Our analysis is based on a probabilistic model built to estimate the probability of good outcome (defined as modified Rankin Scale score ≤ 2) for patients with AIS and unknown vessel status as a function of stroke severity, transport times to the nearest PSC and CSC, and transfer times between PSC and CSC. Details of the model have been published previously. [
3] Briefly, for any location on a two-dimensional temporo-spatial plane closer to a PSC than to a CSC (i.e., the region with uncertainty regarding the optimal transport destination), the optimal RACE cutoff score that should be used to determine the transport destination for a patient with suspected AIS was calculated based on the expected stroke severity-dependent probability of LVO among all patients with ischemic stroke [
6] and published time-decay curves for the effects of thrombolysis and EVT. [
7,
8] This optimal RACE cutoff score takes into account expected transport times to the PSC and CSC, the transfer time between the nearest PSC and CSC, as well as performance metrics at PSC and CSC (door-to-needle time, door-out-time, and door-to-groin time) and was shown to perform better than any fixed RACE cutoff score. Patients with a RACE score ≥ optimal cutoff score would be transported to the nearest CSC (mothership approach), while all other patients would be transported to the nearest PSC with secondary transfer to the CSC if needed (drip and ship approach). Stroke severity is assessed by the RACE scale (scores ranging from 0 to 9) with higher scores indicating more severe strokes. The RACE scale is a prospectively validated 5-item clinical scale that assesses facial palsy, upper and lower limb motor function, gaze deviation, and aphasia or agnosia (according to the side of hemiparesis). Using a fixed cutoff score of ≥5, its accuracy for the detection of LVO was found to be 0.72. [
6] Our model assumes a physiological perspective focusing on reperfusion, which can occur after thrombolysis or EVT. It accounts for possible recanalization during secondary transfer and for reduced time to groin puncture at the CSC if the stroke team is notified in advance. Model parameters are displayed in Table
1. To quantify the added benefit of a hypothetical prehospital LVO detection tool with 100% accuracy, we calculated probabilities of good outcome for each point on the temporo-spatial plane as a function of stroke severity and transfer time between hospitals assuming that vessel status could be ascertained with certainty on scene. We then compared the results with probabilities of good outcome attainable with the currently available RACE scale. Simulations were performed in MATLAB. Results are presented as beanplots [
9] generated in R. [
10] The vertical spread of each bean represents the distribution of results across the temporo-spatial plane (i.e., different combinations of expected transport times to the nearest PSC and CSC). No ethical approval and no informed consent was required for this study.
Table 1
Parameters used in the modela
Onset-to-alarm | 30 | |
Alarm-to-scene | 15 | Federal Highway Research Institute Germany [ 15] |
On-scene | 30 | Personal experience from the Berlin fire brigade [ 3] |
Transfer (PSC-to-CSC) | 15, 60, and 120 | |
Door-to-needle | CSC: 30 PSC: 30 | |
Door-out | 30 | Holodinsky et al., [ 16] Schlemm et al. [ 3] |
Door-to-groin | Mothership approach: 90 Drip and ship approach: max(50, 90 – door-out – transfer) |
Groin-to-reperfusion | 30 |
Treatment time windows | Thrombolysis: 270; EVT (onset-to-groin): 360 | American Heart Association [ 17, 18] |