Starting from 1st case in Italy, on February 20th, 2020, CO-rona VI-rus D-isease 2019 (COVID-19) pandemic spread to whole Italian territory, with different regional distribution. Tuscany has been classified as medium diffusion area (40-100 cases/100000 inhabitants). In this context, all healthcare structures reviewed their organization to meet new needs. Our study’s objectives were description of organizational model outlined to safely manage Emergency Department (ED) and analysis of patients’ flows within Hospital of Pisa during pandemic. The ED has been reorganized with dedicated areas for examination and waiting for tests results. A similar reduction (-62%) of ED accesses comparing to the same period of 2019 and the previous months of 2020 was observed. Hospital Task Force arranged for progressive activation of Units by modules, according to territorial needs. From the beginning of March to the end of April 2020, 315 COVID-19 patients were hospitalized. Overall, a 45% reduction in hospital admissions compared to the same period of 2019 was observed, with increased mortality (4% versus 2%). The University Hospital of Pisa efficiently managed COVID-19 emergency with a logistical reorganization of ED.

Background: Nomograms are easy-to-handle clinical tools which can help in estimating the risk of adverse outcome in certain population. This multi-center study aims to create and validate a simple and usable clinical prediction nomogram for individual risk of post-traumatic Intracranial Hemorrhage (ICH) after Mild Traumatic Brain Injury (MTBI) in patients treated with Direct Oral Anticoagulants (DOACs). Methods: From January 1, 2016 to December 31, 2019, all patients on DOACs evaluated for an MTBI in five Italian Emergency Departments were enrolled. A training set to develop the nomogram and a test set for validation were identified. The predictive ability of the nomogram was assessed using AUROC, calibration plot, and decision curve analysis. Results: Of the 1425 patients in DOACs in the study cohort, 934 (65.5%) were included in the training set and 491 (34.5%) in the test set. Overall, the rate of post-traumatic ICH was 6.9% (7.0% training and 6.9% test set). In a multivariate analysis, major trauma dynamic (OR: 2.73, p = 0.016), post-traumatic loss of consciousness (OR: 3.78, p = 0.001), post-traumatic amnesia (OR: 4.15, p < 0.001), GCS < 15 (OR: 3.00, p < 0.001), visible trauma above the clavicles (OR: 3. 44, p < 0.001), a post-traumatic headache (OR: 2.71, p = 0.032), a previous history of neurosurgery (OR: 7.40, p < 0.001), and post-traumatic vomiting (OR: 3.94, p = 0.008) were independent risk factors for ICH. The nomogram demonstrated a good ability to predict the risk of ICH (AUROC: 0.803; CI95% 0.721–0.884), and its clinical application showed a net clinical benefit always superior to performing CT on all patients. Conclusion: The Hemorrhage Estimate Risk in Oral anticoagulation for Mild head trauma (HERO-M) nomogram was able to predict post-traumatic ICH and can be easily applied in the Emergency Department (ED).

Background/Objectives: Dyspnea is one of the main causes of visits to the Emergency Department (ED) and hospitalization, with its differential diagnosis representing a challenge for the clinician. Lung ultrasound (LUS) is a widely used tool in ED. The objective of this study was to evaluate the impact of LUS, performed by a non-expert operator, in determining diagnosis and prognosis of patients with dyspnea. Methods: A total of 60 patients presenting with dyspnea at the ED were prospectively enrolled and underwent LUS examination by a medical student, after brief training, within 3 h of triage. LUS findings were classified into four patterns: N.1, absence of notable ultrasound findings, attributable to COPD/ASMA exacerbation; N.2, bilateral interstitial syndrome, suggestive of acute heart failure; N.3, subpleural changes/parenchymal consolidations, suggestive of pneumoniae; and N.4, isolate polygonal triangular consolidation, attributable to infarction in the context of pulmonary thromboembolism. Results: The diagnostic hypothesis formulated after LUS was compared with the final diagnosis after further investigations in the ED, showing agreement in 90% of cases. The mean LUS score value was higher in patterns N.2 (18.4 ± 8.5) and N.3 (17 ± 6.6), compared to patterns N.1 and N.4 (9.8± 6.7 and 11.5 ± 2.1). Given the high prevalence of pattern N.2, the diagnostic accuracy of LUS in this context was further evaluated, showing a sensitivity of 82% and specificity of 100%. In terms of the prognostic value of LUS, hospitalized patients had a higher LUS score compared to those discharged (17.3 ± 8.1 vs. 8.5 ± 6.8, p value 0.004). A similar trend was obtained in the subgroup of patients requiring non-invasive ventilation (NIV), who present a higher LUS score (21.1 ± 6.6 vs. 13.1 ± 8.1, p value 0.002). When considering a combined outcome (death and NIV), patients with worse outcomes more often had a LUS score > 15 (p value < 0.001). Conclusions: In conclusion, this study confirms that LUS is a very useful tool in the ED, assisting the clinical evaluation for diagnosis, treatment decision, and determination of the appropriate care setting for patients with acute dyspnea. Its short learning curve allows even non-expert staff to use it effectively.

SARS-CoV-2 management in Emergency Department: risk stratification and care setting identification proposal based on first pandemic wave in Pisa University Hospital Background: COVID-19 patients require early treatment and admission to an appropriate care setting, considering possible rapid and unpredictable to Severe Acute Respiratory Syndrome. Objective: A flow-chart was developed by a multidisciplinary team of Emergency Department (ED) clinicians, intensivists and radiologists aiming to provide tools for disease severity stratification, appropriate ventilation strategy and hospitalization setting identification. Methods: We conducted a retrospective application of our model on 313 hospitalized patients at Pisa University Hospital including 222 patients admitted to ED for respiratory failure between March and April 2020. Risk stratification score was based on respiratory and chest imaging parameters, while management strategy on comorbidities and age. Results: Age, comorbidities, clinical respiratory and arterial blood gas parameters, semi-quantitative chest computed tomography score were significant predictors of mortality (p<0,05). Mortality rate was higher in patients treated in intensive care units (26,5%) and undergoing endo-tracheal intubation (32,7%), compared to medical area (21,3%). We verified a good concordance (81,7%) between the proposed model and actual evaluation in ED. Outcomes analysis of subgroups of patients homogeneous for baseline features allowed to verify safety of our model: in non-elderly and/or non-comorbid patients (15% mortality) our scheme overestimates the risk in 30% of cases, but it suggests non-intensive management in patients with reduced functional reserve, elderly and with comorbidities (50% mortality). Conclusion: Correct management of respiratory failure COVID-19 patients is crucial in this unexpected pandemic. Our flow-chart, despite retrospectively application in small sample, could represents a valid and safe proposal for evaluation in ED.