The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated applications that can meet clinical accuracy requirements. In this study, customized and pre-trained deep learning models based on convolutional neural networks were used to detect pneumonia caused by COVID-19 respiratory complications. Chest X-ray images from 368 confirmed COVID-19 patients were collected locally. In addition, data from three publicly available datasets were used. The performance was evaluated in four ways. First, the public dataset was used for training and testing. Second, data from the local and public sources were combined and used to train and test the models. Third, the public dataset was used to train the model and the local data were used for testing only. This approach adds greater credibility to the detection models and tests their ability to generalize to new data without overfitting the model to specific samples. Fourth, the combined data were used for training and the local dataset was used for testing. The results show a high detection accuracy of 98.7% with the combined dataset, and most models handled new data with an insignificant drop in accuracy.

Al-Mistarehi AH, et al. Clin Exp Vaccine Res. 2021 May;10(2):171-182. https://doi.org/10.7774/cevr.2021.10.2.171

Background: Coronavirus disease 2019 (COVID-19) viral course and behavior remain unpredictable. This study describes incubation time and viral clearance of COVID-19 hospitalized cases in Northern Jordan. Methods: All COVID-19 confirmed cases hospitalized from March 15 to June 09, 2020, were included. Nasopharyngeal swabs were collected, and COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) was performed every two days in all cases. The viral cure was defined when two negative RT-PCR tests were obtained ≥ 24 hours apart. Viral clearance time (VCT) reflects the time from the first positive nasopharyngeal swab to the first of two consecutive negative tests. Results: In this cohort, a total of 157 patients were included. Most cases resulted from two major outbreaks. The median incubation period was 6 days (IQR, 3– 10) and ranged from 1 to 17 days. The median VCT was 13 days (IQR, 7– 2) and ranged from 1 to 40 days. Symptomatic presentation and abnormal chest radiograph were predictors for a prolonged VCT (p=0.015 and p=0.014, respectively). The median time of resolution of symptoms was 7 days (IQR, 3– 10 days). Most symptomatic cases (91.7%) remained RT-PCR positive for up to 20 days after symptoms resolution, with a median of 13.5 days. VCT significantly correlated with the incubation period (p=0.013). Conclusion: Viral cure lagged for as long as 20 days after resolution of symptoms. Continuing with social-distancing, frequent hand hygiene, and wearing facial mask remains essential and is recommended even after clinical resolution of symptoms.

Prevalence of undiagnosed COPD in male patients with coronary artery disease: a cross-sectional study in Jordan Basheer Y Khassawneh,1 Shaher M Samrah,1 Mohamad I Jarrah,1 Rasheed K Ibdah,1 Ali M Ibnian,1 Abdelhameed W Almistarehi,1 Aseel A Zghayer,1 Saddam I Abuqudairi,1 Yousef S Khader2 1Department of Internal Medicine, Public Health and Family Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan; 2Department of Community Medicine, Public Health and Family Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan Purpose: COPD and coronary artery disease (CAD) are common chronic diseases with shared risk factors. COPD continues to be largely underdiagnosed and undertreated. We aimed to describe the prevalence and predictors of undiagnosed COPD in Jordanian men with CAD. Patients and methods: In a cross-sectional study conducted at a referral center in Jordan, male patients who underwent coronary angiography for suspected CAD and reported ≥10 pack-year of cigarette smoking were recruited. Pre- and post-bronchodilator spirometry was undertaken for all participants, and COPD was defined as post-bronchodilator FEV1/FVC

Objective: Unusual clinical course Background: Congenital insensitivity to pain with anhidrosis (CIPA), also referred to as hereditary sensory and autonomic neuropathy type IV, is a rare autosomal recessive disease caused by mutations in the NTRK1 gene. The inability to feel pain and temperature often leads to repeated severe and unintentional self-inflicted injuries; these can result in severe complications, as patients heal slowly from skin and bone injuries. This case report describes a 5-year-old Palestinian girl with self-inflicted injury to the digits, a dislocated distal inter-phalangeal joint of the left big toe, and a diagnosis of CIPA. Case Report: A 5-year-old girl, a daughter of related Palestinian Bedouin parents, presented with a chronic unhealed wound over the planter surface of the left foot. Painless repetitive minor traumata over the same area badly affected wound healing and this led to wound dehiscence and dislocation of the distal inter-phalangeal joint of the left big toe. Surgical fixation of the dislocated joint along with intravenous antibiotics and close follow-up resulted in eventual improvement and near complete wound healing despite the obviously slow healing process. The girl also displayed evidence of unintentional self-inflicted injury, which within the overall clinical context warranted a clinical suspicion of CIPA. This was confirmed by genetic testing for the presence of a homozygous frameshift mutation in the NTRK1 gene (c.1842_1843insT; p.Pro615Serfs*12). Conclusions: This case report shows that a physician should have a low threshold of suspicion to investigate for CIPA when managing children with multiple unintentional self-inflicted injuries, anhidrosis, and pain insensitivity, mainly through genetic testing to detect mutations in the NTRK1 gene.