How Impedance Spectroscopy Improves the Fracture Repair Process
Impedance Spectroscopy for Fracture Healing; Which Patient Reported Outcomes Work Best?; Wearable Sensors Reduce Pressure Injuries

What’s going on with a fracture as it moves through the healing process? A team of California researchers set out to bring some clarity to this question.
Their work, “New opportunities for fracture healing detection: Impedance spectroscopy measurements correlate to tissue composition in fractures,” appears in the December 30, 2018 edition of the Journal of Orthopaedic Research.
Monica Lin, a Ph.D. student in the University of California, Berkeley-University of California San Francisco Graduate Program in Bioengineering, first author on the study, told OTW, “A vast proportion of the population is affected by orthopaedic injuries, yet this field lags behind many other medical areas in terms of quantitative assessment techniques.”
“Physician examinations involving patient questionnaires and qualitative inspection still remain the most common form of assessing the state of fracture healing. While X-rays are typically used during follow-up visits, they rely on mineralization of bone tissue, and are thus only useful at the final stages of healing.”
“Determining how well a fracture is healing is crucial to making correct clinical decisions for patients, yet there are currently no standardized methods of assessing fracture union. Our study demonstrates the potential of impedance spectroscopy to provide additional quantitative information that can better inform physicians about the state of healing in their patients’ fractures.”
“We saw an opportunity to use impedance spectroscopy, a technique that has been used to study different types of tissues, to provide quantitative and more continuous information about the state of a fracture as it progresses through the entire healing process.”
“Smart implant technology in the field of orthopaedics has been mainly limited to mechanical measurements, while our study closely evaluates the potential of impedance spectroscopy to track the different electrical properties of the various tissue types present in fracture healing.”
“While previous studies have shown promise in using impedance spectroscopy to differentiate between fracture and control groups, to our knowledge, we are the first to correlate impedance measurements with histological characterization. In addition, in order to evaluate the translation of this technology to a clinical setting, we conducted an experiment to understand how a metal implant would affect our electrical measurements.”
“In an ex vivo mouse study with samples collected at three time points over healing time, we found that impedance correlates to tissue compositions of heterogeneous calluses. Impedance magnitude (reflects conductivity of tissue) and phase (reflects how resistive or capacitive a measurement is) both show clear trends with the percent of cartilage and trabecular bone within fracture calluses. This demonstrates the power of this technique to predict fracture tissue composition, which has the potential to enable early detection of bone healing and fracture nonunion.”
“We demonstrated the feasibility of impedance spectroscopy for detecting fracture callus composition, laying the groundwork for additional studies that measure in vivo changes in mice and larger animal models that will enable us to fully understand the sensitivity of this technique. Ultimately, for patients undergoing surgical intervention to stabilize their fractures, instrumented implants can provide a quantitative measure of healing during follow-up visits.”
Which Patient Reported Outcomes System Works Best?
Looking at multiple orthopedic domains, researchers undertook a multicenter study to determine whether the Patient-Reported Outcomes Measurement Information System (PROMIS) is as effective as traditional patient reported outcomes (PROs). “Patient-Reported Outcomes Measurement Information System and Legacy Patient-Reported Outcome Measures in the Field of Orthopaedics: A Systematic Review,” appeared in the October 30, 2018 edition of the journal Arthroscopy.
Eric C. Makhni, M.D., M.B.A., attending surgeon in the Division of Sports Medicine at the Henry Ford Health System in Detroit, Michigan and co-author on the study, told OTW, “There has been significant recent interest in the new NIH [National Institutes of Health] patient reported outcome (PRO) system called PROMIS [Patient-Reported Outcomes Measurement Information System].”
“The advantage of PROMIS is that it allows for PRO collection across a number of health and musculoskeletal domains in a far more efficient manner than that of traditional ‘legacy’ PRO scores. The main advantage of PROMIS is the presence of computer adaptive test (CAT) forms, which are highly dynamic and efficient ways to measure patient health.”
“This is the first study to our knowledge to perform a systematic review of research that has utilized PROMIS in musculoskeletal health. We compared PROMIS scores with traditional PRO forms across a number of musculoskeletal domains. This provides some early evidence regarding the correlation between PROMIS forms and legacy PRO forms. Theoretically, if we can demonstrate a good correlation between the two types of PRO forms, then the argument can be made that PROMIS may be a far more efficient method for measuring patient reported outcomes without any loss of validity.”
“The main finding in our study is that PROMIS physical function forms showed strong correlation with legacy PRO scores across orthopedic domains (upper extremity, lower extremity, and spine). Moreover, our study confirmed that administration of PROMIS is more efficient than that of legacy scores (100 seconds versus 244 seconds required for completion, respectively). In other words, PROMIS is just as good as legacy PRO but significantly shorter and more efficient to administer.”
