Introduction: Kawasaki disease (KD) is a systemic vasculitis that occurs mostly in children under five years old. Kawasaki affects the middle-size arteries, especially the coronary arteries. Therefore, without adequate treatment, it may cause coronary artery aneurysm in 25% of patients. The purpose of this study was to investigate the relationship between Kobayashi, Sano, and Egami criterions with coronary artery aneurysm in KD patients during the last ten years and to identify risk factors in patients with intravenous immunoglobulin (IVIG)-resistant and coronary artery aneurysms.
Methodology: Medical records of 363 Kawasaki patients referred during 2008-2017 were reviewed. Patients' demographic data and Kobayashi, Sano, and Egami scores of each patient were calculated. Based on echocardiographic findings, cases of coronary artery aneurysm were determined. Sensitivity, specificity, positive and negative predictive value, and the accuracy of each criterion were determined to predicting IVIG resistance and detect coronary artery aneurysm.
Results: There was a slight relationship between IVIG-resistance in Kawasaki children and its prediction based on the Kobayashi risk score, but no relationship was found between the Egami and Sano criteria. Sixty-three patients (17.4%) had coronary artery lesions (CALs) on time of diagnosis. There were no statistically significant differences between gender and mean age of children with and without CALs. Also, there was no significant relationship between coronary artery aneurysm in Kawasaki children and its prediction based on the above three risk factors. The area under the ROC-curve of all three risk measures of Kobayashi, Egami, and Sano indicated that all three criteria were not useful in predicting CALs.
Conclusion: Despite the low accuracy of the three above criteria to predictive of patients with IVIG resistance, it seems that the variables of age, duration of fever, and C-reactive protein (CRP) are more useful than other variables and may be utilized to evaluate patients by establishing a more appropriate cut-off point.
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http://dx.doi.org/10.2147/OARRR.S255138 | DOI Listing |
Gen Thorac Cardiovasc Surg
January 2025
Department of Perfusion, Faculty of Health Sciences, Harran University, Sanliurfa, Türkiye.
JACC Cardiovasc Imaging
January 2025
Department of Medicine, Lundquist Institute at Harbor-UCLA, Torrance, California, USA.
JACC Cardiovasc Imaging
January 2025
Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address:
Background: Implementation of semaglutide weight loss therapy has been challenging due to drug supply and cost, underscoring a need to identify those who derive the greatest absolute benefit.
Objectives: Allocation of semaglutide was modeled according to coronary artery calcium (CAC) among individuals without diabetes or established atherosclerotic cardiovascular disease (CVD).
Methods: In this analysis, 3,129 participants in the MESA (Multi-Ethnic Study of Atherosclerosis) without diabetes or clinical CVD met body mass index criteria for semaglutide and underwent CAC scoring on noncontrast cardiac computed tomography.
JACC Cardiovasc Interv
December 2024
British Heart Foundation Centre of Research Excellence at the School of Cardiovascular Medicine and Sciences, King's College London, United Kingdom; Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom. Electronic address:
Turk Kardiyol Dern Ars
January 2025
Department of Cardiology, Dr Siyami Ersek Thoracic and Cardiovascular Surgery Training Hospital, İstanbul, Türkiye.
Objective: Coronary artery disease (CAD) is the leading cause of morbidity and mortality globally. The growing interest in natural language processing chatbots (NLPCs) has driven their inevitable widespread adoption in healthcare. The purpose of this study was to evaluate the accuracy and reproducibility of responses provided by NLPCs, such as ChatGPT, Gemini, and Bing, to frequently asked questions about CAD.
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