First Aid 801: Stroke Recognition TFQO: Jan Jensen COI #115 EVREVs: Pascal Cassan COI #40; Daniel Meyran COI#161 ; Jeffrey Ferguson COI #81 Taskforce: First Aid

COI Disclosure (specific to this systematic review) Jan Jensen COI #115 Commercial/industry No conflicts Potential intellectual conflicts Daniel Meyran COI #161 Jeffrey Ferguson #81 Pascal Cassan COI #40

2010 CoSTR Topic Not Reviewed in 2010

C2015 PICO Population: Adults with suspected acute stroke Intervention: Use of a rapid stroke scoring system or scale Comparison: Standard first aid assessment Outcomes: Time to treatment (e.g. door to balloon) 9-Critical Cognitive knowledge 5-Important Discharge with favorable neurologic status 5-Important Recognition of acute injury or illness 5-Important Survival with favorable neurologic outcome 3-Low

Inclusion/Exclusion & Articles Found Inclusions Human studies Include/describe stroke screening tool/scale including the tool/scale usable by EMT. Exclusions Animal studies Number of Articles initially identified: 1446 Number Included: 26 RCTs: 0 non-RCTs: 26 1349 citations retrieved. After reading title and abstract and full text if it is necessary, we selected 18 articles. In a secondary hand-search, we add 6 new articles (4 of them require glucose measure – we included them after the last webex conference too enlarge the topics to EMT and other FA volunteers actors) In a tertiary hand-search we add 2 new articles (from 2014 period) 26 articles included No RCTs, only observational study. Update 2015-02-01

2015 Proposed Treatment Recommendations We recommend stroke screening tools should be used to assess patients with suspected acute stroke (strong recommendation  - low quality of evidence). We suggest the use of a glucometer to increase sensitivity and specificity of screening tools such as with LAPSS, OPSS, ROSIER, KPSS (weak recommendation - low quality of evidence). In the absence of a glucometer we suggest the use of FAST or CPSS screening tools compared to MASS, LAMS, or MDPS (weak recommendation - low quality of evidence).  

Risk of Bias: Diagnosis Figure 2 : Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies 1. Patient selection Risk of bias Most of the study use patients suspected of stroke or transient ischemic attack (TIA) with, age > 18 y transfer to hospital. Most of them excluded unconscious patients and seizures or asymptomatic patients. Nazliel 2008 limited to last known well time within 12 hours of initial ED examination and Final diagnosis of acute ischemic stroke in the anterior circulation. Yock_Corrales 2011 limited the population to children aged 1 month to less 18y, radiologically confirmed acute AIS who presented to a tertiary ED. - Applicability concerns The included patients and setting not match the review question. 2. Index test - Risk of bias The stroke scales or test find in article are : FAST, CPSS, LAPSS, MASS, ROSIER (for physician), MDPS (for EM dispatcher), MASS. Most of them concern lay people or EMT but ROSIER and MDPS concern physician and EM dispatcher. We can say that the risk of bias is low. The index test, its conduct, or interpretation does not differs from the PICO question. 3. Reference standard All of the article use as gold standard diagnostic "Stroke diagnosis at discharge". This diagnosis is making by physician after imaging when it's necessary (SCT, MIR). Nazliel 2008 limited to large vessel occlusion after intracranial vascular imaging. 4. Flow and timing Fothergill 2013 limited the flow time for diagnosis at only 72 hours and not at hospital discharge. All the other articles limited the flow timing to the hospitalisation duration. Sometime the flow and timing are not precise. We could say that the patient flow has not introduced bias and the risk of bias is low. Figure 1 : Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study

Risk of Bias: Interventional Study Year Design Total Patients Population Industry Funding Eligibility Criteria Exposure/ Outcome Confounding Follow-Up Bergs 2010 Observational; prospective 70 EMS pts with neuro complaints low unclear Bray 2005 100 Observational; retrospective 1004 Buck 2009 3474 EMS callers - pts with neuro complaints Chen 2013 1550 Chenkin 325 DeLuca 18231 high Fothergill 312 Frendl Observational; prospective - before & after 154 Harbison 2003 487 acute stroke patients presenting to EMS, EDs or GPs Iguchi 430 Kidwell 2000 206 Kleindorfer 2007   Kothari 1999 171 ED pts with neuro complaints Nazliel 2008 Observational; retrospective - case series 119 acute stroke pts Nor 343 Obrien 2012 115 Ramanujam 882 Studnek 416 Wall 2008 Public Whiteley 2014 356 Wojner 446 Yock-C. 2011 47 pediatrics You acute stroke pts in ED - test used by EMTs Confounding possible: The time interval calculated by each study is not the same. We found 5 different time intervals: In general, studies with small sample sizes had higher stroke prevalence, suggesting a selection bias in these studies that would inappropriately inflate diagnostic accuracy. Since all studies included TIA as a stroke diagnosis, physical examination findings present in the pre-hospital environment may have disappeared by the time the patient was examined by the physician making the discharge diagnosis of stroke. As such, stroke scales performed by pre-hospital providers may influence the ultimate diagnosis of a TIA in the hospital. Prehospital stroke scales thus have the potential to introduce bias because the reference standard (discharge diagnosis) is not independent of the index test (stroke scale). This bias is clearly unavoidable. However, the pre-hospital tests were conducted without knowledge of the ultimate discharge diagnosis.

