Manifestation of Subclinical Extrapulmonary Tuberculosis after COVID-19 Vaccination as Supraclavicular Lymphadenopathy.

Lymphadenopathy after coronavirus disease 2019 (COVID-19) vaccination is a common side effect that usually resolves within several days to weeks, and only observation is recommended. However, for prolonged lymphadenopathy, other possibilities, including malignancy or other lymphoproliferative diseases, may be considered. Herein, we report the case of a 66-year-old woman who experienced prolonged ipsilateral supraclavicular lymph node enlargement after the second dose of the ChAdOx1 (Oxford-AstraZeneca) COVID-19 vaccine, which was eventually diagnosed as extrapulmonary tuberculosis.

Chronic Obstructive Pulmonary Disease Combined with Interstitial Lung Disease.

Although chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) have distinct clinical features, both diseases may coexist in a patient because they share similar risk factors such as smoking, male sex, and old age. Patients with both emphysema in upper lung fields and diffuse ILD are diagnosed with combined pulmonary fibrosis and emphysema (CPFE), which causes substantial clinical deterioration. Patients with CPFE have higher mortality compared with patients who have COPD alone, but results have been inconclusive compared with patients who have idiopathic pulmonary fibrosis (IPF). Poor prognostic factors for CPFE include exacerbation, lung cancer, and pulmonary hypertension. The presence of interstitial lung abnormalities, which may be an early or mild form of ILD, is notable among patients with COPD, and is associated with poor prognosis. Various theories have been proposed regarding the pathophysiology of CPFE. Biomarker analyses have implied that this pathophysiology may be more closely associated with IPF development, rather than COPD or emphysema. Patients with CPFE should be advised to quit smoking and undergo routine lung function tests, and pulmonary rehabilitation may be helpful. Various pharmacologic agents and surgical approaches may be beneficial in patients with CPFE, but further studies are needed.

COVID-19: Highlighting Health Disparities in the Los Angeles Latinx Community.

Objective: Characterization of COVID-19 in the Latinx community is necessary for guiding public health initiatives, health system policy, clinical management practices, and improving outcomes. Our aim was to describe the socioeconomic background and clinical profile of patients with COVID-19 at a large public hospital in Los Angeles to improve health disparities leading to poor outcomes during the pandemic.Design, Setting and Participants: A single center retrospective cross-sectional study of all patients with a positive polymerase chain reaction (PCR) test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who presented to Los Angeles County (LAC)+University of Southern California (USC) Medical Center between March 15, 2020 and April 30, 2020.Methods: We describe patient characteristics, socioeconomic factors, laboratory findings, and outcomes of the first 278 patients to present to LAC+USC Medical Center with COVID-19.Results: Patients self-identified as Hispanic (82.4%) or non-Hispanic (17.6%). Hispanic patients presented later from symptom onset (6 days vs 3 days, P = 0.027) and had higher post-intubation mortality (40.9% vs. 33.3%, P = 1), intensive care unit (ICU) mortality (31.1% vs. 22.2%, P = 0.87), and overall mortality (11.1% vs 10.2%, P = 1). However, the difference in admission rates, mechanical ventilation rates, and overall mortality rates were not statistically significant. A majority of patients, 275/278 (98.9%), reported residency ZIP codes in areas of higher population density, higher percentage of Latinx, born outside the United States, lower median income, and lower high school graduation rate when compared to the rest of Los Angeles County. Regression analysis within the Hispanic cohort found that age, history of hypertension, history of diabetes, lactate dehydrogenase (LDH), and C-reactive protein (CRP) were predictors of mechanical ventilation and mortality.Conclusion: We show the Latinx community has been disproportionally affected by the pandemic in Los Angeles and we identified multiple socioeconomic and clinical characteristics that predispose this population to COVID-19 infection. This study highlights the need for change in local and national strategies to protect vulnerable communities during public health outbreaks.

COVID-19 Vaccination-Associated Lymphadenopathy on FDG PET/CT: Distinctive Features in Adenovirus-Vectored Vaccine.

