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Background: In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting., Objectives: We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI., Methods: This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes., Results: Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0-0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46-50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4-9 %, vs standard cutoff)., Conclusions: The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency., Clinical Trial Registration: Clinicaltrials.gov, NCT04430400., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic and so it is crucial the right evaluation of viral infection. According to the Centers for Disease Control and Prevention (CDC), the Real-Time Reverse Transcription PCR (RT-PCR) in respiratory samples is the gold standard for confirming the disease. However, it has practical limitations as time-consuming procedures and a high rate of false-negative results. We aim to assess the accuracy of COVID-19 classifiers based on Arificial Intelligence (AI) and statistical classification methods adapted on blood tests and other information routinely collected at the Emergency Departments (EDs)., Methods: Patients admitted to the ED of Careggi Hospital from April 7th-30th 2020 with pre-specified features of suspected COVID-19 were enrolled. Physicians prospectively dichotomized them as COVID-19 likely/unlikely case, based on clinical features and bedside imaging support. Considering the limits of each method to identify a case of COVID-19, further evaluation was performed after an independent clinical review of 30-day follow-up data. Using this as a gold standard, several classifiers were implemented: Logistic Regression (LR), Quadratic Discriminant Analysis (QDA), Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN), K-nearest neighbor (K-NN), Naive Bayes (NB)., Results: Most of the classifiers show a ROC >0.80 on both internal and external validation samples but the best results are obtained applying RF, LR and NN. The performance from the external validation sustains the proof of concept to use such mathematical models fast, robust and efficient for a first identification of COVID-19 positive patients. These tools may constitute both a bedside support while waiting for RT-PCR results, and a tool to point to a deeper investigation, by identifying which patients are more likely to develop into positive cases within 7 days., Conclusions: Considering the obtained results and with a rapidly changing virus, we believe that data processing automated procedures may provide a valid support to the physicians facing the decision to classify a patient as a COVID-19 case or not., Competing Interests: The authors declare no conflict of interest. AA is serving as one of the Editorial Board members and Guest editors of this journal. AF was the Guest Editor of this journal. We declare that AA and AF had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to RJPA., (© 2023 The Author(s). Published by IMR Press.)

Background: Lung ultrasound (LUS) has a role in the diagnosis of pulmonary embolism (PE) mainly based on the visualization of pulmonary infarctions. However, examining the whole chest to detect small peripheral infarctions by LUS may be challenging. Pleuritic pain, a frequent presenting symptom in patients with PE, is usually localized in a restricted chest area identified by the patient itself. Our hypothesis is that sensitivity of LUS for PE in patients with pleuritic chest pain may be higher due to the possibility of focusing the examination in the painful area. We combined data from three prospective studies on LUS in patients suspected of PE and extracted data regarding patients with and without pleuritic pain at presentation to compare the performances of LUS., Results: Out of 872 patients suspected of PE, 217 (24.9%) presented with pleuritic pain and 279 patients (32%) were diagnosed with PE. Pooled sensitivity of LUS for PE in patients with and without pleuritic chest pain was 81.5% (95% CI 70-90.1%) and 49.5% (95% CI 42.7-56.4%) (p < 0.001), respectively. Specificity of LUS was similar in the two groups, respectively 95.4% (95% CI 90.7-98.1%) and 94.8% (95% CI 92.3-97.7%) (p = 0.86). In patients with pleuritic pain, a diagnostic strategy combining Wells score with LUS performed better both in terms of sensitivity (93%, 95% CI 80.9-98.5% vs 90.7%, 95% CI 77.9-97.4%) and negative predictive value (96.2%, 95% CI 89.6-98.7% vs 93.3%, 95% CI 84.4-97.3%). Efficiency of Wells score + LUS outperformed the conventional strategy based on Wells score + d-dimer (56.7%, 95% CI 48.5-65% vs 42.5%, 95% CI 34.3-51.2%, p = 0.02)., Conclusions: In a population of patients suspected of PE, LUS showed better sensitivity for the diagnosis of PE when applied to the subgroup with pleuritic chest pain. In these patients, a diagnostic strategy based on Wells score and LUS performed better to exclude PE than the conventional strategy combining Wells score and d-dimer., (© 2022. The Author(s).)