Stroke Scales Studied FAST Face, Arm, Speech Test Bergs, Fothergill, Harbison, Whiteley, Yock-Corrales FASTER Face, Arm, Speech Time, Emergency Response Protocol O’Brien LAPSS*,** LA Prehospital Stroke Scale Bergs, Bray (2005, 2010), Chen, Kidwell, Wojner, Asimos OPSS*, ** Ontario Prehospital Stroke Scale Chenkin CPSS Cincinnati Prehospital Stroke Scale Bergs, Bray 2010, Studnek, Asimos KPSS* Kurashiki Prehospital Stroke Scale Iguchi ROSIER*,** Recognition of Stroke in the Emergency Room Fothergill, Nor, Whiteley, Yock-Corrales, Jiang LAMS Los Angeles Motor Scale Nazliel MPDS Medical Priority Dispatch System Buck, Ramanujam MASS** Melbourne Ambulance Stroke Screen Bergs, Bray (2010) MedPACS* Medic Prehospital Assessment for Code Stroke Studnek * Requires GCS: OPSS ROSIER KPSS LAPSS Requires understanding of high acuity: ** Requires history (seizure/epilepsy): MASS

Evidence profile table: STROKE RECOGNITION FAST KPSS Recognition of stroke – y/n compared to stroke diagnosis in hospital or tPA administration

Evidence profile table: STROKE RECOGNITION FASTER CPSS Recognition of stroke – y/n compared to stroke diagnosis in hospital or tPA administration

Forest plot of tests: FAST, CPSS, LAPSS Diagnostic accuracy of the different stroke scales: For the FAST scale, the sensitivity varied from 77% to 95% and the specificity from 13% to 39%. Prevalance from 60% to 73%. The positive predictive value from 62 to 77% and the negative predictive value from 37% to 80%. For the CPSS scale, the sensitivity varied from 44% to 95% and the specificity from 13% to 39%. Prevalance from 50% to 88%. The positive predictive value from 40% to 85% and the negative predictive value from 56% to 98%. For the LAPSS scale, the sensitivity varied from 74% to 91% and the specificity from 83% to 100%. Prevalance from 2% to 88%. The positive predictive value from 64% to 98% and the negative predictive value from 35% to 99%.

Forest plot of tests: MASS, ROSIER, MDPS, OPSST.   For the MASS scale, the sensitivity varied from 78% to 90% and the specificity from 67% to 74%. Prevalance from 60% to 73%. The positive predictive value from 77% to 90% and the negative predictive value from 74% to 66%. For the ROSIER scale (ROSIER scale is more for physician than for lay people or EMT). For the MDP scale, the sensitivity varied from 41% to 83% and the specificity from 15% to 96%. Prevalance from 42% to 73%. The positive predictive value from 41% to 44% and the negative predictive value from 55% to 95%. For the OPSST scale (ROSIER scale is more for EMT than for lay people).

Graphical Comparison of scales Summary ROC Plot of tests: 1 FAST, 2 CPSS, 3 LAPSS, 4 MASS, 6 ROSIER, 8 MDPS, 11 OPSST.  

Number of participants Number of participants Scales with Glucose Measurement Sensitivity (CI 95%) Specificity (CI 95%) Number of participants (number of studies) Quality of evidence LAPSS 0.75 (0.73 – 0.77) 0.96 (0.96 – 0.77) 16 128 (8) Very low OPSS 0.92 (0.88 – 0.86) 0.86 (0.80 – 0.90) 554 (1) Moderate KPSS No data in diagnostic study   ROSIER 0.88 (0.86 – 0.90) 0.52 (0.48 – 0.55) 1 756 (5) Pooled 0.84 (0.82 – 0.85) 0.97 (0.97 – 0.97) 16 506 Low Scales without Glucose Measurement Sensitivity (CI 95%) Specificity (CI 95%) Number of participants (number of studies) Quality of evidence FAST 0.84 (0.81 – 0.87) 0.28 (0.23 – 0.33) 927 (4) Low MASS 0.88 (0.79 – 0.94) 0.72 (0.55 – 0.85) 130 (2) Very low LAMS 0.81 (0.70 – 0.89) 0.89 (0.76 – 0.96) 119 (1) CPSS 0.80 (0.79 – 0.80) 0.42 (0.41 – 0.44) 8 762 (9) MDPS 0.78 (0.74 – 0.82) 0.61 (0.59 – 0.64) 1 916 (2) Moderate Pooled 0.82 (0.81 – 0.83) 0.48 (0.46 – 0.49) 11 637 * Requires GCS: OPSS ROSIER KPSS LAPSS Requires understanding of high acuity: ** Requires history (seizure/epilepsy): MASS

