Dallas 2015

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

First Aid 801: Stroke Recognition

Dallas 2015COI Disclosure(specific to this systematic review)

Dallas 20152010 CoSTR

Topic Not Reviewed in 2010

Dallas 2015C2015 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-ImportantSurvival with favorable neurologic outcome 3-Low

Dallas 2015Inclusion/Exclusion& Articles Found

InclusionsHuman studiesInclude/describe stroke screening tool/scale including the tool/scale usable by EMT.

ExclusionsAnimal studies

Number of Articles initially identified: 1446 Number Included: 26

RCTs: 0non-RCTs: 26

Update 2015-02-01

Dallas 20152015 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).  

Dallas 2015 Risk of Bias: Diagnosis

Figure 1 : Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study

Figure 2 : Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies

Dallas 2015 Risk of Bias: Interventional

Dallas 2015Stroke 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

Dallas 2015

Evidence profile table:STROKE RECOGNITION

FASTFAST

KPSSKPSS

Dallas 2015

Evidence profile table:STROKE RECOGNITION

FASTERFASTER

CPSSCPSS

Dallas 2015Forest plot of tests: FAST, CPSS, LAPSS

Dallas 2015

Forest plot of tests: MASS, ROSIER, MDPS, OPSST. 

Dallas 2015

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

 

Dallas 2015

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 No data in diagnostic study ROSIER 0.88 (0.86 – 0.90) 0.52 (0.48 – 0.55) 1 756 (5) Moderate

Pooled 0.84 (0.82 – 0.85) 0.97 (0.97 – 0.97) 16 506 Low

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) Low

CPSS 0.80 (0.79 – 0.80) 0.42 (0.41 – 0.44) 8 762 (9) Very low

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 Low

Scales with Glucose Measurement

Scales without Glucose Measurement

Dallas 2015Evidence profile table:TIME TO TX, COG. KNOWLEDGE

Knowledge on 911 call after education by animation on stroke symptom and FAST compared to no education Knowledge on 911 call after education by animation on stroke symptom and FAST compared to no education

Dallas 2015Evidence 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 Knowledge on FAST symptoms retention after education by animation on stroke symptom and FAST compared to no education

Dallas 2015Proposed 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). 

Dallas 2015Proposed 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). 

Dallas 2015Proposed 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).  

Dallas 2015Proposed 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).

Dallas 2015Draft 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).

Dallas 2015Knowledge 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).

Dallas 2015

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)

Dallas 2015Next Steps

This slide will be completed during Task Force Discussion (not EvRev) and should include:

Consideration of interim statementPerson responsibleDue date

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