To investigate the effects of the dramatic reduction in presentations to Italian Emergency Departments (EDs) on the main indicators of ED performance during the SARS-CoV-2 pandemic. From February to June 2020 we retrospectively measured the number of daily presentations normalized for the number of emergency physicians on duty (presentations/physician ratio), door-to-physician and door-to-final disposition (length-of-stay) times of seven EDs in the central area of Tuscany. Using the multivariate regression analysis we investigated the relationship between the aforesaid variables and patient-level (triage codes, age, admissions) or hospital-level factors (number of physician on duty, working surface area, academic vs. community hospital). We analyzed data from 105,271 patients. Over ten consecutive 14-day periods, the number of presentations dropped from 18,239 to 6132 (- 67%) and the proportion of patients visited in less than 60 min rose from 56 to 86%. The proportion of patients with a length-of-stay under 4 h decreased from 59 to 52%. The presentations/physician ratio was inversely related to the proportion of patients with a door-to-physician time under 60 min (slope - 2.91, 95% CI - 4.23 to - 1.59, R 2  = 0.39). The proportion of patients with high-priority codes but not the presentations/physician ratio, was inversely related to the proportion of patients with a length-of-stay under 4 h (slope - 0.40, 95% CI - 0.24 to - 0.27, R 2  = 0.36). The variability of door-to-physician time and global length-of-stay are predicted by different factors. For appropriate benchmarking among EDs, the use of performance indicators should consider specific, hospital-level and patient-level factors., (© 2021. Società Italiana di Medicina Interna (SIMI).)

Objectives: To investigate the extent of synaptic loss, and the contribution of gray matter (GM) inflammation and demyelination to synaptic loss, in multiple sclerosis (MS) brain tissue., Methods: This study was performed on two different post-mortem series of MS and control brains, including deep GM and cortical GM. MS brain samples had been specifically selected for the presence of active demyelinating GM lesions. Over 1,000,000 individual synapses were identified and counted using confocal microscopy, and further characterized as glutamatergic/GABAergic. Synaptic counts were also correlated with neuronal/axonal loss., Results: Important synaptic loss was observed in active demyelinating GM lesions (-58.9%), while in chronic inactive GM lesions, synaptic density was only mildly reduced compared to adjacent non-lesional gray matter (NLGM) (-12.6%). Synaptic loss equally affected glutamatergic and GABAergic synapses. Diffuse synaptic loss was observed in MS NLGM compared to control GM (-21.2% overall)., Conclusion: This study provides evidence, in MS brain tissue, of acute synaptic damage/loss during active GM inflammatory demyelination and of synaptic reorganization in chronically demyelinated GM, affecting equally glutamatergic and GABAergic synapses. Furthermore, this study provides a strong indication of widespread synaptic loss in MS NLGM also independently from focal GM demyelination.

Objectives: To assess concurrent validity of the Dynamic Silver Code (DSC), a tool based on administrative data that predicts prognosis in older adults accessing the emergency department (ED), in terms of association with markers of poor functional and cognitive status., Design: Cross-sectional., Setting and Participants: Data were obtained in the AIDEA study, which enrolled a cohort of ≥75-year-old patients, accessing the ED of 2 hospitals in Florence, Italy., Methods: The DSC score and classes (I to IV, corresponding to an increasing risk of death) were obtained from administrative data. Information on health and functional status prior to ED access were collected from face-to-face, direct, or proxy interviews. The 4AT test was administered to screen for possible delirium. Bivariate comparisons of the prevalence of each functional and cognitive marker across 4 DSC classes were performed. Multinomial logistic regression was used to assess the multivariable risk of being in II, III, or IV DSC class vs I., Results: Among 3358 participants (mean age 83 years, men 44%), 32.9%, 30.3%, 19.5%, and 17.2% were in DSC class I, II, III, and IV. Preadmission abnormal functional and cognitive conditions, and delirium in the ED, were increasingly more common from DSC class I through IV (P < .001). In particular, the prevalence of total inability to walk increased from 2.9% (class I) to 23.4% (class IV). In multivariable analyses, this was the strongest predictor of being in progressively worse DSC classes, whereas feeling of