Analysis and management of the COVID-19 pandemic impact on a multispecialty diagnostic imaging department

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.

Severe headache after adenoviral-vector vaccination against coronavirus disease 2019: a case report

Background: Several cases of vaccine-induced prothrombotic immune thrombocytopenia (VIPIT) following exposition to adenoviral- vector vaccines against SARS-CoV-2 were described. The risk of developing intracranial thrombosis is high in subjects with severe headache, thrombocytopenia and d-dimer increase. Clinical Case: In July 2021 a 20-year-old woman, without risk factors for thrombosis, presented to the emergency room with headache and hematomas in the lower limbs. Ten days earlier she had received the Ad26.CoV2 vaccine (Johnson & Johnson/Jansenn). The blood tests showed thrombocytopenia, increase in d-dimer value, normal level of hemoglobin. A CT scan with contrast enhancement of the head excluded thrombosis of the intracranial veins or hemorrhage. The patient was hospitalized in the internal medicine ward;on admission she reported severe headache with normal neurological examination. The laboratory studies showed: d-dimer 34.430 ng/ml, fibrinogen 64 mg/dl, platelet count 65 x 103/mcl. Upon diagnosis of VIPIT the patient was treated with high dose intravenous immunoglobulins (IVIG), 800 mg/kg for two days. On the second day after IVIG infusion platelet count was 143.000/mmc, d-dimer value 2369 ng/ml and the headache had resolved. Conclusions: The clinical presentation, the laboratory and instrumental findings, the response to the treatment supported a prothrombotic condition, potentially associated with microthrombosis in intracranial smaller veins. Our experience suggests that early use of IVIG can be efficacious in avoiding the evolution into manifest thrombosis.

Ct-derived chest muscle metrics for outcome prediction in covid-19 patients

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.