Pre COVID-19 usage of smartphones and medical applications among medical students

Background: To determine awareness of medical students that utilize smartphone and their familiarity of medical applications.Methods: The questionnaire-based descriptive study was conducted in December 2019 and comprised medical students of first year and second year of the CMH Kharian Medical College, Kharian, and Nawaz Sharif Medical College, Gujrat, Gujranwala Medical College, Gujranwala and Mohi-ud-Din Islamic Medical College, Mirpur. Questionnaires were distributed in the classrooms and were filled by the students anonymously. SPSS 20 was used for statistical analysis.Results: Among the 770 medical students in the study, 747 (97%) had smartphones and 23 (3%) were using simple cell phones. Overall, 362 (47%) of the smart phone users were using some medical apps. Besides, 223 (29%) were aware of the medical apps but were not using them. Also, 655 (85%) students were not using any type of medical text eBooks through their phone, and only 115 (15%) had relevant text eBooks in their phones.Conclusions: A very low awareness among medical college students exists regarding smartphones as a gadget for improving medical knowledge

DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function

The structure and topology of the pulmonary arteries is crucial to understand, plan, and conduct medical treatment in the thorax area. Due to the complex anatomy of the pulmonary vessels, it is not easy to distinguish between the arteries and veins. The pulmonary arteries have a complex structure with an irregular shape and adjacent tissues, which makes automatic segmentation a challenging task. A deep neural network is required to segment the topological structure of the pulmonary artery. Therefore, in this study, a Dense Residual U-Net with a hybrid loss function is proposed. The network is trained on augmented Computed Tomography volumes to improve the performance of the network and prevent overfitting. Moreover, the hybrid loss function is implemented to improve the performance of the network. The results show an improvement in the Dice and HD95 scores over state-of-the-art techniques. The average scores achieved for the Dice and HD95 scores are 0.8775 and 4.2624 mm, respectively. The proposed method will support physicians in the challenging task of preoperative planning of thoracic surgery, where the correct assessment of the arteries is crucial

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders