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- Mattila, O. S., et al.
(författare)
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Targets for improving dispatcher identification of acute stroke
- 2019
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Ingår i: International Journal of Stroke. - : SAGE Publications. - 1747-4930 .- 1747-4949. ; 14:4, s. 409-416
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Tidskriftsartikel (refereegranskat)abstract
- Background: Accurate identification of acute stroke by Emergency Medical Dispatchers (EMD) is essential for timely and purposeful deployment of Emergency Medical Services (EMS), and a prerequisite for operating mobile stroke units. However, precision of EMD stroke recognition is currently modest. Aims: We sought to identify targets for improving dispatcher stroke identification. Methods: Dispatch codes and EMS patient records were cross-linked to investigate factors associated with an incorrect dispatch code in a prospective observational cohort of 625 patients with a final diagnosis of acute stroke or transient ischemic attack (TIA), transported to our stroke center as candidates for recanalization therapies. Call recordings were analyzed in a subgroup that received an incorrect low-priority dispatch code indicating a fall or unknown acute illness (n = 46). Results: Out of 625 acute stroke/TIA patients, 450 received a high-priority stroke dispatch code (sensitivity 72.0%; 95% CI, 68.5-75.5). Independent predictors of dispatcher missed acute stroke included a bystander caller (aOR, 3.72; 1.48-9.34), confusion (aOR, 2.62; 1.59-4.31), fall at onset (aOR, 1.86; 1.24-2.78), and older age (aOR [per year], 1.02; 1.01-1.04). Of the analyzed call recordings, 71.7% revealed targets for improvement, including failure to recognize a Face Arm Speech Time (FAST) test symptom (21/46 cases, 18 with speech disturbance), or failure to thoroughly evaluate symptoms (12/46 cases). Conclusions: Based on our findings, efforts to improve dispatcher stroke identification should primarily focus on improving recognition of acute speech disturbance, and implementing screening of FAST-symptoms in emergency phone calls revealing a fall or confusion.
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| 2. |
- Mattila, O S, et al.
(författare)
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Ultra-acute diagnostics for stroke: Large-scale implementation of prehospital biomarker sampling.
- 2017
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Ingår i: Acta neurologica Scandinavica. - : Hindawi Limited. - 1600-0404 .- 0001-6314. ; 136:1, s. 17-23
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Tidskriftsartikel (refereegranskat)abstract
- Blood-based biomarkers could enable early and cost-effective diagnostics for acute stroke patients in the prehospital setting to support early initiation of treatments. To facilitate development of ultra-acute biomarkers, we set out to implement large-scale prehospital blood sampling and determine feasibility and diagnostic timesavings of this approach.Emergency medical services (EMS) personnel of the Helsinki metropolitan area were trained to collect prehospital blood samples from thrombolysis candidates using a cannula adapter technique. Time delays, sample quality, and logistics were investigated between May 20, 2013 and May 19, 2014.Prehospital blood sampling and study recruiting were successfully performed for 430 thrombolysis candidates, of which 50% had ischemic stroke, 14.4% TIA, 13.5% hemorrhagic stroke, and 22.1% stroke mimics. A total of 66.3% of all samples were collected during non-office hours. The median (interquartile range) emergency call to prehospital sample time was 33minutes (25-41), and the median time from reported symptom onset or wake-up to prehospital sample was 53minutes (38-85; n=394). Prehospital sampling was performed 31minutes (25-42) earlier than hospital admission blood sampling and 37minutes (30-47) earlier than admission neuroimaging. Hemolysis rate in serum and plasma samples was 6.5% and 9.3% for EMS samples, and 0.7% and 1.6% for admission samples.Prehospital biomarker sampling can be implemented in all EMS units and provides a median timesaving of more than 30minutes to first blood sample. Large prehospital sample sets will enable development of novel ambulance biomarkers to improve early differential diagnosis and treatment of thrombolysis candidates.
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| 3. |
- Mattila, O. S., et al.
(författare)
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Ultra-Early Differential Diagnosis of Acute Cerebral Ischemia and Hemorrhagic Stroke by Measuring the Prehospital Release Rate of GFAP
- 2021
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Ingår i: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 67:10, s. 1361-1372
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Plasma glial fibrillary acidic protein (GFAP) and tau are promising markers for differentiating acute cerebral ischemia (ACI) and hemorrhagic stroke (HS), but their prehospital dynamics and usefulness are unknown. METHODS: We performed ultra-sensitivite single-molecule array (Simoa((R))) measurements of plasma GFAP and total tau in a stroke code patient cohort with cardinal stroke symptoms [National Institutes of Health Stroke Scale (NIHSS) >= 3]. Sequential sampling included 2 ultra-early samples, and a follow-up sample on the next morning. RESULTS: We included 272 cases (203 ACI, 60 HS, and 9 stroke mimics). Median (IQR) last-known-well to sampling time was 53 (35-90) minutes for initial prehospital samples, 90 (67-130) minutes for secondary acute samples, and 21 (16-24) hours for next morning samples. Plasma GFAP was significantly higher in patients with HS than ACI (P<0.001 for <1hour and <3hour prehospital samples, and <3hour secondary samples), while total tau showed no intergroup difference. The prehospital GFAP release rate (pg/mL/minute) occurring between the 2 very early samples was significantly higher in patients with HS than ACI [2.4 (0.6-14.1)] versus 0.3 (-0.3-0.9)pg/mL/minute, P<0.001. For cases with <3hour prehospital sampling (ACI n=178, HS n=59), a combined rule (prehospital GFAP >410pg/mL, or prehospital GFAP 90-410pg/mL together with GFAP release >0.6pg/mL/minute) enabled ruling out HS with high certainty (NPV 98.4%) in 68% of patients with ACI (sensitivity for HS 96.6%, specificity 68%, PPV 50%). CONCLUSIONS: In comparison to single-point measurement, monitoring the prehospital GFAP release rate improves ultra-early differentiation of stroke subtypes. With serial measurement GFAP has potential to improve future prehospital stroke diagnostics.
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