PURPOSE: This study investigated 18F-FDG PET/CT features of adenovirus-vectored vaccination against COVID-19 in healthy subjects. PATIENTS AND METHODS: Thirty-one health care workers had been vaccinated Vaxzevria and underwent FDG PET/CT as an optional test for a cancer screening program. Size and FDG uptake of the hypermetabolic lymph nodes were measured. Uptake value of spleen was also measured with liver for comparison. RESULTS: All examinees who underwent FDG PET/CT within 14 days' interval showed hypermetabolic lymphadenopathies ipsilateral to vaccine injection. All examinees with hypermetabolic lymphadenopathy had simultaneous muscular uptakes until 23 days' interval. Among 12 examinees who underwent FDG PET/CT more than 15 days after vaccination, only 3 male examinees did not show hypermetabolism in the axillary lymph nodes. There was no female examinee with negative hypermetabolic lymphadenopathy until 29 days after vaccination. CONCLUSIONS: Hypermetabolic reactive lymphadenopathy in the ipsilateral axillary area with or without supraclavicular area is most likely to occur in a healthy person with recent adenovirus-vectored COVID-19 vaccination on FDG PET/CT.

Honduras: two hurricanes, COVID-19, dengue and the need for a new digital health surveillance system.

A recently published article of this journal stated that informatics solutions can guide better public health decision-making during the COVID 19 (Coronavirus Disease 2019) pandemic. Honduras is a country facing the COVID-19 pandemic with a weak health surveillance system while also fighting a dengue epidemic and the aftermath of two hurricanes that struck its territory in November 2020. In response, we as academics started a COVID-19 and Dengue Observatory combining several technological platforms and developing multidisciplinary research to help the country navigate the crisis. Mapping the pandemic and the natural disasters showed us that technology can be applied toward epidemiology to benefit communities in a time of need by quickly building a basic digital health surveillance system for Honduras.

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal pharyngitis, which can cause immune-mediated and post-infectious complications. The recent global pandemic of coronavirus disease (COVID-19) encourages the use of telemedicine for patients with respiratory symptoms. This study, therefore, purposes automated detection of severe pharyngitis using a deep learning framework with self-taken throat images. METHODS: A dataset composed of two classes of 131 throat images with pharyngitis and 208 normal throat images was collected. Before the training classifier, we constructed a cycle consistency generative adversarial network (CycleGAN) to augment the training dataset. The ResNet50, Inception-v3, and MobileNet-v2 architectures were trained with transfer learning and validated using a randomly selected test dataset. The performance of the models was evaluated based on the accuracy and area under the receiver operating characteristic curve (ROC-AUC). RESULTS: The CycleGAN-based synthetic images reflected the pragmatic characteristic features of pharyngitis. Using the synthetic throat images, the deep learning model demonstrated a significant improvement in the accuracy of the pharyngitis diagnosis. ResNet50 with GAN-based augmentation showed the best ROC-AUC of 0.988 for pharyngitis detection in the test dataset. In the 4-fold cross-validation using the ResNet50, the highest detection accuracy and ROC-AUC achieved were 95.3% and 0.992, respectively. CONCLUSION: The deep learning model for smartphone-based pharyngitis screening allows fast identification of severe pharyngitis with a potential of the timely diagnosis of pharyngitis. In the recent pandemic of COVID-19, this framework will help patients with upper respiratory symptoms to improve convenience in diagnosis and reduce transmission.

Comparison of media and standards for SARS-CoV-2 RT-qPCR without prior RNA preparation.

Since the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there have been demands on the testing infrastructure that have strained testing capacity. As a simplification of method, we confirm the efficacy of RNA extraction-free RT-qPCR and saline as an alternative patient sample storage buffer. In addition, amongst potential reagent shortages, it has sometimes been difficult to obtain inactivated viral particles. We have therefore also characterized armored SARS-CoV-2 RNA from Asuragen as an alternative diagnostic standard to ATCC genomic SARS-CoV-2 RNA and heat inactivated virions and provide guidelines for its use in RT-qPCR.