How to recognize pulmonary embolism in syncope patients: A simple rule.

BACKGROUND: Syncope can be the presenting symptom of Pulmonary Embolism (PE). It is not known wether using a standardized algorithm to rule-out PE in all patients with syncope admitted to the Emergency Departments (ED) is of value or can lead to overdiagnosis and overtreatment. METHODS: We tested if simple anamnestic and clinical parameters could be used as a rule to identify patients with syncope and PE in a multicenter observational study. The rule's sensitivity was tested on a cohort of patients that presented to the ED for syncopal episodes caused by PE. The clinical impact of the rule was assessed on a population of consecutive patients admitted for syncope in the ED. RESULTS: Patients were considered rule-positive in the presence of any of the following: hypotension, tachycardia, peripheral oxygen saturation ≤ 93 % (SpO2), chest pain, dyspnea, recent history of prolonged bed rest, clinical signs of deep vein thrombosis, history of previous venous thrombo-embolism and active neoplastic disease. The sensitivity of the rule was 90.3 % (95 % CI: 74.3 % to 98.0 %). The application of the rule to a population of 217 patients with syncope would have led to a 70 % reduction in the number of subjects needing additional diagnostic tests to exclude PE. CONCLUSIONS: Most patients with syncope due to PE present with anamnestic and clinical features indicative of PE diagnosis. A clinical decision rule can be used to identify patients who would benefit from further diagnostic tests to exclude PE, while reducing unnecessary exams that could lead to over-testing and over-diagnosis.

Incidence of delayed bleeding in patients on antiplatelet therapy after mild traumatic brain injury: a systematic review and meta-analysis.

BACKGROUND: The scientific evidence regarding the risk of delayed intracranial bleeding (DB) after mild traumatic brain injury (MTBI) in patients administered an antiplatelet agent (APA) is scant and incomplete. In addition, no consensus exists on the utility of a routine repeated head computed tomography (CT) scan in these patients. OBJECTIVE: The aim of this study was to evaluate the risk of DB after MTBI in patients administered an APA. METHODS: A systematic review and meta-analysis of prospective and retrospective observational studies enrolling adult patients with MTBI administered an APA and who had a second CT scan performed or a clinical follow-up to detect any DB after a first negative head CT scan were conducted. The primary outcome was the risk of DB in MTBI patients administered an APA. The secondary outcome was the risk of clinically relevant DB (defined as any DB leading to neurosurgical intervention or death). RESULTS: Sixteen studies comprising 2930 patients were included in this meta-analysis. The pooled absolute risk for DB was 0.77% (95% CI 0.23-1.52%), ranging from 0 to 4%, with substantial heterogeneity (I2 = 61%). The pooled incidence of clinically relevant DB was 0.18%. The subgroup of patients on dual antiplatelet therapy (DAPT) had an increased DB risk, compared to the acetylsalicylic acid (ASA)-only patients (2.64% vs. 0.22%; p = 0.04). CONCLUSION: Our systematic review showed a very low risk of DB in MTBI patients on antiplatelet therapy. We believe that such a low rate of DB could not justify routine repeated CT scans in MTBI patients administered a single APA. We speculate that in the case of clinically stable patients, a repeated head CT scan could be useful for select high-risk patients and for patients on DAPT before discharge.

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments.

Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has infected more than 34 million persons in a worldwide pandemic leading to over one million deaths worldwide (data from the Johns Hopkins University). Since the virus begun to spread, emergency departments were busy with COVID-19 patients for whom a quick decision regarding in- or outpatient care was required. The virus can cause characteristic abnormalities in chest radiographs (CXR), but, due to the low sensitivity of CXR, additional variables and criteria are needed to accurately predict risk. Here, we describe a computerized system primarily aimed at extracting the most relevant radiological, clinical, and laboratory variables for improving patient risk prediction, and secondarily at presenting an explainable machine learning system, which may provide simple decision criteria to be used by clinicians as a support for assessing patient risk. To achieve robust and reliable variable selection, Boruta and Random Forest (RF) are combined in a 10-fold cross-validation scheme to produce a variable importance estimate not biased by the presence of surrogates. The most important variables are then selected to train a RF classifier, whose rules may be extracted, simplified, and pruned to finally build an associative tree, particularly appealing for its simplicity. Results show that the radiological score automatically computed through a neural network is highly correlated with the score computed by radiologists, and that laboratory variables, together with the number of comorbidities, aid risk prediction. The prediction performance of our approach was compared to that that of generalized linear models and shown to be effective and robust. The proposed machine learning-based computational system can be easily deployed and used in emergency departments for rapid and accurate risk prediction in COVID-19 patients.

Introduction of a standardised protocol, including systematic use of tranexamic acid, for management of severe adult trauma patients in a low-resource setting: the MSF experience from Port-au-Prince, Haiti.

BACKGROUND: Bleeding is an important cause of death in trauma victims. In 2010, the CRASH-2 study, a multicentre randomized control trial on the effect of tranexamic acid (TXA) administration to trauma patients with suspected significant bleeding, reported a decreased mortality in randomized patients compared to placebo. Currently, no evidence on the use of TXA in humanitarian, low-resource settings is available. We aimed to measure the hospital outcomes of adult patients with severe traumatic bleeding in the Médecins Sans Frontières Tabarre Trauma Centre in Port-au-Prince, Haiti, before and after the implementation of a Massive Haemorrhage protocol including systematic early administration of TXA. METHODS: Patients admitted over comparable periods of four months (December2015- March2016 and December2016 - March2017) before and after the implementation of the Massive Haemorrhage protocol were investigated. Included patients had blunt or penetrating trauma, a South Africa Triage Score ≥ 7, were aged 18-65 years and were admitted within 3 h from the traumatic event. Measured outcomes were hospital mortality and early mortality rates, in-hospital time to discharge and time to discharge from intensive care unit. RESULTS: One-hundred and sixteen patients met inclusion criteria. Patients treated after the introduction of the Massive Haemorrhage protocol had about 70% less chance of death during hospitalization compared to the group "before" (adjusted odds ratio 0.3, 95%confidence interval 0.1-0.8). They also had a significantly shorter hospital length of stay (p = 0.02). CONCLUSIONS: Implementing a Massive Haemorrhage protocol including early administration of TXA was associated with the reduced mortality and hospital stay of severe adult blunt and penetrating trauma patients in a context with poor resources and limited availability of blood products.