Lorenz MW, Lauer A, and Foerch C. Quantifying the Benefit of Prehospital Rapid Treatment in Acute Stroke: Benchmark for Future Innovative Clinical Trials. Stroke. 2015  
 
​”Time is Brain,” so systems of care interventions in acute stroke have focused on decreasing the onset-to-treatment time (OTT). Such interventions have focused on prehospital time delay (i.e. increasing patient education on stroke warning signs, to decrease the onset-to-EMS call time), as well as in-hospital factors (i.e. transporting patients directly to CT, pharmacy at bedside for tPA administration). One novel method of decreasing prehospital delay is the use of a mobile CT scanner, which demonstrated a decrease in OTT of 40 minutes in a rural area, and 25 minutes in an urban area. Another approach has focused on the use of a blood test for GFAP (plasma glial fibrillary acidic protein) to rule out hemorrhage. GFAP has been shown to have a sensitivity of 80% for ICH, with a negative predictive value of 96%. The revolutionary idea of substituting the blood test in the prehospital phase for the pre-treatment CT scan would allow EMS to treat with tPA en route to the ED. One obvious concern is the risk of treating ICH patients with a false-negative GFAP with tPA.

The authors took an innovative approach to the problem of determining the benchmark for these novel prehospital interventions. They created decision models based on a mixed cohort of patients (ischemic stroke, ICH, SDH, SAH, and mimics) who were assumed to present within 4.5 hours, with NIHSS 4-22 and no exclusion criteria. Based on the available literature, estimations were made of the proportion of patients in each disease category, and the distribution of outcomes, with favorable outcome defined as mrs 0-1 at 90 days.

A model was created for prehospital mobile CT-guided tPA. A time gain of 60 minutes corresponded to a 6.6% increase in the likelihood of a favorable outcome. Treatment with tPA increased this likelihood by 7%, so an hour of decreased delay essentially doubled the benefit. The mobile CT scanner decreased the OTT by 40 minutes in a rural area, which would correspond to a 4.6% increased likelihood of favorable outcome. The 25 minutes saved by the mobile CT in an urban area increased the likelihood by 3%. Another model examined the use of prehospital CT (with CTA) to take patients directly to a stroke center with endovascular capability, but this only minimally increased the likelihood of favorable outcome.

A hypothetical blood-test-based prehospital tPA algorithm increased the likelihood of a favorable outcome by 3.9% when OTT was reduced by 40 minutes, and 5.9% with a time gain of 60 minutes. Using sensitivity analysis, the critical variables to this algorithm were time gain and sensitivity of the blood test to detect ICH. With an 80% sensitivity, a time gain of only 5 minutes was enough to justify the algorithm with the endpoint of “favorable outcome”. When quality-adjusted life years (QALY) was used as the endpoint, however, a minimum time gain of 32 minutes was required to compensate for the risk. The number needed to treat (when the time saved was between 40-60 minutes) to save one QALY was between 4 and 12.5, which amounted to 400 to 1250 Euros per QALY. Comparing this to the cost of a QALY with mobile CT, which is around 32000 Euros, the blood test is cost-effective.

The prehospital mobile CT does not increase risk, potentially increases benefit, and its only downside seems to be cost. The prehospital blood test has the potential to increase treatment rates and decrease treatment times, and is cheaper to implement, making it seemingly ideal for low-tech areas with long delays to CT scan (due to distance needing to be traveled) or without access to CT at all. However, the use of this test as a substitute for CT raises significantly more ethical issues than does the substitution of the mobile CT. While more patients may be treated and treated earlier, imparting better outcomes, there will be more patients who will be put in known danger – because we would be foregoing a reliable and safe test for a faster but less reliable one. As we shift to more patient-centered care, will we give patients the option of having the blood test (a high-risk-high-reward) versus the standard in-hospital CT (assuming mobile CT is not at play here)? Since these are pre-hospital interventions, will consent for tPA be obtained? Will EMS be responsible for reviewing the exclusion criteria? We will also be relying on EMS to determine the last known normal time, and there is data to show that these are often inaccurate. Will there be more complications since EMS is not perfect at identifying stroke syndromes, both having a low sensitivity (especially for posterior circulation strokes) and a relatively low specificity (difficulty weeding out mimics). Maybe the presence of a physician via telemedicine would help in the determination of appropriateness of tPA.

This excellent paper sets up the foundation for several important next steps, the first of which is further rigorous testing of the GFAP blood test. Once this is thought to be ready for prime-time, the next step would be an ambulance based “road test” of the blood test, in which the treatment decision is made based on the blood test, but the actual treatment is administered based on standard-of-practice in-hospital CT, and the results are compared. This will help determine the actual sensitivity of the test, the diagnoses of patients who would have been treated, and the accuracy of EMS at determining not only the last known normal time but identifying which patients are having stroke syndromes. If this is a success, we may consider whether a clinical trial of the blood test, in which patients are randomized to the blood test or an in-hospital CT and treated based on the results, is safe and ethical to implement.