Radiology indispensable for tracking COVID-19

With the rapid spread of COVID-19 worldwide, early detection and efficient isolation of suspected patients are especially important to prevent the transmission. Although nucleic acid testing of SARS-CoV-2 is still the gold standard for diagnosis, there are well-recognized early-detection problems including time-consuming in the diagnosis process, noticeable false-negative rate in the early stage and lacking nucleic acid testing kits in some areas. Therefore, effective and rational applications of imaging technologies are critical in aiding the screen and helping the diagnosis of suspected patients. Currently, chest computed tomography is recommended as the first-line imaging test for detecting COVID-19 pneumonia, which could allow not only early detection of the typical chest manifestations, but also timely estimation of the disease severity and therapeutic effects. In addition, other radiological methods including chest X-ray, magnetic resonance imaging, and positron emission computed tomography also show significant advantages in the detection of COVID-19 pneumonia. This review summarizes the applications of radiology and nuclear medicine in detecting and diagnosing COVID-19. It highlights the importance for these technologies to curb the rapid transmission during the pandemic, considering findings from special groups such as children and pregnant women.     

Interventional oncology at the time of COVID-19 pandemic: Problems and solutions

The COVID-19 pandemic has deeply impacted the activity of interventional oncology in hospitals and cancer centers. In this review based on official recommendations of different international societies, but also on local solutions found in different expert large-volume centers, we discuss the changes that need to be done for the organization, safety, and patient management in interventional oncology. A literature review of potential solutions in a context of scarce anesthesiologic resources, limited staff and limited access to hospital beds are proposed and discussed based on the literature data.     

Increased Firearm Injury During the COVID-19 Pandemic: A Hidden Urban Burden

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COVID-19 pneumonia: A review of typical CT findings and differential diagnosis

The standard of reference for confirming COVID-19 relies on microbiological tests such as real-time polymerase chain reaction (RT-PCR) or sequencing. However, these tests might not be available in an emergency setting. Computed tomography (CT) can be used as an important complement for the diagnosis of COVID-19 pneumonia in the current epidemic context. In this review, we present the typical CT features of COVID-19 pneumonia and discuss the main differential diagnosis.     

Imaging of COVID-19: An update of current evidences

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been reported as a global emergency. As respiratory dysfunction is a major clinical presentation of COVID-19, chest computed tomography (CT) plays a central role in the diagnosis and management of patients with COVID-19. Recent advances in imaging approaches using artificial intelligence have been essential as a quantification and diagnostic tool to differentiate COVID-19 from other respiratory infectious diseases. Furthermore, cardiovascular involvement in patients with COVID-19 is not negligible and may result in rapid worsening of the disease and sudden death. Cardiac magnetic resonance imaging can accurately depict myocardial involvement in SARS-CoV-2 infection. This review summarizes the role of the radiology department in the management and the diagnosis of COVID-19, with a special emphasis on ultra-high-resolution CT findings, cardiovascular complications and the potential of artificial intelligence.     

Chest CT in COVID-19 pneumonia: A review of current knowledge

The current COVID-19 pandemic has highlighted the essential role of chest computed tomography (CT) examination in patient triage in the emergency departments, allowing them to be referred to “COVID” or “non-COVID” wards. Initial chest CT examination must be performed without intravenous administration of iodinated contrast material, but contrast material administration is required when pulmonary embolism is suspected, which seems to be frequent in severe forms of the disease. Typical CT features consist of bilateral ground-glass opacities with peripheral, posterior and basal predominance. Lung disease extent on CT correlates with clinical severity. Artificial intelligence could assist radiologists for diagnosis and prognosis evaluation.     

Decreased Incidence of Hirschsprung-Associated Enterocolitis During COVID-19 Across United States Children's Hospitals

