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Cost-effectiveness of a novel, non-invasive diagnostic test for chronic low back pain patients.  

Thirty-one million Americans suffer from low back pain. In approximately 20%, the pain is chronic with about 5% ultimately receiving surgery. However, there is no consensus method to differentiate those who will benefit from surgery from those who won’t. Typically, the decision for surgery is made by clinical exam plus MRI imaging, alone or with a provocative discogram (PD). However, PD is controversial for its potential adverse events, subjective nature, and discomfort for the patient. A promising non-invasive diagnostic method for identifying painful lumbar discs in those with discogenic back pain is magnetic resonance spectroscopy (MRS) plus a Nociscan diagnostic algorithm that converts the quantitative and continuous spectral data into a binary pain classification validated against PD. The objective of this study was to determine if this non-invasive diagnostic is cost-effective compared with PD. We will calculate the incremental cost-effectiveness ratio (ICER) and conduct probabilistic sensitivity analysis using Mone Carlo simulations to demonstrate parameter uncertainty across all variables.


Principal Investigator: Dr. Leslie Wilson

Regeneration of Craniofacial Muscle after Volumetric Muscle Loss using Hydrogel, Muscle Stem Cells and Chemokines

Massive loss of facial muscle from traumatic injuries or cancer resection surgery, often beyond repair, can result in face deformation, pain, and psychological affliction. We propose a combination approach of a bioinspired hydrogel with human muscle stem cells and chemokines to stimulate the regeneration of craniofacial muscle.

Principal Investigator: Dr. Jason Pomerantz

Principal Investigator: Dr. Kevin Healy


Understanding Bacterial Infiltration into Bone and Bone Allograft

Bacterial colonization of orthopaedic implants and bones is a devastating condition that is difficult to treat. In this project we use microfluidic systems to determine how bacteria (S. aureus) can penetrate into nanoscale channels in bone and other materials. Our findings have the potential to influence sterilization of bone allograft and surgical treatment for periprosthetic joint infection.

Principal Investigator: Dr. Christopher Hernandez


Evaluating the Efficacy of Low-Cost Patient Handling Interventions for Home Healthcare

Home healthcare workers HHW) are essential workers, assisting millions of people in performing daily personal care task, including some tasks that are phsyically stressful for the HHW, who is typically working alone (unassisted).  To retain current HHW (median age 46 yr; PHI, 2021) and attract new workers to the field, the quality of worklife needs to be improved for these essential workers, including reducing their injury risk factor exposure.  A recent report found “little literature or research on the prevalence of the use and effectiveness of assistive technologies and home modifications for lifting, transferring, and repositioning for reducing homecare worker injuries”….and barriers to obtaining and using such equipment in the home, including “difficulty identifying appropriate assistive technologies and home modifications,…, and limited training on appropriate use” (DHHS, 2022).  This study will investigate multiple types of affordable equipment that are of particular interest to home healthcare agencies, as well as report the results in a format(s) and mode(s) that is useful and accessible to home healthcare agencies and other intended users. 


Principal Investigator: Dr. Carolyn Sommerich

Principal Investigator: Dr. Steve Lavender

Extending the Use of Dynamic Spine Modeling with Machine Learning Project Summary

The Ohio State University Spine Research Institute has an extensive database of motion, EMG, and resultant spinal load model data from years of different biomechanics studies. This study will leverage existing data with machine learning to build predictive models. These models will predict time dependent spinal load data using only wireless sensors for inputs which will make it feasible to employ them in the field. This could provide a more accurate and useful tool to evaluate spine injury risk in industrial work environments. This would reduce the reliance on laboratory work task simulations and the use of naïve subjects instead of actual workers.


Principal Investigator: Dr. Gregory Knapik

Principal Investigator: Dr. William Marras

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