EDITORIAL
Are prehospital stroke scales better than a coin toss at predicting acute stroke?
Gillian Gordon-Perue, MBBS, DM Tatjana Rundek, MD, PhD
Correspondence to Dr. Rundek: [email protected] Neurology® 2014;82:2154–2155
Acute therapy for ischemic stroke is exquisitely time sensitive.1 Patients treated within 90 minutes of symptom onset fare far better than patients treated beyond 90 minutes,2 with a 1.5 greater likelihood of ambulating independently at discharge, a 1.3 greater likelihood of discharge to home, and a 0.74 lower likelihood of dying in hospital. Yet only 1%–8% of all ischemic stroke patients are currently treated within the “golden hour” after the onset of stroke symptoms.3 This persists even in urban settings, where the majority of patients live within 60 minutes of an acute stroke center.4 As a community of neurologists, we have improved our systems of care,4 shortened our door-to-needle times, and embarked on new innovations and technologies such as telestroke or ambulances with CT scanners.3 In addition, we have conducted trials of neuroprotective agents in the prehospital setting.5 All in an effort to bring our treatment to stroke patients within the golden hour. All this effort hinges on one question: How well can first responders recognize, and prehospital stroke scales accurately identify, the acute stroke patient? Despite the critical role that emergency medical services (EMS) plays in recognizing stroke and activating the stroke team, the structure of EMS systems varies widely among and even within countries.3 In this issue of Neurology®, Brandler et al.6 present the first-ever systematic review of prehospital stroke scales to answer this question.6 The study reports on the operating characteristics of 7 different prehospital stroke scales with the aim of identifying the bestperforming scale. They compare sensitivity (true positive rate) and specificity (true negative rate) for each scale to the gold standard of stroke diagnosis at discharge. The Face Arm Speech Time (FAST) scale is short, easy to remember, and often used in public education campaigns. In this systematic review, source data for the performance of FAST were derived from 295 persons in London. FAST has a high sensitivity of 0.97 (confidence interval [CI] 0.93–0.99), but this comes at the expense of specificity, 0.13 (CI 0.07–0.20). The overall result is that the receiver operating characteristic
(ROC) point estimate approaches the diagonal line of uncertainty (sensitivity 1 specificity 5 1). The Cincinnati Prehospital Stroke Scale (CPSS) differs from FAST only in the method of speech assessment. CPSS asks the patient to repeat a sentence whereas FAST assesses speech during the course of the conversation. CPSS is well-studied, with data readily available from 1,366 patients across 3 studies. It has been validated in the United States and Australia. However, the performance of CPSS is variable across studies and even within the same population, with sensitivity ranging from 0.79 (CI 0.72–0.85) to 0.98 (0.87–0.98). Of interest, the CIs do not overlap, thus creating questions about the reliability and reproducibility of CPSS. The Recognition of Stroke in the Emergency Room (ROSIER) includes an assessment of visual fields as part of a 7-item stroke scale. It was studied in 295 patients in London. In that analysis, the ROC point estimates of the FAST, CPSS, and ROSIER scales all approached the diagonal line of uncertainty, thus appearing to be no better than a coin toss. The Ontario Prehospital Stroke Scale (OPSS) is similar to the aforementioned scales but includes the additional requirement of a 2-hour arrival at the nearest stroke center. In this review, data from a Canadian trial of 554 patients were included. The sensitivity of OPSS was 0.92 (CI 0.88–0.94) and specificity was 0.86 (CI 0.80–0.90). The use of this prehospital scale and the accompanying change in the Ontario stroke network is credited with doubling the rate of thrombolytic therapy (IV recombinant tissue plasminogen activator) administration from 5.9% to 10.1%. The Los Angeles Prehospital Stroke Screen (LAPSS) goes a step further by screening for mimics such as hypoglycemia and seizures. It strives to identify ideal candidates for thrombolytic therapy by assessing the last time they were seen well and their premorbid functional level. It has been validated in multiple populations (United States, Australia, China) of varying ethnic backgrounds. Source data were available for 12,732 patients across 4 studies.