exhaustion, reporting of serious falls, weight loss, and severe memory loss or diagnosis of dementia gave some contribution., Conclusions and Implications: The ability of the DSC to predict survival in older persons appears to rely on its prevailing association with markers of functional impairment. These results may support clinical use of the tool., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Acute brain injury (ABI) can cause out of hospital cardiac arrest (OHCA). The aim of this study was to compare clinical features, mortality and potential for organ donation in patients with OHCA due to ABI vs other causes., Methods: From January 2017 to December 2018, all adult patients presenting to ED for OHCA were considered for the study. Two physicians established the definitive cause of OHCA, according to clinical, laboratory, diagnostic imaging and autoptic findings. Clinical features in patients with OHCA due to ABI or other causes were compared., Results: 280 patients were included in the analysis. ABI was the third most frequent cause of OHCA (21, 7.5%); ABIs were 8 subarachnoid hemorrhage, 8 intracerebral hemorrhage, 2 ischemic stroke, 2 traumatic spinal cord injury and 1 status epilepticus respectively. Neurological prodromes such as seizure, headache and focal neurological signs were significantly more frequent in patients with OHCA due to ABI (OR 5.34, p = 0.03; OR 12.90, p = 0.02; and OR 66.53, p < 0.01 respectively) while among non-neurological prodromes chest pain and dyspnea were significantly more frequent in patients with OHCA due to other causes (OR 14.5, p < 0.01; and OR 10.4, p = 0.02 respectively). Anisocoria was present in 19% of patients with OHCA due to ABI vs 2.7% due to other causes (OR 8.47, p < 0.01). In 90.5% of patients with ABI and in 53.1% of patients with other causes the first cardiac rhythm was non shockable (OR 8.1; p = 0.05). Multivariate logistic regression analysis revealed that older age, active smoking, post-traumatic OHCA, neurological prodromes, anisocoria at pupillary examination were independently associated with OHCA due to ABI. Patients with ABI showed a higher mortality compared with the other causes group (19 pts., 90.5% versus 167 pts., 64.5%; p = 0.015). Potential organ donors were more frequent among ABI than other causes group (10 pts., 47.6% vs 75 pts., 28.9%) however the difference did not reach the statistical significance (p = 0.07)., Conclusions: ABI is the third cause of OHCA. Neurological prodromes, absence of chest pain and dyspnea before cardiac arrest, anisocoria and initial non-shockable rhythm might suggest a neurological etiology of the cardiac arrest. Patients with OHCA due to ABI has an unfavorable outcome, however, they could be candidate to organ donation., Competing Interests: Declaration of Competing Interest none., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose:  Diverticulitis is a common cause of abdominal pain and CT scan is commonly used for its diagnosis in the emergency department (ED). The diagnostic performance of point-of-care ultrasound (POCUS) integrated into a clinical exam for diverticulitis is still not established. We evaluate the accuracy of clinical-sonographic assessment for the diagnosis of diverticulitis and whether POCUS could improve the selection of patients needing CT scan for complicated diverticulitis., Materials and Methods:  This is a multicentric observational study involving adult patients suspected of having diverticulitis presenting at 4 EDs. 21 sonographer physicians were asked to diagnose diverticulitis and complicated diverticulitis based on clinical-sonographic assessment. The final diagnosis was established by two reviewers, blinded to POCUS, based on data collected during the one-month follow-up comprehensive CT scan., Results:  Among 393 enrolled patients, 218 (55.5 %) were diagnosed with diverticulitis and 33 (8 %) had complicated diverticulitis. The time to diagnosis by the sonographer physicians was shorter compared to standard care (97 ± 102 vs. 330 ± 319 minutes, p < 0.001). Clinical-sonographic assessment showed optimal sensitivity (92.7 %) and specificity (90.9 %) for diverticulitis. However, the sensitivity (50 %) for complicated diverticulitis was low. The sonographer physician would have proceeded to CT scan in 194 (49.4 %) patients and the CT scan request compared to the final diagnosis of complicated diverticulitis demonstrated 94 % sensitivity., Conclusion:  Clinical-sonographic assessment is rapid and accurate for the diagnosis of diverticulitis. Even if POCUS has low sensitivity for complicated diverticulitis, it can be used to safely select patients needing CT., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)