“In practical terms, the orthopedic community should consider incorporating PROMIS into their PRO collection algorithms. While PROMIS is new and therefore still a largely unknown entity to most researchers and practitioners, the case can be made that we should educate the orthopedic community about the benefits and utility of PROMIS.”
“Hopefully, this study will motivate orthopedic clinicians and researchers to read and learn about PROMIS and in particular begin to think about different ways that PROMIS may be useful from a clinical and research application. Widespread incorporation of such a useful clinical tool will no doubt assist in patient care and clinical research alike, allowing us to take the best care of our patients that is possible.”
Study: Wearable Sensors Protect Against Pressure Injuries
The results of a new randomized controlled trial from Stanford Health Care show that a wearable patient sensor goes a long way toward preventing pressure injuries.
The study, “Effect of a wearable patient sensor on care delivery for preventing pressure injuries in acutely ill adults: A pragmatic randomized clinical trial (LS-HAPI study),” was published in the January 1, 2018 edition of the International Journal of Nursing Studies. The study found that patients treated by wearable sensors were 73% less likely to develop a pressure injury. The manufacturer is Pleasanton, California based Leaf Healthcare.
According to the company, “The investigator-initiated, prospective, blinded, randomized, controlled trial involved over 1,200 patients and over 100,000 hours of data was analyzed…. In the Treatment group, the Leaf sensor was used to help ensure that patients were repositioned with sufficient frequency and quality. The Leaf sensor continuously monitors all patient movements and is designed to notify providers if repositioning is required to prevent a pressure injury. The sensor seamlessly monitors patient position and activity, regardless of whether they are in bed, a chair, or ambulating.”
“This large, randomized, controlled trial confirms what has been demonstrated in smaller studies and is consistent with real-world customer experience,” said Leaf Healthcare CEO and Co-Founder Barrett Larson, M.D. “This study is an important step towards redefining the standard of care for pressure injury prevention.”
Dr. Larson told OTW, “This landmark research study has the potential to fundamentally change the way care is delivered for patients at risk for pressure injuries. The clinical and financial benefits associated with improved patient mobility are well established. As we think about the hospital of the future, it’s hard to imagine turning protocols being coordinated using manual methods, clinical observation, and intuition. It’s time for this fundamental nursing practice to evolve through the use of technology. The LS-HAPI study proves that a wearable sensor can be used to intelligently optimize patient mobility protocols and significantly improve patient outcomes.”
“The LS-HAPI study was one of the largest and most scientifically rigorous studies ever to be conducted in the field of pressure injury prevention. This was a ‘gold standard’ study that had the following design elements:
- Investigator-initiated: Study was initiated by Stanford (not Leaf). Leaf had no role in the design of the study, recruitment of subjects, data collection or management, analysis or interpretation of results, drafting of manuscript, or decision to publish.
- Pragmatic: Study was done in a real-world clinical environment, not a hyper-controlled research setting that doesn’t reflect clinical reality.
- Prospective and Parallel: After randomization, patients were assigned to treatment or control groups which ran in parallel (same ICUs, no difference in clinical environment between groups).
- Blinded: Wound care nurses responsible for staging HAPIs were blinded to subject group allocation. Data analysts were also blinded to subject group allocation.
- Randomized: Patients were randomly allocated to either a Treatment or Control Group. The randomization schema minimizes bias. This is considered the ‘gold-standard’ approach for clinical trials.”
“The Leaf system helped ensure that patients were turned with with sufficient frequency and quality. In patients treated with Leaf, there was a significant improvement in position optimization and a significant decrease in rates of hospital-acquired pressure injuries (73% reduction).”
“Patient turning is considered one of the most effective strategies for pressure injury prevention (Class A Evidence). However, in the busy hospital setting, it can be difficult to ensure that every patient reaches their individual mobility goals. The Leaf System intelligently optimizes turning and mobility protocols for large groups of patients and it is much more effective than standard reminder systems (i.e., kitchen timers, musical chimes, manual documentation, etc.). The Leaf System can be used to significantly improve patient mobility and clinical outcomes. Leaf has been clinically proven to prevent pressure injuries.”
“Improved post-operative mobility is associated with lower complication rates (i.e., pressure injuries, DVT, etc.) and reduced length of stay. The Leaf System is designed to monitor, coordinate, and optimize care throughout the mobility continuum—from bedridden to fully ambulating patients. When patients are in bed, the Leaf system will help ensure that they are repositioned with sufficient frequency and quality in order to prevent pressure injuries. As a patient’s mobility level improves, the Leaf System will track other important mobility metrics (i.e., time spent upright, steps taken, etc.) as part of a comprehensive mobility management program.”

Discussion
This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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