Prehospital Stroke Screening Showdown Crowns Two Tools

Two prehospital prediction scales were better than others at identifying stroke patients who might be candidates for mechanical thrombectomy in the Netherlands, though results might vary in other countries and regions.

The most accurate large vessel occlusion (LVO) prediction scales were the Los Angeles Motor Scale (LAMS) and Rapid Arterial Occlusion Evaluation (RACE) tool, with estimated accuracy rates of 89% and 88%, respectively, according to Nyika Kruyt, PhD, of Leiden University Medical Center, the Netherlands, and colleagues reporting online in JAMA Neurology.

These two scales significantly outperformed other prediction scales tested:

• Cincinnati Stroke Triage Assessment Tool (C-STAT)
• Prehospital Acute Stroke Severity (PASS)
• Gaze-face-arm-speech-time (G-FAST)
• Field Assessment Stroke Triage for Emergency Destination (FAST-ED)
• Gaze, facial asymmetry, level of consciousness, extinction/inattention (GACE)

For the study, paramedics filled in a page of 10 to 13 neurologic observations on-site or during transport of each stroke code patient in the Leiden and The Hague regions. Investigators then retrospectively reconstructed and tested seven LVO prediction scales from this data on 2,007 adults with suspected stroke.

Prevalence of symptomatic, anterior circulation LVO [sLAVO] was 7.9% in this cohort.

“In practice, the preferred sLAVO prediction scale will depend on the local context, which will include such factors as prevalence of sLAVO, differences in transport times between hospitals, in-hospital performance metrics, and local policies,” according to Kruyt and colleagues.

Thus, results of their head-to-head comparison of stroke scales — in the setting of a Dutch population counting approximately 2 million people with two EMS systems, three comprehensive stroke centers, and four primary stroke centers — may not be reproduced in other places.

All seven prehospital triage scales demonstrated good accuracy, high specificity (80%-93%), and low sensitivity (38%-62%) in identifying candidates for endovascular thrombectomy.

“Of course, given their universally low sensitivities by design, application of any of these scales is expected to lead to a high rate of false positives. And the consequence for patients with false positives is a high level of overtriage to thrombectomy stroke centers or to comprehensive stroke centers,” commented Kori Zachrison, MD, MSc, of Massachusetts General Hospital and Harvard Medical School in Boston, and Pooja Khatri, MD, MSc, of University of Cincinnati, Ohio.

Such overtriage could lead to longer transport times and delays in alteplase (Activase) administration for eligible patients, the distancing of patients from families and support networks, and unnecessary crowding at comprehensive stroke centers, they warned in an accompanying editorial.

“Even so, in the long run, some overtriage is likely justified, and resources may need to be allocated to allow for this, given the unprecedented but time-sensitive benefit of endovascular thrombectomy on patient morbidity and mortality,” they wrote.

The study included people with EMS-activated stroke codes after initial FAST testing in 2018-2019. Mean age was 71.1 years, and 50.9% of the patients were men. The median NIH Stroke Scale score was 4.

Among the screening tools tested, RACE had a relatively low 78.1% feasibility rate, or the proportion of acute stroke codes for which the prehospital scale could be reconstructed. The most frequently missing item was motor deficit in the legs.

In contrast, the PASS scale had the best feasibility at 87.9%, which the authors suggested was due to the scale having fewer items that needed to be assessed compared with the other scales.

“[I]t is important to take feasibility into account before implementing a prediction scale in the field because focused training could substantially increase these rates,” Kruyt’s group said.

“The authors appropriately recognized that, in addition to accuracy, consideration of feasibility is critical when evaluating scales for the prehospital setting. Implementation should not place an undue burden on paramedics in the uncontrolled prehospital environment and amidst the various demands of the on-scene evaluation and transport of a patient who is in critical condition,” according to Zachrison and Khatri.

Kruyt’s team cautioned that paramedics did not fill out the observation sheet in 26.7% of acute stroke codes, which were excluded from the study. Furthermore, the study was limited in that it did not test all available prediction scales.

In any case, future advances in prehospital stroke triage might depend more on technology, according to the editorialists.

“Perhaps noninvasive sensors will turn out to be more efficient at identification of large strokes than these simple prehospital screening tools. Or perhaps we should consider more mathematically complex decision models easily made widely accessible by smartphone applications; such models may deal with uncertainty, consider probabilities, weigh various transport options, and even incorporate live traffic patterns to drive decision-making using artificial intelligence,” Zachrison and Khatri wrote.