Paramedic identification of stroke mimic presentations : development and preliminary evaluation of a pre-hospital clinical assessment tool

PhD ThesisBackground Stroke mimic (SM) conditions produce stroke-like symptoms through diverse mechanisms. Up to 43% of pre-hospital suspected stroke patients are SM because identification tools prioritise sensitivity over specificity, leading to inefficient use of ambulances and stroke services. No existing pre-hospital SM identification tools could be identified. A pragmatic SM identification tool using easily available information from suspected stroke patients was developed. Methods A systematic literature review and a national paramedic survey generated possible tool content. Independent predictors were isolated by regression analysis of selected variables documented in ambulance records of suspected stroke patients linked to primary hospital diagnoses (derivation dataset, n=1,650, 40% SM). The tool was refined using an expanded dataset (n=3,797, 41% SM), usability testing and professional focus groups. The potential clinical impact was evaluated through basic service efficiency modelling and focus groups. Results The “STEAM tool” combines six variables: 1 point for Systolic blood pressure<90mmHg 1 point for Temperature>38.5oC with heart rate>90bpm 1 point for seizures or 2 points for seizures with known diagnosis of Epilepsy 1 point for Age<40 years or 2 points for age<30 years 1 point for headache with known diagnosis of Migraine 1 point for FAST-ve suspected stroke A score of ≥2 on STEAM predicted SM diagnosis in the refinement dataset with 5.5% sensitivity, 99.6% specificity and positive predictive value (PPV) of 91.4%. External validation (n=1,848, 33% SM) showed 5.6% sensitivity, 99.5% specificity and a PPV of 85.0%. Focus groups with paramedics and hospital clinicians identified benefits and risks to patients ii and clinical services from using STEAM. Conclusions A multi-method approach developed and validated a tool using common clinical characteristics to identify a small proportion of SM patients with a high degree of certainty. The tool appears feasible for pre-hospital use but its impact will depend upon local models of stroke care.The Stroke Associatio

The positive predictive value of stroke identification by ambulance clinicians in North East England: a retrospective cohort study

Introduction/background Accurate prehospital identification of patients who had an acute stroke enables rapid conveyance to specialist units for time-dependent treatments such as thrombolysis and thrombectomy. Misidentification leads to patients who had a ‘stroke mimic’ (SM) being inappropriately triaged to specialist units. We evaluated the positive predictive value (PPV) of prehospital stroke identification by ambulance clinicians in the North East of England. Methods This service evaluation linked routinely collected records from a UK regional ambulance service identifying adults with any clinical impression of suspected stroke to diagnostic data from four National Health Service hospital trusts between 1 June 2013 and 31 May 2016. The reference standard for a confirmed stroke diagnosis was inclusion in Sentinel Stroke National Audit Programme data or a hospital diagnosis of stroke or transient ischaemic attack in Hospital Episode Statistics. PPV was calculated as a measure of diagnostic accuracy. Results Ambulance clinicians in North East England identified 5645 patients who had a suspected stroke (mean age 73.2 years, 48% male). At least one Face Arm Speech Test (FAST) symptom was documented for 93% of patients who had a suspected stroke but a positive FAST was only documented for 51%. Stroke, or transient ischaemic attack, was the final diagnosis for 3483 (62%) patients. SM (false positives) accounted for 38% of suspected strokes identified by ambulance clinicians and included a wide range of non-stroke diagnoses including infections, seizures and migraine. Discussion In this large multisite data set, identification of patients who had a stroke by ambulance clinicians had a PPV rate of 62% (95% CI 61 to 63). Most patients who had a suspected stroke had at least one FAST symptom, but failure to document a complete test was common. Training for stroke identification and SM rates need to be considered when planning service provision and capacity. http://dx.doi.org/10.1136/emermed-2019-208902. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0

A survey of UK paramedics’ views about their stroke training, current practice and the identification of stroke mimics

Aims ‐ Paramedics play a crucial role in identifying patients with suspected stroke and transporting them to appropriate acute care. Between 25% and 50% of suspected stroke patients are later diagnosed with a condition other than stroke known as a ‘stroke mimic’. If stroke mimics could be identified in the pre-hospital setting, unnecessary admissions to stroke units could potentially be avoided. This survey describes UK paramedics’ stroke training and practice, their knowledge about stroke mimic conditions and their thoughts about pre-hospital identification of these patients.Methods ‐ An online survey invitation was circulated to members within the UK College of Paramedics and promoted through social media (8 September 2016 and 23 October 2016). Topics included: stroke training; assessment of patients with suspected stroke; local practice; and knowledge about and identification of stroke mimics.Results ‐ There were 271 responses. Blank responses (39) and non-paramedic (1) responses were removed, leaving 231 responses from paramedics which equates to 2% of College of Paramedics membership and 1% of Health and Care Professions Council registered paramedics. The majority of respondents (78%) thought that they would benefit from more training on pre-hospital stroke care. Narrative comments focused on a desire to improve the assessment of suspected stroke patients and increase respondents’ knowledge about atypical stroke presentations and current stroke research. The Face Arm Speech Test was used by 97% of respondents to assess suspected stroke patients, although other tools such as Recognition of Stroke in the Emergency Room (17%) and Miami Emergency Neurological Deficit (11%) were also used. According to those responding, 50% of stroke patients were taken to emergency departments, 35% went straight to a stroke ward and 8% were taken directly to CT scan. Most respondents (65%) were aware of the term ‘stroke mimic’. Two-thirds of respondents (65%) thought a tool that predicted the likelihood of a suspected stroke being a stroke mimic would be useful in pre-hospital care.Conclusion ‐ This study reports a survey of UK paramedics’ views about the stroke care they provide. Conclusions are limited by the low number of responses. Assessment of suspected stroke patients was recognised as an important skill by paramedics and an area where many would like further training. Respondents’ current practice varied in terms of the stroke assessment tools used and whether suspected stroke patients were taken to the emergency department or direct to a stroke ward. A stroke mimic identification tool would be useful if it allowed stroke mimic patients to be directed to appropriate care, but it would need to have a high level of specificity and not adversely impact on time to treatment for true stroke patients

