Cost-Effectiveness Analysis of the Nociscan Guiding the Accurate Diagnosis and Appropriate Treatment of Back Pain due to Painful Disc Degeneration
Determine the cost-effectiveness of the use of Nocimed/Nociscan compared with usual diagnostic decision making in patients with discogenic low back pain. The cohort studies would include patients undergoing one or two level fusion surgery for a diagnosis of symptomatic disc degeneration, in the absence of instability or deformity following data from the Gornet study results. The present care pathway for this cohort of patients includes diagnostic imaging, provocative testing including discography, and diagnostic injections. The costs of care include both the diagnostic modalities, and the costs of care including inappropriate fusions, or inappropriate use of non-operative interventions resulting in limited improvement or worsening of health status of patients.
Principal Investigator: Dr. Leslie Wilson
Principal Investigator: Dr. Sigurd Berven
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