See page 2241 From the University of Miami Miller School of Medicine, FL. Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the editorial. 2154
© 2014 American Academy of Neurology
Its sensitivity and specificity among studies cluster and overlap well. Kidwell et al.7 showed a sensitivity of 0.91 (CI 0.76–0.98) and specificity of 0.97 (CI 0.93–0.99), vs Chen et al.,8 sensitivity 0.78 (CI 0.76– 0.81) and specificity 0.90 (CI 0.84–0.95). The Melbourne Ambulance Stroke Scale (MASS) is a combination of the LAPSS and the CPSS. Source data were available for 950 patients from 2 Melbourne studies. When the MASS and the LAPSS were simultaneously studied in the same population, they had indistinguishable operating characteristics. Therefore the MASS appeared to provide no additional benefit beyond using the LAPSS alone. To answer our question, it appears that prehospital scales performed variably across countries, some with no better odds than that of a coin toss. Furthermore, the LAPSS, which had the best operating characteristic and was the most reliable, still missed 22% of acute stroke patients. This study has limitations. Most of the data were collected retrospectively. The prevalence of stroke in each population varied widely, a substantial problem given that estimates of sensitivity and specificity depend heavily on the prevalence of the condition within the population. This study focuses the research spotlight on this critical first step along the stroke chain of survival and forces us, as a community, to ask ourselves: is it time for a national prehospital EMS stroke registry to track our performance better? Whether we use an existing prehospital system of stroke recognition or implement new models such as the Mobile Stroke Unit9 recently launched in Houston,10 this critical first step should not be left to chance. STUDY FUNDING No targeted funding reported.
DISCLOSURE The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.
REFERENCES 1. Saver JL. Time is brain: quantified. Stroke 2006;37:263–266. 2. Saver JL, Fonarow GC, Smith EE, et al. Time to treatment with intravenous tissue plasminogen activator and outcome from acute ischemic stroke. JAMA 2013;309:2480–2488. 3. Fassbender K, Balucani C, Walters S, Levine SR, Haass A, Grotta J. Streamlining of prehospital stroke management: the golden hour. Lancet Neurol 2013;12:585–596. 4. Schwamm L, Fayad P, Sacco RL, et al. Translating evidence into practice: a decade of efforts by the American Heart Association/American Stroke Association to reduce death and disability due to stroke: a presidential advisory form the American Heart Association/American Stroke Association. Stroke 2010;41:1051–1065. 5. Saver JL, Kidwell C, Eckstein M, Starkman S; for the FAST-MAG pilot trial investigators. Pre hospital neuroprotective therapy for acute stroke results of the Field Administration of Stroke Therapy-Magnesium (FASTMAG) pilot trial. Stroke 2004;35:e106–e108. 6. Brandler ES, Sharma M, Sinert RH, Levine SR. Prehospital stroke scales in urban environments: a systematic review. Neurology 2014;82:2241–2249. 7. Kidwell CS, Starkman S, Eckstein M, Weems K, Saver JL. Identifying stroke in the field: prospective validation of the Los Angeles Prehospital Stroke Screen (LAPSS). Stroke 2000;31:71–76. 8. Chen S, Sun H, Lei Y, et al. Validation of the Los Angeles Prehospital Stroke Screen (LAPSS) in a Chinese urban emergency medical service population. PLoS One 2013;8:e70742. 9. Walter S, Kostopoulos P, Haass A, et al. Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial. Lancet Neurol 2012;11:397–404. 10. Mann Lake D. UTHealth introduces the nation’s first mobile stroke unit: ambulance equipped with scanner to be part of EMS services for Houston area. Available at: https://www.uth.edu/media/story.htm?id=b1485cfc-110f4a4c-91ea-06b573b3ba6d. Published February 3, 2014. Accessed May 10, 2014.
Neurology 82
June 17, 2014
2155
Are prehospital stroke scales better than a coin toss at predicting acute stroke? Gillian Gordon-Perue and Tatjana Rundek Neurology 2014;82;2154-2155 Published Online before print May 21, 2014 DOI 10.1212/WNL.0000000000000531 This information is current as of May 21, 2014 Updated Information & Services
including high resolution figures, can be found at: http://www.neurology.org/content/82/24/2154.full.html
References
This article cites 9 articles, 4 of which you can access for free at: http://www.neurology.org/content/82/24/2154.full.html##ref-list-1
Permissions & Licensing
Information about reproducing this article in parts (figures,tables) or in its entirety can be found online at: http://www.neurology.org/misc/about.xhtml#permissions
Reprints
Information about ordering reprints can be found online: http://www.neurology.org/misc/addir.xhtml#reprintsus
Neurology ® is the official journal of the American Academy of Neurology. Published continuously since 1951, it is now a weekly with 48 issues per year. Copyright © 2014 American Academy of Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.