Evidence profile table: TIME TO TX, COG. KNOWLEDGE Knowledge on 911 call after education by animation on stroke symptom and FAST compared to no education 9-Critical : time to treatment The time interval calculated by each study are not the same. We found 5 different time intervals: * Door to balloon = 1 article; O’Brien 2012 Onset to door = 3 articles Chenkin 2009, Wojner-Alexandrov 2005, You 2013, Onset to admission = 2 articles: harbison 2003, Iguchi 2010 (both proportion of patinets within time categories, such as under 3 hours) * Onset to treat = 1 article; O’Brien 2012 * Door to stroke unit = 1 article ; O’Brien 2012 * on scene time = 1 article ; Frendl 2009 Here – pooled ‘Sx Onset to Arrival ED’ times from 4 studies. 2 didn’t have variance and one didn’t have comparison group. Unsure if they should be pooled? 5-Important : cognitive knowledge = 1 article : Wall 2008 In addition: 3-months after 100% remembered slurred speech and facial drooping as symptoms; 98.5% (64/65) recalled arm weakness or numbness.

Evidence profile table: TIME TO TX, COG. KNOWLEDGE Knowledge on FAST symptoms retention after education by animation on stroke symptom and FAST compared to no education 9-Critical : time to treatment The time interval calculated by each study are not the same. We found 5 different time intervals: * Door to balloon = 1 article; O’Brien 2012 Onset to door = 3 articles Chenkin 2009, Wojner-Alexandrov 2005, You 2013, Onset to admission = 2 articles: harbison 2003, Iguchi 2010 (both proportion of patinets within time categories, such as under 3 hours) * Onset to treat = 1 article; O’Brien 2012 * Door to stroke unit = 1 article ; O’Brien 2012 * on scene time = 1 article ; Frendl 2009 Here – pooled ‘Sx Onset to Arrival ED’ times from 4 studies. 2 didn’t have variance and one didn’t have comparison group. Unsure if they should be pooled? 5-Important : cognitive knowledge = 1 article : Wall 2008 In addition: 3-months after 100% remembered slurred speech and facial drooping as symptoms; 98.5% (64/65) recalled arm weakness or numbness.

Proposed Consensus on Science statements For the critical outcome of “time to treatment” we identified six studies (Chenkin 2009, 153; Frendl 2009, 754; Harbison 2003, 71; Iguchi 2010, 51; O’Brien 2012, 241; Wojner-Alexandrov 2005, 1512) with six different stroke scales studied. For the Face, Arm, Speech, Test (FAST) Scale (measured as number of patients with time from symptom onset to hospital arrival within 3h), we have identified moderate quality evidence from one observational study enrolling 356 patients (Harbison 2003, 71) showing benefit where 48.2% patients who had the scale applied arrived within three hours compared to 14.6% who did not have the scale applied (RR 3.3 (95%CI 2.29 – 4.75). For the Kurashiki Prehospital Stroke Scale (KPSS) (measured as number of patients with time from symptom onset to hospital arrival within 3h), we have identified very low quality evidence from one observational study enrolling 430 patients (Iguchi 2010, 51) (evidence downgraded due to risk of bias), showing benefit where 62.9% patients who had the scale applied arrived within three hours compared to 52.3% who did not have the scale applied (RR 1.2 (95%CI 1.01 – 1.43). In the same study, the mean time was 2.1 hours for those who had a stroke screening tool applied compared to 2.7 hours  for those who did not have a stroke screening tool applied (MD -0.6, 95%CI -2.45 – 1.25). 

