Adam Ferguson, Brain and Spinal Injury Center (BASIC), University of California San Francisco, San Francisco, USA

Reproducibility and translation of hemodynamic predictors in SCI: Testing the limits using big-data

Funded in: 2016, 2017, 2018

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Problem: Large number of potential targets, but so far no translation into clinical care

Target: Analyses revealed the finding that blood pressure in the acute phase of SCI predicted long-term recovery

Goal: Testing the limits using big-data on reproducibility and translation


INTRODUCTION: Spinal cord injury is extremely complex. This complexity results in a wide set of functional changes that are due to system-wide changes in multiple organ systems, including the nervous system, cardiovascular, immune and musculoskeletal systems. Using tightly-controlled laboratory studies in animal models, researchers have revealed a number of distinct aspects of the biology of injury. The good news is that this work has generated large number of potential therapeutic targets for clinical application. However, none of these therapies have yet translated into clinical care.

PROBLEM STATEMENT: In this sense, SCI represents a ‘big-data’ problem: we now have enormous amounts of basic scientific discoveries about SCI, but it remains unclear how best to integrate all of this science to promote translational therapies for clinical application. METHODS: In prior work we took a novel analytical approach for SCI data integration, applying machine learning tools a large repository of pooled data from preclinical animal studies from multiple centers (the VISION-SCI repository). These analyses revealed the unexpected finding that blood pressure in the acute phase of SCI predicted long-term recovery with greater precision than many other biological factors. For the proposed study we will cross-validate these findings in newly-curated rat data and test for translation of these effects using de-identified human medical records.

EXPECTED RESULTS: We predict that abnormally high or low blood pressure in the acute injury phase will predict outcome with high precision in both animal models and human patients.

POTENTIAL APPLICATION: High-resolution blood pressure management may represent a highly treatable new therapeutic target for precision medicine in SCI since numerous drugs exist to treat blood pressure. The funded project will allow us to define the limits of this effect, generating precise information that can be used to help develop clinical guidelines for SCI acute care to optimize chronic recovery.