BackgroundThe Coronavirus Disease 2019 pandemic provided a natural experiment to study the effect of social distancing on the risk of developing Hirschsprung's Associated Enterocolitis (HAEC).MethodsUsing the Pediatric Health Information System (PHIS), a retrospective cohort study of children (<18 years) with Hirschsprung's Disease (HSCR) across 47 United States children's hospitals was performed. The primary outcome was HAEC admissions per 10,000 patient-days. The exposure (COVID-19) was defined as April 2020–December 2021. The unexposed (historical control) period was April 2018–December 2019. Secondary outcomes included sepsis, bowel perforation, intensive care unit (ICU) admission, mortality, and length of stay.ResultsOverall, we included 5707 patients with HSCR during the study period. There were 984 and 834 HAEC admissions during the pre-pandemic and pandemic periods, respectively (2.6 vs. 1.9 HAEC admissions per 10,000 patient-days, incident rate ratio [95% confidence interval]: 0.74 [0.67, 0.81], p < 0.001). Compared to pre-pandemic, those with HAEC during the pandemic were younger (median [IQR]: 566 [162, 1430] days pandemic vs. 746 [259, 1609] days pre-pandemic, p < 0.001) and more likely to live in the lowest quartile of median household income zip codes (24% pandemic vs. 19% pre-pandemic, p = 0.02). There were no significant differences in rates of sepsis (6.1% pandemic vs. 6.1% pre-pandemic, p > 0.9), bowel perforation (1.3% pandemic vs. 1.2% pre-pandemic, p = 0.8), ICU admissions (9.6% pandemic vs. 12% pre-pandemic, p = 0.2), mortality (0.5% pandemic vs. 0.6% pre-pandemic, p = 0.8), or length of stay (median [interquartile range]: 4 [(Pastor et al., 2009; Gosain and Brinkman, 2015) 2,112,11 days pandemic vs. 5 [(Pastor et al., 2009; Tang et al., 2020) 2,102,10 days pre-pandemic, p = 0.4).ConclusionsThe COVID-19 pandemic was associated with significantly decreased incidence of HAEC admissions across US children's hospitals. Possible etiologies such as social distancing should be explored.Level of evidenceII.     

Understanding Hispanic Patient Satisfaction with Telehealth During COVID-19

BackgroundRecent studies have described the use of telehealth for pediatric surgical care during the COVID-19 pandemic. We aimed to evaluate equity in telehealth use by comparing rates of utilization and satisfaction with pediatric surgical telemedicine among Hispanic patients.MethodsWe conducted a retrospective cohort study of patients seen by a surgical subspecialty provider in the outpatient setting at a quaternary pediatric hospital between April 1 and June 30, 2020. Patients evaluated in the same three-month period in 2019 were analyzed as a historic control. Differences in Family Experience Survey (FES) responses based on race and ethnicity and preferred language of care were assessed using univariable and multivariable generalized linear modeling.ResultsThe pandemic cohort included fewer patients of Hispanic ethnicity and fewer Spanish-speakers. After controlling for visit type, comparison of Spanish-speaking and English-speaking patients revealed that Spanish-speaking families had significantly lower scores for FES items that evaluated healthcare provider explaining (IRR 0.74, 95% CI: 0.61–0.90), listening (IRR 0.76, 95% CI: 0.63–0.92), and time spent with the family (IRR 0.73, 95% CI: 0.60–0.89). There were no differences in FES responses based on insurance status or degree of medical complexity.ConclusionsTelehealth services were less commonly used among Hispanic and Spanish-speaking patients. Language may differentially affect family satisfaction with healthcare and telehealth solutions. Strategies to mitigate these inequities are needed and may include strengthening interpreter services and providing language-concordant care.Level of evidenceLevel IV.     

COVID-19: A qualitative chest CT model to identify severe form of the disease

PurposeThe purpose of this study was to identify clinical and chest computed tomography (CT) features associated with a severe form of coronavirus disease 2019 (COVID-19) and to propose a quick and easy to use model to identify patients at risk of a severe form.Materials and methodsA total of 158 patients with biologically confirmed COVID-19 who underwent a chest CT after the onset of the symptoms were included. There were 84 men and 74 women with a mean age of 68 ± 14 (SD) years (range: 24–96 years). There were 100 non-severe and 58 severe cases. Their clinical data were recorded and the first chest CT examination was reviewed using a computerized standardized report. Univariate and multivariate analyses were performed in order to identify the risk factors associated with disease severity. Two models were built: one was based only on qualitative CT features and the other one included a semi-quantitative total CT score to replace the variable representing the extent of the disease. Areas under the ROC curves (AUC) of the two models were compared with DeLong's method.ResultsCentral involvement of lung parenchyma (P < 0.001), area of consolidation (P < 0.008), air bronchogram sign (P < 0.001), bronchiectasis (P < 0.001), traction bronchiectasis (P < 0.011), pleural effusion (P < 0.026), large involvement of either one of the upper lobes or of the middle lobe (P < 0.001) and total CT score ≥ 15 (P < 0.001) were more often observed in the severe group than in the non-severe group. No significant differences were found between the qualitative model (large involvement of either upper lobes or middle lobe [odd ratio (OR) = 2.473], central involvement [OR = 2.760], pleural effusion [OR = 2.699]) and the semi-quantitative model (total CT score ≥ 15 [OR = 3.342], central involvement [OR = 2.344], pleural effusion [OR = 2.754]) with AUC of 0.722 (95% CI: 0.638–0.806) vs. 0.739 (95% CI: 0.656–0.823), respectively (P = 0.209).ConclusionWe have developed a new qualitative chest CT-based multivariate model that provides independent risk factors associated with severe form of COVID-19.