![]() ![]() However, frequent collection of multiple questionnaires at shorter interval visits is burdensome for people living with chronic pain (and their clinicians), as it requires up to 54 questions across instruments. An individual’s perception of pain and its effect on daily activities and overall health are hard to capture in a single data point recorded in a clinical visit 20. ![]() Additionally, there are limitations and the potential for subjective bias on the part of clinical evaluators 20. These tools rely on the person’s assessment, which is subject to memory, cognitive, social desirability, and other psychologically influenced response biases. To capture the more comprehensive and multidimensional effects of pain, people with chronic pain often answer several other questionnaires, such as the Pain Catastrophizing Scale (PCS) 15, which provides insight into the psychological aspects of pain, Oswestry Disability Index (ODI) for disability and function 16, and Patient-Reported Outcomes Measurement Information System 29 (PROMIS-29) for global health measure 17, Patient Health Questionnaire-9 (PHQ-9) for depression 18, and Patient Global Impression of Change (PGIC) 19 for the perception of improvement with different therapies. Efforts to capture multidimensional aspects of chronic pain and treatment effects have historically been done through the addition of other validated PRO questionnaires 13, 14. The current gold standard for evaluating pain is using unidimensional PROs such as the Numerical Rating Scale (NRS) or the Visual Analog Scale (VAS) 11, 12. The condition of a person with chronic pain is usually evaluated through several patient-reported outcome (PRO) measures administrated manually in an in-clinic visit. Thus, appropriate individual selection and long-term monitoring are crucial in optimizing the outcomes of SCS therapy 9, 10. Response to therapy over time varies from person to person and often requires interactive adjustment of therapy parameters 8. Spinal cord stimulation (SCS) is an effective treatment option for chronic pain and often leads to pain reduction and improvement in quality of life 4, 5, 6, 7. Pain that lasts for more than three to six months is often considered chronic and is influenced by a complex combination of biopsychosocial factors including but not limited to emotional, psychological, physical, and social considerations 2, 3. Similar content being viewed by othersĬhronic pain is a debilitating condition affecting a widespread population in the United States, estimated at over 50 million American adults 1. The results of the study suggest that wearable biomarkers can be used to predict therapy outcomes in people with chronic pain, enabling continuous, real-time monitoring of patients during the use of implanted therapies. ![]() Feature importance analysis showed that digital biomarkers from the smartwatch such as heart rate, heart rate variability, step count, and stand time can contribute to modeling different aspects of pain. The model reached an accuracy of 0.768 ± 0.012 in predicting the pain intensity of mild, moderate, and severe. During the six months of the study, activity and physiological metrics were collected and data from 15 participants was used to develop a machine learning pipeline to objectively predict pain levels and categories of PRO measures. Twenty participants with chronic pain were recruited and implanted with SCS. This study aims to assess the feasibility of using digital biomarkers collected from wearables during SCS treatment to predict pain and PRO outcomes. Patient Reported Outcomes (PROs) from standard survey questions do not provide the full picture of what has happened to a patient since their last visit, and digital PROs require patients to visit an app or otherwise regularly engage with software. However, perceived treatment response to SCS therapy may vary among people with chronic pain due to diverse needs and backgrounds. Spinal Cord Stimulation (SCS) is a well-established therapy for treating chronic pain. ![]()
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