New Prehospital Score to Classify Stroke Subtypes

August 10, 2018

A new set of clinical prediction rules to help paramedics classify patients with suspected stroke into different stroke subtypes in the prehospital setting has shown a high degree of accuracy in a new Japanese study.

The researchers developed a new score, known as the Japan Urgent Stroke Triage (JUST) score, based on 21 variables. This analysis showed the score could discriminate between different types of stroke, including large-vessel occlusion (LVO), intracranial hemorrhage (ICH), and subarachnoid hemorrhage (SAH).

"Differences across the types of stroke directly influence the differences in the respective treatment approaches," point out the authors, led by Kazutaka Uchida, MD, Hyogo College of Medicine, Japan. The urgency for invasive treatment also differs across stroke types.

"Our clinical prediction rule is the first tool to simultaneously classify these different types of stroke at the prehospital stage, helping to transfer the patients suspected to have stroke to the appropriate hospitals," they conclude. "Applying these rules to daily clinical practice should help more patients with acute stroke receive appropriate interventions, such as EVT [endovascular therapy], tPA [tissue plasminogen activator], and surgeries, just on time. Such a system would undoubtedly save the lives and decrease the disability of patients with acute stroke."

Commenting on the study for Medscape Medical News, Mitchell Elkind, MD, professor of neurology and epidemiology at Columbia University, New York City, said, "This carefully conducted and interesting study from Japanese investigators shows that emergency medical technicians can predict with good accuracy the likelihood of different stroke diagnoses, including hemorrhage types and large vessel occlusions."

"Being able to predict the stroke subtype immediately on arrival to the hospital is potentially very important, as appropriate services and specialists can then be engaged," Elkind said. "It is important to remember, though, that all these patients will still need to get brain imaging as soon as they arrive since even the best prediction tool cannot distinguish these stroke types with 100% accuracy."  

He cautioned that the study has some limitations. "The large number of items required for the prediction will take some time, and Japanese patients may differ from US patients in terms of the proportion with hemorrhages as opposed to ischemic strokes."

The study is published in the August issue of Stroke.  

For the study, the researchers evaluated 29 predetermined potentially predictive variables for patients with suspected stroke that could be recorded by paramedics, including information on demographics and risk factors, medical history, medication, and symptoms and signs of stroke.  

On arrival at the hospital, the diagnosis was confirmed by neurologists or neurosurgeons with relevant imaging. 

The association between each of the 29 variables and the final diagnosis results was studied in a derivation cohort of 1229 patients with suspected stroke. Of these, 533 patients were confirmed to have stroke, including 104 LVOs, 169 ICHs, and 57 SAHs.

Multivariate logistic regression models showed 21 variables to be independently associated with any stroke, LVO, ICH, or SAH.

Headache was significantly associated with presence of SAH but with the absence of LVO. Similarly, arrhythmia was significantly associated with the presence of LVO but the absence of ICH.

A final risk score was calculated for each patient by assigning points for each variable present and summing them.

These scores were then applied to a validation cohort, and the calculated risk score for each patient was compared with the actual outcomes.

The validation cohort consisted of 1007 patients, of whom 617 patients were confirmed as having stroke, including 131 with LVO, 183 with ICH, and 50 with SAH.

When applying the clinical prediction rules obtained from the derivation cohort to the validation cohort, the area under the curve in the receiver-operating characteristic analyses were 0.80 for any stroke, 0.85 for LVO, 0.77 for ICH, and 0.94 for SAH. The authors say these results show higher discriminative ability compared with other prediction rules.

"The probabilities of the 4 outcomes, according to the categorized risk scores, showed excellent stratification for patients with different types of stroke, ranging from low probability to high probability," the researchers write. "For example, when score for LVO was ≥8, the positive predictive value was 79%.... However, when score for SAH was ≤−3, the negative predictive value was 100%."

They note that the biggest drawback of these new clinical prediction rules is the need for 21 variables to be assessed at the prehospital stage, but they point out that in the validation part of this study, it took a median time of just 37 seconds to input the 21 variables when the paramedics used the application on tablet devices.

"Most paramedics, in developed countries, nowadays use tablet devices to search for the receiving hospitals or record the status of patients," they write. "With the help of our clinical prediction rules, if the paramedics suspect the patients to have acute stroke with neurological symptoms, they can easily estimate the probability of each type of stroke and transfer the patient to an appropriate hospital without unnecessary delay."

While they acknowledge that these clinical prediction rules were developed in Japan and are consequently, of uncertain generalizability, they emphasize that "the variables used are common findings clinically associated with the pathology of all types of stroke and generally considered as relevant risk factors."

This study was supported by the Grant-in-Aid for Graduate Students, Hyogo College of Medicine.

Stroke. 2018;49:1820-1827. Full text 

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