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Introduction The propose of this study was to evaluate the impact of the first two waves of the COVID-19 pandemic on a multispecialty radiology department in a large tertiary university hospital in Northern Italy. Methods The numbers of all radiological exams performed in the radiology department of Scientific Institute for Research, Hospitalization and Healthcare (namely, IRCCS) Policlinico San Donato (San Donato Milanese, Italy) from March 2019 to March 2021 were collected and compared, subdividing them both temporally, modality, sub-specialty, and setting. Results Comparing the first 12 months of the COVID-19 pandemic (from March 2020 to February 2021) with the previous 12 months (from March 2019 to February 2020), there was an overall decrease in total radiological examinations equal to 26% (from 127,998 to 94,550). The most affected modality was DXA (from 4,706 to 2,989, -36%), followed by ultrasonography (from 17,212 to 11,644, -32%), digital radiography (from 66,050 to 47,374, -28%), MRI (from 13,332 to 10,140, -24%), CT (from 19,208 to 15,746, -18%), and mammograms (from 7,490 to 6,657, -11%). Chest CTs of inpatients saw a +15% surge (from 1,087 to 1,144), with far larger sizable increments being observed for chest X-ray examinations of outpatients (from 3,032 to 7,536, +131%). Further sub-analysis according to pandemic waves highlighted an overall -65% decrease of radiological services during the first wave (from March to May 2020), curtailed to -3% during the June–October period and then again rising to -23% during the second wave (from November 2020 to February 2021). Conclusion The COVID-19 pandemic led to a marked decrease of total radiological examinations during the two pandemic waves, limited to -26% by the implementation of safety protocols during the second wave and by increased activity during the inter-wave period.
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Background/Introduction: Brazil is among the 10 biggest pharmaceutical markets in the world [1] and local recent publications show that prevalence of adverse events of medicines on Brazilian population is around 6.6% [2] and hospitalizations caused by potential side effects can reach a prevalence of approximately 46% [3]. Despite that, population does not have enough information about rational use of medicines. Besides, there is lack of capacity building among healthcare professionals (HCPs) and health services (HS) about their role in the healthcare with regards to safe use of medicines. Objective/Aim: HCPs need to be instructed and encouraged to recognize and report adverse events of medicines inside and outside of the HS. With this, they will be able to make communities aware of the importance of taking care and paying special attention on medicine's use. Methods: Through a partnership between different stakeholders (pharmaceutical industry, academia, clinical practice), it was built a e-learning-set for HCPs based on the real need of target audience by sharing knowledge and experiences about correct, safe and rational use of medicines. Results: A 30-h online "Patient Safety and Pharmacovigilance" Course split in 4 modules was offered by Pharmacy College (Universidade de Sao Paulo) and FIPFARMA (Fundacao Instituto de Pesquisas Farmaceuticas) in Nov 2020. There were recorded classes, synchronous meetings and also workshops about the main topics: Overview of Healthcare and Pharmacovigilance (PV);Drug Safety and Management of Drug Utilization;Patient Safety Culture. 51 participants were approved and they expressed the importance of the course to improve adverse event notification flow in HS, enhance quality of existing processes, promote activities of education to other HCPs, including the development of a PV system from scratch in a covid-19 HS. Conclusion: The e-learning format course was an effective tool to achieve and integrate HCPs in pandemics time, providing knowledge and changing mindset about PV. This initiative demonstrated that cocreation by different stakeholders with one common purpose "patient safety" can make the difference improving people's live preventing and avoiding any unnecessary risk related to medicines.
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Purpose or Learning Objective: Decreased muscle mass is a predictor of unfavorable outcome in several conditions, but its prognostic impact on COVID-19 patients is unknown. We assessed and compared the contribution of computed tomography (CT)-derived muscle status and lung parenchymal features in predicting clinical outcomes in COVID-19 patients. Methods or Background: Clinical/laboratory data and clinical outcomes (intensive care unit [ICU] admission and death) were retrieved retrospectively for patients with COVID-19 confirmed by reverse transcriptase polymerase chain reaction who underwent chest CT on admission in four hospitals in northern Italy from February 21 to April 30, 2020. Extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation of paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral levels. Multivariate linear and binary logistic regression were used to find associations between variables in predicting ICU admission or death and to obtain predictive models, including odds ratios (ORs), tested and compared using receiver operating characteristic curve (ROC) analysis. Results or Findings: A total of 552 patients (364 men;median age: 65 years;interquartile range: 54-75) were included. In a CT-based model (including lung and muscle status), reduced paravertebral muscle area at the T5 level showed the highest ORs for ICU admission (4.83;p < .001) and death (2.25;p = .027). When this model was extended to include clinical variables, reduced paravertebral muscle area at the T5 level still showed the highest ORs both for ICU admission (4.34;p < .001) and death (2.28;p = .001). At ROC analysis comparing these models, the chest CT-based model had the same area under the curve (AUC) for ICU admission prediction (0.83;p = .380) and a nonsignificantly lower AUC for death prediction (0.86 versus 0.87;p =. 282). Conclusion: The combination of CT-derived lung parenchymal features and muscle status allowed us to predict outcomes reliably of COVID-19 patients, without a relevant contribution from clinical variables.
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Introduction: Chest x-ray (CXR) severity score and obesity are predictive risk factors for COVID-19 hospital admission. However, the relationship between abdominal obesity and CXR severity score is not fully explored. Methods: This retrospective cohort study analyzed the association of different adiposity indexes, including waist circumference and body mass index (BMI), with CXR severity score in 215 hospitalized patients with COVID-19. Results: Patients with abdominal obesity had significantly higher CXR severity scores (Figure 1A) and higher rates of these scores than those without abdominal obesity (P<0.001;P=0.001, respectively) while there were no significant differences between BMI classes (P=0.104;P=0.271, respectively) (Figure 1B). Waist circumference and waist-to-height ratio correlated more closely with CXR severity score than BMI (r=0.43, P<0.001;r=0.41, P<0.001;r=0.17, P=0.012, respectively). The AUCs for waist circumference and WHtR were significantly higher than those for BMI for distinguishing a high CXR severity score (≥8) (0.68 [0.60-0.75] and 0.67 [0.60-0.74] vs 0.58 [0.51-0.66], P=0.001) (Figure 2). Multivariable analysis indicated abdominal obesity (risk ratio: 1.75, 95% CI: 1.25-2.45, P<0.001), bronchial asthma (risk ratio: 1.73, 95% CI: 1.07-2.81, P=0.026) and oxygen saturation at admission (risk ratio: 0.96, 95% CI: 0.94-0.97, P<0.001) as the only independent predictors of a high CXR severity score. Conclusion: Abdominal obesity might predict a high CXR severity score better than general obesity in hospitalized patients with COVID-19. Therefore, in hospital clinical practice waist circumference should be assessed and patients with abdominal obesity should be monitored closely.