Diagnostic accuracy of clinical tools for assessment of acute stroke: a systematic review

Abstract

Introduction: Recanalisation therapy in acute ischaemic stroke is highly time-sensitive, and requires early identification of eligible patients to ensure better outcomes. Thus, a number of clinical assessment tools have been developed and this review examines their diagnostic capabilities. Methods: Diagnostic performance of currently available clinical tools for identification of acute ischaemic and haemorrhagic strokes and stroke mimicking conditions was reviewed. A systematic search of the literature published in 2015-2018 was conducted using PubMed, EMBASE, Scopus and The Cochrane Library. Prehospital and in-hospital studies with a minimum sample size of 300 patients reporting diagnostic accuracy were selected. Results: Twenty-five articles were included. Cortical signs (gaze deviation, aphasia and neglect) were shown to be significant indicators of large vessel occlusion (LVO). Sensitivity values for selecting subjects with LVO ranged from 23% to 99% whereas specificity was 24% to 97%. Clinical tools, such as FAST-ED, NIHSS, and RACE incorporating cortical signs as well as motor dysfunction demonstrated the best diagnostic accuracy. Tools for identification of stroke mimics showed sensitivity varying from 44% to 91%, and specificity of 27% to 98% with the best diagnostic performance demonstrated by FABS (90% sensitivity, 91% specificity). Hypertension and younger age predicted intracerebral haemorrhage whereas history of atrial fibrillation and diabetes were associated with ischaemia. There was a variation in approach used to establish the definitive diagnosis. Blinding of the index test assessment was not specified in about 50% of included studies. Conclusions: A wide range of clinical assessment tools for selecting subjects with acute stroke has been developed in recent years. Assessment of both cortical and motor function using RACE, FAST-ED and NIHSS showed the best diagnostic accuracy values for selecting subjects with LVO. There were limited data on clinical tools that can be used to differentiate between acute ischaemia and haemorrhage. Diagnostic accuracy appeared to be modest for distinguishing between acute stroke and stroke mimics with optimal diagnostic performance demonstrated by the FABS tool. Further prehospital research is required to improve the diagnostic utility of clinical assessments with possible application of a two-step clinical assessment or involvement of simple brain imaging, such as transcranial ultrasonography.

A Bayesian Framework to Optimize Performance of Pre-Hospital Stroke Triage Scales

“…Current prediction scales have low sensitivity (range 38% to 67%) for LVO-given their superficial focus on gross deficitsbut high specificity (80% to 93%). [12][13][14][15][16][17] A meta-analysis estimated that with a positive LVO prediction test, the LVO probability could be 50% to 60% depending on LVO prevalence in the population, but the probability with a negative test could still be ≥10%. 13 Thinking of patient-centered care, such a low sensitivity means that treatment might be withheld/delayed from patients who might still benefit from it, which is suboptimal, especially when considering that most pre-hospital tools are used in relatively wealthy, industrial countries with sufficient healthcare resources.…”

Validation of a shortened FAST-ED algorithm for smartphone app guided stroke triage

“…Among these, the Rapid Arterial Occlusion Evaluation (RACE) and the Field Assessment Stroke Triage for Emergency Destination (FAST-ED) have shown to be superior to other LVO recognition scales. 7 For both scales smartphone app versions are available. 8 This provides the opportunity to digitally transmit the results to the target hospital stroke team prior to hospital admission.…”

FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service

“…Among them, the simple and short Field Assessment Stroke Triage for Emergency Destination (FAST-ED) scale yields high sensitivity by adding cortical symptoms to the regular FAST-test. 4 Previous studies have shown superior prediction quality in comparison to other LVO recognition scores; 5 however, in-field validation has not yet been studied. In addition, very limited experience with prehospital smartphone-assisted assessment of stroke patients by paramedic EMS personnel is available 6 and further proof of practicability is urgently needed.…”