Are prehospital stroke scales better than a coin toss at predicting acute stroke?
Gillian Gordon-Perue, MBBS, DM Tatjana Rundek, MD, PhD
Correspondence to Dr. Rundek: [email protected] Neurology® 2014;82:2154–2155
Acute therapy for ischemic stroke is exquisitely time sensitive.1 Patients treated within 90 minutes of symptom onset fare far better than patients treated beyond 90 minutes,2 with a 1.5 greater likelihood of ambulating independently at discharge, a 1.3 greater likelihood of discharge to home, and a 0.74 lower likelihood of dying in hospital. Yet only 1%–8% of all ischemic stroke patients are currently treated within the “golden hour” after the onset of stroke symptoms.3 This persists even in urban settings, where the majority of patients live within 60 minutes of an acute stroke center.4 As a community of neurologists, we have improved our systems of care,4 shortened our door-to-needle times, and embarked on new innovations and technologies such as telestroke or ambulances with CT scanners.3 In addition, we have conducted trials of neuroprotective agents in the prehospital setting.5 All in an effort to bring our treatment to stroke patients within the golden hour. All this effort hinges on one question: How well can first responders recognize, and prehospital stroke scales accurately identify, the acute stroke patient? Despite the critical role that emergency medical services (EMS) plays in recognizing stroke and activating the stroke team, the structure of EMS systems varies widely among and even within countries.3 In this issue of Neurology®, Brandler et al.6 present the first-ever systematic review of prehospital stroke scales to answer this question.6 The study reports on the operating characteristics of 7 different prehospital stroke scales with the aim of identifying the bestperforming scale. They compare sensitivity (true positive rate) and specificity (true negative rate) for each scale to the gold standard of stroke diagnosis at discharge. The Face Arm Speech Time (FAST) scale is short, easy to remember, and often used in public education campaigns. In this systematic review, source data for the performance of FAST were derived from 295 persons in London. FAST has a high sensitivity of 0.97 (confidence interval [CI] 0.93–0.99), but this comes at the expense of specificity, 0.13 (CI 0.07–0.20). The overall result is that the receiver operating characteristic
(ROC) point estimate approaches the diagonal line of uncertainty (sensitivity 1 specificity 5 1). The Cincinnati Prehospital Stroke Scale (CPSS) differs from FAST only in the method of speech assessment. CPSS asks the patient to repeat a sentence whereas FAST assesses speech during the course of the conversation. CPSS is well-studied, with data readily available from 1,366 patients across 3 studies. It has been validated in the United States and Australia. However, the performance of CPSS is variable across studies and even within the same population, with sensitivity ranging from 0.79 (CI 0.72–0.85) to 0.98 (0.87–0.98). Of interest, the CIs do not overlap, thus creating questions about the reliability and reproducibility of CPSS. The Recognition of Stroke in the Emergency Room (ROSIER) includes an assessment of visual fields as part of a 7-item stroke scale. It was studied in 295 patients in London. In that analysis, the ROC point estimates of the FAST, CPSS, and ROSIER scales all approached the diagonal line of uncertainty, thus appearing to be no better than a coin toss. The Ontario Prehospital Stroke Scale (OPSS) is similar to the aforementioned scales but includes the additional requirement of a 2-hour arrival at the nearest stroke center. In this review, data from a Canadian trial of 554 patients were included. The sensitivity of OPSS was 0.92 (CI 0.88–0.94) and specificity was 0.86 (CI 0.80–0.90). The use of this prehospital scale and the accompanying change in the Ontario stroke network is credited with doubling the rate of thrombolytic therapy (IV recombinant tissue plasminogen activator) administration from 5.9% to 10.1%. The Los Angeles Prehospital Stroke Screen (LAPSS) goes a step further by screening for mimics such as hypoglycemia and seizures. It strives to identify ideal candidates for thrombolytic therapy by assessing the last time they were seen well and their premorbid functional level. It has been validated in multiple populations (United States, Australia, China) of varying ethnic backgrounds. Source data were available for 12,732 patients across 4 studies.
