Accurate and reliable non-invasive monitoring of early systemic disease—such as ongoing hemorrhage, sepsis, and acute respiratory disease like COVID-19—is one of the largest unmet needs in biomedicine. An early alert to progression with high sensitivity and an acceptable false-positive rate would allow medical staff to risk-stratify patients, saving resources, lives, and in the context of pandemic disease, minimize staff exposure. Noninvasive technologies have thus far failed to produce a reliable early detection system, reflecting the limitation of uniplex approaches to describe complex pathophysiology. Our team, in collaboration with an STTR start-up, have developed an optico-impedance system combining near-infrared spectroscopy and electrical impedance tomography measured at three locations (thorax, abdomen, limb) together with machine learning methods to provide exceptional diagnostic performance in systemic disease. The optical portion consists of 6 pairs of time-multiplexed red and IR LEDs embedded in custom 3D-printed probes, which are each connected to the leg of a trifurcated fiber bundle, allowing measurement of three-location, two-distance broadband 550-950 nm spectra using a single commercial spectrometer. Data is demultiplexed and analyzed using derivative spectroscopy to quantify oxy/deoxyhemoglobin. Additional diagnostic signal was obtained from: impedance tomography and spectroscopy, ECG and plethysmography. In one of the largest porcine hemorrhage studies to date (n = 60), we demonstrate an 85% accuracy to detect a 2-3% blood volume loss. Preliminary results from 11 healthy human subjects undergoing lower body negative pressure (LBNP) challenge show a 95% accuracy in detecting 15-mmHg changes in pressure—an excellent surrogate for occult hemorrhage. Our system fills a critical need, including in the current pandemic, where clinicians struggle to predict which patients will deteriorate.
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