Search

Background: Spinal cord stimulation (SCS) is a highly effective therapy for treating and management of refractory chronic pain. However, complex nature of pain and infrequent in-clinic visits, determining subject’s long-term response to the therapy remains difficult. Frequent measurement of pain in this population can help with early diagnosis, disease progression monitoring, and evaluating long-term therapeutic efficacy. This paper compares the utilization of the common subjective patient-reported outcomes with objective measures captured through a wearable device for predicting the response to SCS therapy. Method: Data is from the ongoing international prospective post-market REALITY clinical study, which collects long-term patient-reported outcomes from 557 subjects and the sub-study designed for collecting additional wearables data on a subset of participants for up to six months after SCS implantation. We first implemented a combination of dimensionality reduction algorithms and correlation analyses to explore the mathematical relationships between objective wearable data and subjective patient-reported outcomes. We then developed machine learning models to predict SCS therapy outcome based on the subject’s response to NRS or PGIC. Results: Principal component analysis results showed that psychological aspects of pain were closely associated with heart rate variability, while movement-related measures were closely associated with patient-reported outcomes related to physical function and social role participation. Our machine learning models using objective wearable data predicted both PGIC and NRS outcomes with high accuracy in the absence of subjective data. The prediction accuracy was higher for PGIC compared with the NRS using subjective-only measures primarily driven by the patient satisfaction feature. Similarly, the PGIC questions, reflects an overall change since the study onset and could be a better predictor of long-term therapy outcome. Conclusions: The significance of this study is to introduce a novel use of wearable data collected from a subset of patients to capture multi-dimensional aspects of pain and compare the prediction power with the subjective data from a larger data set. The discovery of pain digital biomarkers could result in a better understanding of the patient’s response to therapy and their general well-being.

In this review, we present a comprehensive clinical approach to restorative neurostimulation, a novel form of stimulation for refractory chronic mechanical low back pain, targeting impaired neuromuscular control and degeneration of the multifidus muscle. We focus on patient identification, technique guidance, and review of the scientific background and clinical evidence. As our understanding of back pain grows, there is clear evidence that impaired neuromuscular control and consequent degeneration of the multifidus muscle contribute to mechanical low back pain development and maintenance. We provide clinical guidance regarding an implantable restorative neurostimulation system that targets impaired neuromuscular control. Supported by results from a randomized, active-sham-controlled clinical trial with long-term follow-up, we provide clinicians with a comprehensive overview and practical clinical guidance for the adoption of this therapy modality.

Spinal Cord Stimulation (SCS) is a well-established therapy for treating chronic pain. However, treatment response to SCS therapy may vary among people with chronic pain due to diverse pain perspectives amongst them. While, currently, chronic pain is evaluated by clinically validated patient reported outcomes (PROs) measures completed during a clinical assessment, monitoring improvement of the participant’s progress over time and comparison of PROs across participants remains subjective and challenging. Thus, objective measures to quantify pain are invaluable. This study aims to assess the feasibility of using digital biomarkers collected from wearables during SCS treatment to predict pain and PRO outcomes. Twenty participants with chronic pain were recruited and implanted with SCS. 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 and PRO measures. We were able to reach the accuracy of 0.832 ± 0.012 in pain intensity prediction. The feature importance analysis showed that digital biomarker from the smart watch such as heart rate, heart rate variability, step count, and stand time can contribute to modeling different aspects of pain. The results of the study suggest that wearable biomarkers can be used to predict therapy outcomes in people with chronic pain and bring us another step closer towards objective evaluation of chronic pain.

Introduction DeRidder's burst stimulation design has become a key spinal cord stimulation (SCS) waveform because it reduces the intensity of pain as well as its associated emotional distress. The brain pathways underlying these outcomes may also allow for the effects of stimulation to carry over after stimulation is turned off, making it amenable to intermittent application. Here, the utility of intermittently cycled burst was evaluated using data from two large real-world prospective studies (TRIUMPH, REALITY). Materials and methods Subjects used intermittent dosing in a 1:3 ratio (30 sec on, 90 sec off; N = 100) in TRIUMPH and 1:12 ratio in REALITY (30-sec on, 360-sec off; N = 95) for six months. Pain intensity (0-10 numeric rating scale), pain-related emotions on the pain catastrophizing scale (PCS), and physical function on PROMIS questionnaires were compared with preimplant baseline ratings and by group. Results In both groups, mean pain intensity decreased by nearly 50% relative to baseline, PCS scores significantly decreased, and physical function improved. Importantly, no differences between the 1:3 and 1:12 groups were identified. A high proportion, 80% and 77% of the 1:3 and 1:12 groups, respectively, were considered responders on a multiple measures. No adverse events were associated with intermittent stimulation. Discussion Intermittent cycling of burst SCS lowers the overall electric charge delivered to the spinal cord and preserves battery consumption, without compromising pain relief and associated symptoms.

