Abstract Body (Do not enter title and authors here): Introduction: Early detection of large vessel occlusion (LVO) facilitates triage to appropriate stroke centers and reduces treatment times. Prehospital stroke scales are insensitive, so we investigated the ability of the Openwater Headset, a portable optical blood flow monitor, to detect LVO in patients undergoing acute stroke evaluation.
Hypothesis: We hypothesized that the Openwater Headset would detect LVO with greater sensitivity and specificity than prehospital scales.
Methods: At two comprehensive stroke centers, eligible patients presented to the emergency department or were transferred from another facility for acute stroke evaluation within 24 hours of symptom onset and NIHSS ≥2. Eligible patients underwent emergent vascular imaging as per routine care. LVO was defined as occlusion of the ICA or the first/second segment of the MCA. Each patient underwent a 70-second bedside optical blood flow evaluation with the Openwater Headset (prior to endovascular therapy, if applicable). The Openwater Headset generated blood flow waveforms based on the relative change in the speckle contrast, acquired at 40 Hz. A deep neural network was trained to identify waveform features that discriminate LVO status (Figure 1a), withholding a validation set to test model performance. ROC analysis compared Openwater Headset performance with that of prehospital stroke scales.
Results: 135 patients completed the optical evaluation a median of 6 hours after symptom onset (IQR: 3-14). The median NIHSS was 9 (IQR: 4-18). 52 patients (39%) had a LVO. The Openwater LVO stroke alert algorithm had 81% sensitivity and 80% specificity for the presence of LVO (AUC 0.85 by ROC analysis), exceeding that of prehospital stroke scales (Figure 1b).
Conclusions: The Openwater Headset outperformed prehospital stoke scales for LVO detection in patients who underwent acute stroke evaluation, but further investigation is needed to assess performance in pre-hospital settings.