Strokecopilot: a literature-based clinical decision support system for acute ischemic stroke treatment.

BACKGROUND: Acute ischemic stroke (AIS) is an immediate emergency whose management is becoming more and more personalized while facing a limited number of neurologists with high expertise. Clinical decision support systems (CDSS) are digital tools leveraging information and artificial intelligence technologies. Here, we present the Strokecopilot project, a CDSS for the management of the acute phase of AIS. It has been designed to support the evidence-based medicine reasoning of neurologists regarding the indications of intravenous thrombolysis (IVT) and endovascular treatments (ET). METHODS: Reference populations were manually extracted from the field's main guidelines and randomized clinical trials (RCT). Their characteristics were harmonized in a computerized reference database. We developed a web application whose algorithm identifies the reference populations matching the patient's characteristics. It returns the latter's outcomes in a graphical user interface (GUI), whose design has been driven by real-world practices. RESULTS: Strokecopilot has been released at www.digitalneurology.net . The reference database includes 25 reference populations from 2 guidelines and 15 RCTs. After a request, the reference populations matching the patient characteristics are displayed with a summary and a meta-analysis of their results. The status regarding IVT and ET indications are presented as "in guidelines", "in literature", or "outside literature references". The GUI is updated to provide several levels of explanation. Strokecopilot may be updated as the literature evolves by loading a new version of the reference populations' database. CONCLUSION: Strokecopilot is a literature-based CDSS, developed to support neurologists in the management of the acute phase of AIS.

High Prevalence of Deep Venous Thrombosis in Non-Severe COVID-19 Patients Hospitalized for a Neurovascular Disease.

INTRODUCTION: Severe SARS-CoV-2 infection induces COVID-19 along with venous thromboembolic occurrences particularly in intensive care units. For non-severe COVID-19 patients affected by neurovascular diseases, the prevalence of deep venous thrombosis (DVT) is unknown. The aim of our study was to report data obtained after systematic Doppler ultrasound scanning (DUS) of lower limbs in such patients. METHODS: Between March 20 and May 2, 2020, the deep venous system of 13 consecutive patients diagnosed with neurovascular diseases and non-severe COVID-19 was investigated with a systematic bedside DUS. RESULTS: Thirteen patients were enrolled in the study including 9 acute ischaemic strokes, 1 occlusion of the ophthalmic artery, 1 transient ischaemic attack, 1 cerebral venous thrombosis and 1 haemorrhagic stroke. On admission, the median National Institute of Health Stroke Scale (NIHSS) score was of 6 (IQR, 0-20). During the first week after admission, and despite thromboprophylaxis, we found a prevalence of 38.5% of asymptomatic calves' DVT (n = 5). One patient developed a symptomatic pulmonary embolism and 2 other patients died during hospitalization. The outcome was positive for the other patients with a discharge median NIHSS score of 1 (IQR, 0-11). DISCUSSION/CONCLUSION: Despite thromboprophylaxis, systematic bedside DUS showed a high prevalence (38.5%) of asymptomatic DVT in non-severe COVID-19 patients suffering from a neurovascular disease. In the absence of a reliable marker of DVT, we suggest that this non-invasive investigation could be an interesting tool to monitor peripheral venous thrombotic complications in such patients.