Proposed Consensus on Science statements For the Ontario Prehospital Stroke Scale (OPSS) (measured as number of patients with time from symptom onset to hospital arrival within 3h), we have identified very low quality evidence from one observational study enrolling 861 patients (Chenkin 2009, 153) (evidence downgraded due to risk of bias), showing equal benefit where 52.3% patients who had the scale applied arrived within three hours compared to 47.2% who did not have the scale applied (RR 1.1 (95%CI 0.96 – 1.28). For the Los Angeles Prehospital Stroke Scale (LAPSS) (measured with symptom onset to emergency department arrival time), we have identified low quality evidence from one observational study enrolling 1027 patients (Wojner-Alexandrov 2005, 1512), the mean time was 356 minutes for those who had a stroke screening tool applied compared to 359 minutes  for those who did not have a stroke screening tool applied (MD -1.00 95%CI 115.19 -113.19) and the mean time was 180 minutes for those who had a stroke screening tool applied compared to 214 minutes for those who did not have a stroke screening tool applied (MD 6.37 95%CI 2.3 -10.4) if we excluded the patients arrived at ED after 24h of symptoms.  For the Cincinatti prehospital stroke scales (CPSS) (measured with symptom onset to door emergency department arrival time), we have identified low quality evidence from one observational study enrolling 284 patients (You 2013, 284), the mean time was 75.5 minutes for those who had a stroke screening tool applied compared to 127 minutes  for those who did not have a stroke screening tool applied (p = 0.0001). For the Face, Arm, Speech Time, Emergency Response Protocol (FASTER (measured with symptom onset to door time), we have identified low quality evidence from one observational study enrolling 115 patients (O’Brien 2012, 241) (evidence downgraded due to risk of bias) showing equal benefit where the mean time was 59 minutes for those who had a stroke screening tool applied compared to 76 minutes for those who did not have a stroke screening tool applied (p=0.180). 

Proposed Consensus on Science statements For the important outcome of “recognition of stroke” (diagnostic studies, outcome defined as correct stroke diagnosis), we identified low quality evidence from 22 observational studies enrolling 30,635 patients studying 8 different screening tools (Bergs 2010, 2; Bray 2005, 28; Bray 2010, 1363; Buck 2009, 2027; Chen 2013, e70742; Chenkin 2009, 153; DeLuca 2013, 513; Fothergill, 3007; Frendl 2009, 754; Harbison 2003, 71; Kidwell 2000, 71; Kleindorfer 2007, 2864; Kothari 1999, 373; Nazliel 2008, 2264; Nor 2005, 727; Ramanujam 2008, 307; Studnek 2013, 348; Whiteley 2014, 1006; Wojner-Alexandrov 2005, 1512; Yock Corrales 2011, 93; Asimos 2014, 1217; Jiang 2014, 715) (all evidence downgraded for risk of bias) showing benefit with diagnostic performance across all stroke screening tools of: sensitivity ranging from 0.41 to 0.97 and specificity ranging from 0.13 to 1.00. These studies were divided into sub-groups if the stroke scales included glucose measurement or not. For studies that included stroke scales with glucose measurement (LAPSS, OPSS, KPSS and Recognition of Stroke in the Emergency Room (ROSIER)), the pooled sensitivity was 0.84 (95%CI 0.82 – 0.85), pooled specificity was 0.97 (0.97 – 0.97) showing benefit compared to stroke scales without glucose measurement (FAST, Melbourne Ambulance Stroke Screen (MASS), Los Angeles Motor Scale (LAMS), CPSS, Medical Priority Dispatch System (MPDS)), which has pooled sensitivity of 0.82 (0.81 – 0.83) and pooled specificity of 0.48 (0.46 – 0.49).  

Proposed Consensus on Science statements For the important outcome of “cognitive knowledge”, very low quality evidence from one human study enrolling 72 participants (members of the public) (Wall 2008, 1) (evidence downgraded due to risk of bias) showing benefit where 76.4% (55/72) participants were able to identify signs of stroke prior to training on a stroke screening tool compared to 94.4% (68/72) immediately after training (OR 5.25, 95% CI 1.67 – 16.52), and 96.9% (63/65) participants were able to identify the signs of stroke 3-months after training (OR 2.07, 95% CI 0.36 – 11.69). Cognitive knowledge (5-Important) = 1 article: Wall 2008

Draft Treatment Recommendations We recommend stroke-screening tools should be used to assess patients with suspected acute stroke (strong recommendation, low quality of evidence). We suggest the use of a glucometer to increase sensitivity and specificity of screening tools such as with LAPSS, OPSS, ROSIER, KPSS (weak recommendation, low quality of evidence). In the absence of a glucometer we suggest the use of FAST or CPSS screening tools compared to MASS, LAMS, or MDPS (weak recommendation, low quality of evidence).

Knowledge Gaps More research is required on how much training is required and what type of training should be used for first aid providers to correctly apply stroke screening tools, particularly without obtaining blood glucose readings, and on accuracy of use of stroke tools by first aid providers compared to health care providers. Research is also required to determine diagnostic accuracy compared to survival and neurological status at discharge. In addition, future research could include investigating direct transport to specified stroke centres when stroke screening tool is positive (bypassing community/small emergency departments).

Public comments We suggest refining or removing the reference to use of glucometers since issues such as accuracy of readings was not addressed in this review and glucometers are medical devices not expected to be used by first aid providers. (First Aid Subcouncil of the American Red Cross Scientific Advisory Council)

Next Steps This slide will be completed during Task Force Discussion (not EvRev) and should include: Consideration of interim statement Person responsible Due date Essential slide (one slide only). Estimated time <30 sec