Clinicians Must Go Beyond FAST When Diagnosing Acute Stroke

 Only partly right, I'd suggest removing clinicians also and just go with these much faster objective diagnosis tools.

Maybe you want these much faster objective diagnosis options.

Hats off to Helmet of Hope - stroke diagnosis in 30 seconds; February 2017

 

Microwave Imaging for Brain Stroke Detection and Monitoring using High Performance Computing in 94 seconds March 2017

 

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The latest here:

Clinicians Must Go Beyond FAST When Diagnosing Acute Stroke 

Stroke diagnosis can be challenging for clinicians, primarily because the clinical manifestations, patient reported symptoms, and physical examination findings are highly variable. Subtle stroke signs are frequently missed, researchers reported at the 2021 American Association of Nurse Practitioners National Conference (AANP 2021).¹

In the US, over 795,000 people are impacted by stroke each year, representing a leading cause of chronic adult disability. Rapid recognition of stroke signs and symptoms, transportation to and treatment at an accredited stroke center, and thrombolytic administration can reduce both disability and cost of care.

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The FAST acronym—face, arm, speech, and time—is widely used in both public and health care settings to identify stroke symptoms, but the tool can exclude more subtle signs and symptoms. To describe the limitations of currently available stroke screening as well as newer modifications made to these tools to improve diagnostic accuracy, Stephanie Rosser, DNP, APRN, of the University of Texas Medical Branch School of Nursing in Galveston, Texas, conducted a literature review.

Twenty-four articles were reviewed and 8 were included in the final analysis: 4 systematic reviews and 4 case control, cohort, or descriptive studies. Four studies were determined to provide level 1 evidence and 4 studies were of level 4 evidence.

The first systematic review, published in 2016, found that the Melbourne Ambulance Stroke Scale (MASS), Medic Prehospital Assessment for Code Stroke (MedPACS), and Ontario Prehospital Stroke Screening (OPSS) tools were evaluated only in a single prehospital setting, with high variability in the sensitivity and specificity of the studies.² The remaining 3 systematic reviews, found that the Cincinnati Pre-Hospital Stroke Scale (CPSS) had a high degree of both sensitivity and specificity in field settings and should be used preferentially over other scales.^3-5

ROSIER Test Has a Higher Sensitivity Over FAST

Zhelev et al found that in emergency department settings, both Recognition of Stroke in the Emergency Room (ROSIER) and FAST demonstrated similar levels of accuracy.⁴ However, the ROSIER scale was evaluated in more studies with “consistently higher sensitivity” compared with FAST, making it the test of choice.⁴ Meyran and colleagues reported that both FAST and OPSS were associated with “a positive increase in the number of patients who received timely reperfusion treatment.”⁵

BE-FAST May Improve Diagnostic Accuracy

The case control, cohort, and descriptive studies found that patients who presented with typical posterior stroke symptoms (nausea, vomiting, and dizziness) received delayed evaluation and 14% of stroke diagnoses were missed using the FAST acronym.^6-8 However, adding balance and eye examination to the acronym (BE-FAST) reduced the number of missed strokes.⁸

Finally, results of a study by Oostema and colleagues showed that adding the finger to nose test to the CPSS improved recognition of posterior stroke in field settings.⁹

“Current stroke screening tools generally perform well when patients display overt signs of stroke [hemiparesis and neglect],” Dr Rosser concluded. “However, they lack sensitivity in recognizing more subtle signs associated with [posterior circulating stroke] including visual changes, balance, dizziness, nausea, and vomiting.”

“Providers must be aware of the limitations of existing stroke screening tools and suggested modifications to improve identification of acute stroke, particularly [posterior circulating stroke], to ensure timely treatment,” she concluded.

 

Does Use of the Recognition Of Stroke In the Emergency Room Stroke Assessment Tool Enhance Stroke Recognition by Ambulance Clinicians?

Why haven't we gotten to objective diagnosis of type of stroke rather than continuing down this subjective path? Like maybe one of these 17.  Does no one think at all?
http://stroke.ahajournals.org/content/44/11/3007.abstract.html?etoc

1. Rachael T. Fothergill, PhD;
2. Julia Williams, PhD;
3. Melanie J. Edwards, PhD;
4. Ian T. Russell, DSc, FRCPEd;
5. Patrick Gompertz, MBChB, FRCP

+ Author Affiliations

1. From the Clinical Audit and Research Unit, London Ambulance Service National Health Service (NHS) Trust, London, United Kingdom (R.T.F., M.J.E.); School of Health and Social Work, University of Hertfordshire, Hatfield, United Kingdom (J.W.); College of Medicine, Swansea University, Swansea, United Kingdom (I.T.R.); and Royal London Hospital, Barts Health NHS Trust, London, United Kingdom (P.G.).

1. Correspondence to Rachael Fothergill, PhD, London Ambulance Service NHS Trust, 8–20 Pocock St, London, SE1 0BW, United Kingdom. E-mail rachael.fothergill@lond-amb.nhs.uk

Abstract

Background and Purpose—UK ambulance services assess patients with suspected stroke using the Face Arm Speech Test (FAST). The Recognition Of Stroke In the Emergency Room (ROSIER) tool has been shown superior to the FAST in identifying strokes in emergency departments but has not previously been tested in the ambulance setting. We investigated whether ROSIER use by ambulance clinicians can improve stroke recognition.

Methods—Ambulance clinicians used the ROSIER in place of the FAST to assess patients with suspected stroke. As the ROSIER includes all FAST elements, we calculated a FAST score from the ROSIER to enable comparisons between the two tools. Ambulance clinicians’ provisional stroke diagnoses using the ROSIER and calculated FAST were compared with stroke consultants’ diagnosis. We used stepwise logistic regression to compare the contribution of individual ROSIER and FAST items and patient demographics to the prediction of consultants’ diagnoses.

Results—Sixty-four percent of strokes and 78% of nonstrokes identified by ambulance clinicians using the ROSIER were subsequently confirmed by a stroke consultant. There was no difference in the proportion of strokes correctly detected by the ROSIER or FAST with both displaying excellent levels of sensitivity. The ROSIER detected marginally more nonstroke cases than the FAST, but both demonstrated poor specificity. Facial weakness, arm weakness, seizure activity, age, and sex predicted consultants’ diagnosis of stroke.

Conclusions—The ROSIER was not better than the FAST for prehospital recognition of stroke. A revised version of the FAST incorporating assessment of seizure activity may improve stroke identification and decision making by ambulance clinicians.