The frequency, characteristics and aetiology of stroke mimic presentations::a narrative review

A significant proportion of patients with acute stroke symptoms have an alternative ‘mimic’ diagnosis. A narrative review was carried out to explore the frequency, characteristics and aetiology of stroke mimics. Prehospital and thrombolysis-treated patients were described separately. Overall, 9972 studies were identified from the initial search and 79 studies were included with a median stroke mimic rate of 19% (range: 1–64%). The prehospital median was 27% (range: 4–43%) and the thrombolysis median 10% (range: 1–25%). Seizures, migraines and psychiatric disorders are the most frequently reported causes of stroke mimics. Several characteristics are consistently associated with stroke mimics; however, they do not fully exclude the possibility of stroke. Nineteen per cent of suspected stroke patients had a mimic condition. Stroke mimics were more common with younger age and female sex. The range of mimic diagnoses, a lack of clear differentiating characteristics and the short treatment window for ischaemic stroke create challenges for early identification

Development and validation of a pragmatic prehospital tool to identify stroke mimic patients

Aim Stroke mimics (SM) are non-stroke conditions producing stroke-like symptoms. Prehospital stroke identification tools prioritise sensitivity over specificity.1 It is estimated that >25% of prehospital suspected stroke patients are SM.2 Failure to identify SM creates inefficient use of ambulances and specialist stroke services. We developed a pragmatic tool to identify SM amongst suspected prehospital stroke patients. Method The tool was developed using regression analysis of clinical variables documented in ambulance records of suspected stroke patients linked to primary hospital diagnoses (derivation dataset, n=1,650, 40% SM).3 It was refined using feedback from paramedics (n=3) and hospital clinicians (n=9), and analysis of an expanded prehospital derivation dataset (n=3,797, 41% SM (original 1650 patients included)). Results The STEAM tool combines six variables: 1 point for Systolic blood pressure 38.5°C with Abstracts A2 BMJ Open 2018;8(Suppl 1):A1–A34 (NHS). Protected by copyright. on 14 August 2019 at Manchester University NHS Foundation Trust http://bmjopen.bmj.com/ BMJ Open: first published as 10.1136/bmjopen-2018-EMS.6 on 16 April 2018. Downloaded from heart rate >90 bpm; 1 point for seizures or 2 points for seizures with known diagnosis of Epilepsy; 1 point for Age <40 years or 2 points for age <30 years; 1 point for headache with known diagnosis of Migraine; 1 point for FAST-ve. A score of 2 on STEAM predicted SM diagnosis in the derivation dataset with 5.5% sensitivity, 99.6% specificity and positive predictive value (PPV) of 91.4%. External validation (n=1,848, 33% SM) showed 5.5% sensitivity, 99.4% specificity and a PPV of 82.5%. Conclusion STEAM uses common clinical characteristics to identify SM patients with high certainty. The benefits of using STEAM to reduce SM admissions to stroke services need to be weighed up against delayed admissions for stroke patients wrongly identified as SM. https://bmjopen.bmj.com/content/8/Suppl_1/A2.3 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ http://dx.doi.org/10.1136/bmjopen-2018-EMS.

Human μ-calpain: Simple isolation from erythrocytes and characterization of autolysis fragments

Heterodimeric μ-calpain, consisting of the large (80 kDa) and the small (30 kDa) subunit, was isolated and purified from human erythrocytes by a highly reproducible four-step purification procedure. Obtained material is more than 95% pure and has a specific activity of 6 - 7 mU/mg. Presence of contaminating proteins could not be detected by HPLC and sequence analysis. During storage at -80 °C the enzyme remains fully activatable by Ca²⁺, although the small subunit is partially processed to a 22 kDa fragment. This novel autolysis product of the small subunit starts with the sequence (60)RILG and is further processed to the known 18 kDa fragment. Active forms and typical transient and stable autolysis products of the large subunit were identified by protein sequencing. In casein-zymograms only the activatable forms 80 kDa+30 kDa, 80 kDa+22 kDa and 80 kDa+18 kDa displayed caseinolysis