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Background Patients hospitalized in medical ICUs (MICUs) with acute noncardiac illnesses may have underlying cardiovascular abnormalities, especially in Egypt where rheumatic heart disease is still frequently encountered. This may affect the diagnosis and/or plan of management. Routine cardiac examination may not be informative because of the acuteness of the illness and the need for frequent concurrent mechanical ventilation. Purpose The purpose of this study was to utilize transthoracic echocardiography to define cardiac abnormalities, especially rheumatic valve disease that may be present in noncardiac patients. Materials and methods Over a 4-month period, 75 patients without primary cardiac diagnoses admitted to the MICU of Kasr El Ainy hospital underwent transthoracic echocardiography (TTE). The MICU mortality rates and length of stay were compared in patients with and without significant cardiac abnormalities. Results One or more cardiac abnormalities were observed in 61.3% patients of the studied group. Of these abnormalities, 15% were rheumatic in origin. Right atrial and right ventricular dilatation were the most encountered lesions, followed by left ventricular hypertrophy and pulmonary hypertension. Although there was no correlation between the presence of cardiac abnormalities and the length of ICU stay or mortality, the plan of management was affected in 14.67% of patients. Conclusion A significant proportion of patients admitted to the MICU with noncardiac illness had underlying cardiac abnormalities, and this affected the plan of management in a significant number of patients.

<abstract><p>The accurate visualization and assessment of the complex cardiac and pulmonary structures in 3D is critical for the diagnosis and treatment of cardiovascular and respiratory disorders. Conventional 3D cardiac magnetic resonance imaging (MRI) techniques suffer from long acquisition times, motion artifacts, and limited spatiotemporal resolution. This study proposes a novel time-resolved 3D cardiopulmonary MRI reconstruction method based on spatial transformer networks (STNs) to reconstruct the 3D cardiopulmonary MRI acquired using 3D center-out radial ultra-short echo time (UTE) sequences. The proposed reconstruction method employed an STN-based deep learning framework, which used a combination of data-processing, grid generator, and sampler. The reconstructed 3D images were compared against the start-of-the-art time-resolved reconstruction method. The results showed that the proposed time-resolved 3D cardiopulmonary MRI reconstruction using STNs offers a robust and efficient approach to obtain high-quality images. This method effectively overcomes the limitations of conventional 3D cardiac MRI techniques and has the potential to improve the diagnosis and treatment planning of cardiopulmonary disorders.</p></abstract>