Sickle cell disease (SCD) is a hereditary condition of abnormal hemoglobin affecting over 100,000 Americans, primarily those of African descent, where sudden onsets of severe pain called vaso-occlusive crisis (VOC) occur due to obstruction of microvascular blood flow by rigid sickle-shaped red blood cells. Sympathetically-mediated vasoconstriction in the peripheral vasculature with resulting decrease in tissue perfusion is the likely triggering mechanism for the onset of VOC and inherent differences in autonomic vasoreactivity, which likely contribute to variability in VOC frequency and severity, make SCD a model disease for the study of vasoconstriction mediated disease. We have shown that a greater magnitude of vasoconstriction occurring during sleep is predictive of higher VOC frequency. In order to develop this finding into a biomarker for early detection of increased VOC risk, and explore vasoconstriction in other disorders, long term monitoring of large patient populations in home settings is needed. We propose the development of a “smart” system, consisting of a wearable wrist optical device with integrated mobile application for home monitoring of daily pain frequency and severity. Advanced biomedical signal processing techniques and artificial intelligence algorithms will be employed to determine nocturnal vasoconstriction indices and their correlation with future clinical pain outcomes. The integration of these components will be the basis of a low-cost “early detection system” for increased VOC risk, providing a window for therapeutic interventions to mitigate VOC and decrease opioid dependence. This mHealth solution has not only national but global implications in improving access to care in this underserved population, and may also impact other disease states where peripheral vasoconstriction plays a role in the pathophysiology.
