transfusion among patients with hip arthroplasty. The high-risk group with anemia, age and comorbid conditions need to be treated with tranexamic acid, iron and/or other appropriate interventions.
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Main pancreatic duct (MPD) dilatation is reported to be a risk factor for pancreatic cancer (PC). Although magnetic resonance cholangiopancreatography (MRCP) and ultrasonographic modalities are valuable for monitoring the pancreas, there is limited information on the efficacy of different imaging modalities in measuring MPD diameter. To improve pancreatic imaging, we developed a specialized ultrasound approach focusing on the pancreas (special pancreatic US). ⋯ There were strong positive correlations between MPD diameter measured on special pancreatic US and that measured on MRCP (R = 0.925, P < .001). This study revealed strong positive correlations between the MPD diameter measurements using special pancreatic US and MRCP. MPD diameter measurements from each imaging method can be helpful during follow-up in individuals at a high risk of PC.
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Teres minor denervation (TMD) has gained increasing attention in recent years, particularly with the advent of magnetic resonance imaging (MRI). The potential association between TMD and shoulder instability or rotator cuff tear remains a subject of interest in the orthopedic community. In this retrospective and cross-sectional study, authors aim to investigate the potential association between TMD and shoulder instability or rotator cuff tears. ⋯ Our findings suggest that TMD is significantly associated with rotator cuff tears and shoulder instability. This study highlights the importance of identifying and treating PLCC tears in patients with TMD to address shoulder instability. Further research is needed to elucidate the role of TMD in the pathogenesis of shoulder instability and rotator cuff pathology.