See page 2241 From the University of Miami Miller School of Medicine, FL. Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the editorial. 2154
© 2014 American Academy of Neurology
Its sensitivity and specificity among studies cluster and overlap well. Kidwell et al.7 showed a sensitivity of 0.91 (CI 0.76–0.98) and specificity of 0.97 (CI 0.93–0.99), vs Chen et al.,8 sensitivity 0.78 (CI 0.76– 0.81) and specificity 0.90 (CI 0.84–0.95). The Melbourne Ambulance Stroke Scale (MASS) is a combination of the LAPSS and the CPSS. Source data were available for 950 patients from 2 Melbourne studies. When the MASS and the LAPSS were simultaneously studied in the same population, they had indistinguishable operating characteristics. Therefore the MASS appeared to provide no additional benefit beyond using the LAPSS alone. To answer our question, it appears that prehospital scales performed variably across countries, some with no better odds than that of a coin toss. Furthermore, the LAPSS, which had the best operating characteristic and was the most reliable, still missed 22% of acute stroke patients. This study has limitations. Most of the data were collected retrospectively. The prevalence of stroke in each population varied widely, a substantial problem given that estimates of sensitivity and specificity depend heavily on the prevalence of the condition within the population. This study focuses the research spotlight on this critical first step along the stroke chain of survival and forces us, as a community, to ask ourselves: is it time for a national prehospital EMS stroke registry to track our performance better? Whether we use an existing prehospital system of stroke recognition or implement new models such as the Mobile Stroke Unit9 recently launched in Houston,10 this critical first step should not be left to chance. STUDY FUNDING No targeted funding reported.
DISCLOSURE The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.
REFERENCES 1. Saver JL. Time is brain: quantified. Stroke 2006;37:263–266. 2. Saver JL, Fonarow GC, Smith EE, et al. Time to treatment with intravenous tissue plasminogen activator and outcome from acute ischemic stroke. JAMA 2013;309:2480–2488. 3. Fassbender K, Balucani C, Walters S, Levine SR, Haass A, Grotta J. Streamlining of prehospital stroke management: the golden hour. Lancet Neurol 2013;12:585–596. 4. Schwamm L, Fayad P, Sacco RL, et al. Translating evidence into practice: a decade of efforts by the American Heart Association/American Stroke Association to reduce death and disability due to stroke: a presidential advisory form the American Heart Association/American Stroke Association. Stroke 2010;41:1051–1065. 5. Saver JL, Kidwell C, Eckstein M, Starkman S; for the FAST-MAG pilot trial investigators. Pre hospital neuroprotective therapy for acute stroke results of the Field Administration of Stroke Therapy-Magnesium (FASTMAG) pilot trial. Stroke 2004;35:e106–e108. 6. Brandler ES, Sharma M, Sinert RH, Levine SR. Prehospital stroke scales in urban environments: a systematic review. Neurology 2014;82:2241–2249. 7. Kidwell CS, Starkman S, Eckstein M, Weems K, Saver JL. Identifying stroke in the field: prospective validation of the Los Angeles Prehospital Stroke Screen (LAPSS). Stroke 2000;31:71–76. 8. Chen S, Sun H, Lei Y, et al. Validation of the Los Angeles Prehospital Stroke Screen (LAPSS) in a Chinese urban emergency medical service population. PLoS One 2013;8:e70742. 9. Walter S, Kostopoulos P, Haass A, et al. Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial. Lancet Neurol 2012;11:397–404. 10. Mann Lake D. UTHealth introduces the nation’s first mobile stroke unit: ambulance equipped with scanner to be part of EMS services for Houston area. Available at: https://www.uth.edu/media/story.htm?id=b1485cfc-110f4a4c-91ea-06b573b3ba6d. Published February 3, 2014. Accessed May 10, 2014.
Neurology 82
June 17, 2014
2155
Are prehospital stroke scales better than a coin toss at predicting acute stroke? Gillian Gordon-Perue and Tatjana Rundek Neurology 2014;82;2154-2155 Published Online before print May 21, 2014 DOI 10.1212/WNL.0000000000000531 This information is current as of May 21, 2014 Updated Information & Services
including high resolution figures, can be found at: http://www.neurology.org/content/82/24/2154.full.html
References
This article cites 9 articles, 4 of which you can access for free at: http://www.neurology.org/content/82/24/2154.full.html##ref-list-1
Permissions & Licensing
Information about reproducing this article in parts (figures,tables) or in its entirety can be found online at: http://www.neurology.org/misc/about.xhtml#permissions
Reprints
Information about ordering reprints can be found online: http://www.neurology.org/misc/addir.xhtml#reprintsus
Neurology ® is the official journal of the American Academy of Neurology. Published continuously since 1951, it is now a weekly with 48 issues per year. Copyright © 2014 American Academy of Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.
