Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective.

As health systems organize to deliver the highest quality stroke care to their patients, there is increasing emphasis being placed on prehospital stroke recognition, accurate diagnosis, and efficient triage to improve outcomes after stroke. Emergency medical services (EMS) personnel currently rely heavily on dispatch accuracy, stroke screening tools, bypass protocols and prehospital notification to care for patients with suspected stroke, but novel tools including mobile stroke units and telemedicine-enabled ambulances are already changing the landscape of prehospital stroke care. Herein, the authors provide our perspective on the current state of prehospital stroke diagnosis and triage including several of these emerging trends. Then, we provide commentary to highlight potential artificial intelligence (AI) applications to improve stroke detection, improve accurate and timely dispatch, enhance EMS training and performance, and develop novel stroke diagnostic tools for prehospital use.

High-throughput metabolite profiling: identification of plasma taurine as a potential biomarker of functional outcome after aneurysmal subarachnoid hemorrhage.

OBJECTIVE: Metabolite profiling (or metabolomics) can identify candidate biomarkers for disease and potentially uncover new pathways for intervention. The goal of this study was to identify potential biomarkers of functional outcome after subarachnoid hemorrhage (SAH). METHODS: The authors performed high-throughput metabolite profiling across a broad spectrum of chemical classes (163 metabolites) on plasma samples taken from 191 patients with SAH who presented to Massachusetts General Hospital between May 2011 and October 2016. Samples were drawn at 3 time points following ictus: 0-5, 6-10, and 11-14 days. Elastic net (EN) and LASSO (least absolute shrinkage and selection operator) machine learning analyses were performed to identify metabolites associated with 90-day functional outcomes as assessed by the modified Rankin Scale (mRS). Additional univariate and multivariate analyses were then conducted to further examine the relationship between metabolites and clinical variables and 90-day functional outcomes. RESULTS: One hundred thirty-seven (71.7%) patients with aneurysmal SAH met the criteria for inclusion. A good functional outcome (mRS score 0-2) at 90 days was found in 79 (57.7%) patients. Patients with good outcomes were younger (p = 0.002), had lower admission Hunt and Hess grades (p < 0.0001) and modified Fisher grades (p < 0.0001), and did not develop hydrocephalus (p < 0.0001) or delayed cerebral ischemia (DCI) (p = 0.049). EN and LASSO machine learning methods identified taurine as the leading metabolite associated with 90-day functional outcome (p < 0.0001). Plasma concentrations of the amino acid taurine from samples collected between days 0 and 5 after aneurysmal SAH were 21.9% (p = 0.002) higher in patients with good versus poor outcomes. Logistic regression demonstrated that taurine remained a significant predictor of functional outcome (p = 0.013; OR 3.41, 95% CI 1.28-11.4), after adjusting for age, Hunt and Hess grade, modified Fisher grade, hydrocephalus, and DCI. CONCLUSIONS: Elevated plasma taurine levels following aneurysmal SAH predict a good 90-day functional outcome. While experimental evidence in animals suggests that this effect may be mediated through downregulation of pro-inflammatory cytokines, additional studies are required to validate this hypothesis in humans.