Multidisciplinary patient-reported outcomes are a critical part of assessing patients to better understand their well-being during treatment. The use of multidisciplinary patient-reported outcomes is recommended in many areas of medicine. The Patient-Reported Outcomes Measurement Information System-29 (PROMIS-29) has been utilized as a common measurement language across universally relevant domains, including pain, mood, sleep, social participation, and function. Retrospective analysis of prospectively collected data was performed. Subjects were identified and consecutively enrolled upon entry into chronic pain centers across 24 sites in the United States. The PROMIS-29 v2.1 and the numerical rating scale (NRS) were recorded. The pain impact score and the Health Utilities Index Mark 3 (HUI-3) were calculated. Statistical differences were assessed between genders and among age groups comprising subjects less than 40, 41–60, 61–80, and over 80 years of age. A total of 19,546 patients were assessed over the enrollment period from 2018 to 2020. The PROMIS-29 v2.1 was evaluated across the seven domains, along with the numerical rating sale (NRS). The mean scores of the population for PROMIS SF v1.0 Pain Interference 4a, PROMIS SF v1.0 Sleep Disturbance 4a, PROMIS SF v1.0 Fatigue 4a, PROMIS SF v1.0 Anxiety 4a, PROMIS SF V1.0 Depression 4a, PROMIS SF v2.0 Ability to Participate in Social Roles and Activities 4a, and PROMIS SF v1.0 Physical Function 4a, measuring pain interference, sleep disturbance, fatigue, anxiety, depression, social participation, and physical function, were 64.61, 57.19, 58.50, 53.94, 54.45, 40.06, and 36.23, respectively. Pain intensity was 6.38 on an 11-point NRS scale. The pain impact score (PIS) and health utilities index mark 3 (HUI-3) scores, calculated across the designated age groups, were 33.19 and 0.67, respectively. Statistical differences were observed for the domains of sleep disturbance and physical function for age groups less than 40 and greater than 80 years of age. This data set is the first published normative data set describing the PROMIS-29 assessment in the chronic pain population. The patient population is more homogeneous than expected, and females were found to have higher levels of dysfunction.

Multidisciplinary patient-reported outcomes are a critical part of assessing patients to better understand their well-being during treatment. The use of multidisciplinary patient-reported outcomes is recommended in many areas of medicine. The Patient-Reported Outcomes Measurement Information System-29 (PROMIS-29) has been utilized as a common measurement language across universally relevant domains, including pain, mood, sleep, social participation, and function.Retrospective analysis of prospectively collected data was performed. Subjects were identified and consecutively enrolled upon entry into chronic pain centers across 24 sites in the United States. The PROMIS-29 v2.1 and the numerical rating scale (NRS) were recorded. The pain impact score and the Health Utilities Index Mark 3 (HUI-3) were calculated. Statistical differences were assessed between genders and among age groups comprising subjects less than 40, 41-60, 61-80, and over 80 years of age.A total of 19,546 patients were assessed over the enrollment period from 2018 to 2020. The PROMIS-29 v2.1 was evaluated across the seven domains, along with the numerical rating sale (NRS). The mean scores of the population for PROMIS SF v1.0 Pain Interference 4a, PROMIS SF v1.0 Sleep Disturbance 4a, PROMIS SF v1.0 Fatigue 4a, PROMIS SF v1.0 Anxiety 4a, PROMIS SF V1.0 Depression 4a, PROMIS SF v2.0 Ability to Participate in Social Roles and Activities 4a, and PROMIS SF v1.0 Physical Function 4a, measuring pain interference, sleep disturbance, fatigue, anxiety, depression, social participation, and physical function, were 64.61, 57.19, 58.50, 53.94, 54.45, 40.06, and 36.23, respectively. Pain intensity was 6.38 on an 11-point NRS scale. The pain impact score (PIS) and health utilities index mark 3 (HUI-3) scores, calculated across the designated age groups, were 33.19 and 0.67, respectively. Statistical differences were observed for the domains of sleep disturbance and physical function for age groups less than 40 and greater than 80 years of age.This data set is the first published normative data set describing the PROMIS-29 assessment in the chronic pain population. The patient population is more homogeneous than expected, and females were found to have higher levels of dysfunction.

OBJECTIVE The purpose of this study was to compare the trial success rate between anatomic lead placement (AP) and paresthesia-mapped (PM) lead placement techniques for spinal cord stimulation (SCS) using a nonlinear burst stimulation pattern. MATERIALS AND METHODS Eligible patients with back and/or leg pain with a Numeric Rating Scale (NRS) score of ≥6 who had not undergone previous SCS were enrolled in the study. A total of 270 patients were randomized in a 1:1 ratio to each treatment arm. In the AP group, one lead tip was placed at the mid-body of T8, and the other at the superior endplate of T9. In the PM group, physicians confirmed coverage of the patient's primary pain location. Trial success was a composite of the following: ≥50% patient-reported pain relief at the end of the minimum three-day trial period, physician's recommendation, and patient's interest in a permanent implant. RESULTS Trial success for AP vs. PM groups was equivalent to 84.4% and 82.3%, respectively. Physicians who performed both techniques preferred AP technique (70% vs. 30%). Procedure times for placement of two leads were 31% shorter in the AP group (p