BackgroundPhysical activity (PA) is recommended for people with persistent musculoskeletal pain due to its benefits on symptoms, function and general health. This systematic review aimed to identify the barriers and facilitators to PA for people with persistent musculoskeletal pain and categorise these using the Theoretical Domains Framework (TDF). It also aimed to identify the prominence of each TDF domain and similarities and differences between included conditions and PA types.MethodsEligible studies reported barriers and/or facilitators to PA for adults with persistent musculoskeletal pain. Barriers and facilitators were coded using the TDF. Thematic analysis was then conducted within each TDF domain. TDF domains and barrier and facilitators were then compared across the different conditions and PA types.ResultsThirty articles were included. 'Environmental context and resources', 'social influences' and 'beliefs about consequences' are the most prominent TDF domains for both barriers and facilitators, whereas 'beliefs about capabilities' and 'emotion' are prominent domains specifically for barriers, and 'reinforcement' and 'behavioural regulation' for facilitators. These domains were consistent across conditions and most PA types.ConclusionsThese findings can inform future intervention development. Healthcare professionals may benefit from prioritising addressing the more prominent TDF domains to enhance patients' PA.

IntroductionPhysical activity (PA) promotion is a core element of musculoskeletal rehabilitation. Many people with musculoskeletal conditions do not meet PA guidelines, such as those provided by the World Health Organization (WHO). This study aimed to explore the level of awareness and perspectives on the WHO PA guidelines among people with musculoskeletal conditions and identify how patients can be supported with PA in clinical practice.MethodsA mixed-method cross-sectional survey was conducted using a uniquely developed questionnaire, which was disseminated to patients attending outpatient physiotherapy or occupational therapy appointments. The questionnaire collected data on participant characteristics, awareness and perspectives on the WHO guidelines and suggestions for supporting patients with PA in clinical practice. Descriptive statistics and content analysis were used to analyse the quantitative and qualitative data respectively.ResultsOne-hundred and two responses were included in the analysis. Forty-two percent of respondents were aware of the guidelines, 50% knew why they existed and 53% felt they were achievable. Perspectives varied, ranging from the guidelines being positive and aiding motivation to being unachievable. Some respondents felt an individualised approach is required. Suggestions for supporting patients with PA included facilitating social support, providing education, exercise groups and personalised advice, and signposting to community services.ConclusionThere is limited awareness of the WHO PA guidelines and a variety of perspectives on the guidelines among patients with musculoskeletal conditions. There is a need to enhance the promotion of the guidelines in clinical practice, whilst considering local context and individual patient's circumstances.

OBJECTIVE:This study aimed to understand the impact of pain management programmes, focusing on the unwanted effects and their influence on patients' long-term use of self-management strategies.DESIGN:Qualitative study.SETTING:Specialist musculoskeletal hospital in North London, England.PARTICIPANTS:Patients with chronic musculoskeletal pain that have completed a pain management programme.INTERVENTION:Multidisciplinary pain management programmes.MAIN MEASURES:Data were collected regarding patients' experiences and unwanted effects from the pain management programme using semi-structured interviews. Data were analysed using thematic analysis.RESULTS:Fourteen participant interviews were included in the analysis (median age 54 years, 12 females). Four themes were generated from the data: Benefits and burdens, Pain management programme and real life, Social support and Healthcare interventions. Unwanted effects included heightened anxiety related to negative interactions with peers, being in a new environment, worries about ability to cope with the programme, social anxiety from being in a group, the strain on families due to participants being away from home and a sense of abandonment at end of the programme. Burdens associated with implementing pain management strategies were identified, including the emotional burden of imposing their self-management on close family and competing demands with time and energy spent on self-management at the expense of work or home commitments.CONCLUSIONS:Pain management programmes have an important role in helping patients to learn how to self-manage chronic pain. Their unwanted effects and the treatment burdens associated with long-term self-management may be an important consideration in improving the longevity of their beneficial effects.

BACKGROUND:Understanding the short-term complication profile following unicompartmental knee arthroplasty (UKA) versus total knee arthroplasty (TKA) can improve surgical decision-making and patient outcomes. This study aimed to determine if the difference in risk of 30-day morbidity and mortality between UKA and TKA varied based on patient age. METHODS:This retrospective study of a national quality improvement database using data from 2014 to 2020 included 403,342 patients undergoing UKA (n = 12,324) or TKA (n = 391,018). A generalized additive model evaluated nonlinear relationships between primary outcome and predictors (age, procedure, and procedure × age interaction) using a 1:5 UKA to TKA matched sample. Probabilities and odds ratios (95% confidence interval [CI]) estimated the relative risk of complications by age. RESULTS:In the generalized additive model, TKA patients relative to UKA had 1.30 odds (95% CI 1.19 to 1.43, P < 0.001) of 30-day morbidity and mortality. There was a significant nonlinear relationship between age and primary outcome (P = 0.02), such that the odds were lowest at younger ages. They increased slowly until the age of 65 years, when the slope became steeper. The interaction terms for age and procedure were not significant (P = 0.30). The 30-day probability for short-term complications of a 65-, 75-, and 85-year-olds undergoing UKA was 2.1% (95% CI 1.8 to 2.3), 2.4% (95% CI 2.0 to 2.8), and 3.2% (95% CI 2.3 to 4.1), respectively. The probability of a 65-, 75-, and 85-year-old undergoing TKA was 2.9% (95% CI 2.7 to 3.0), 3.6% (95% CI 3.3 to 3.8), and 5.5% (95% CI 4.7 to 6.3), respectively. CONCLUSIONS:Patients undergoing UKA had a quantifiable lower likelihood of morbidity or mortality than TKA at all ages. These data can provide individualized risk for UKA and TKA across the age spectrum and could be helpful in counseling patients regarding their perioperative risk. LEVEL OF EVIDENCE:III (retrospective comparative study).

Discharge destination impacts costs and perioperative planning for primary total knee (TKA) or hip arthroplasty (THA). The purpose of this study was to create a tool to predict discharge destination in contemporary patients. Models were developed using more than 400,000 patients from the National Surgical Quality Improvement Program database. Models were compared with a previously published model using area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). AUC on patients with TKA was 0.729 (95% confidence interval [CI]: 0.719 to 0.738) and 0.688 (95% CI: 0.678 to 0.697) using the new and previous models, respectively. AUC on patients with THA was 0.768 (95% CI: 0.758 to 0.778) and 0.726 (95% CI: 0.714 to 0.737) using the new and previous models, respectively. DCA showed substantially improved net clinical benefit. The new models were integrated into a web-based application. This tool enhances clinical decision making for predicting discharge destination following primary TKA and THA. (Journal of Surgical Orthopaedic Advances 32(4):252-258, 2023).

PURPOSE:Faculty feedback on trainees is critical to guiding trainee progress in a competency-based medical education framework. The authors aimed to develop and evaluate a Natural Language Processing (NLP) algorithm that automatically categorizes narrative feedback into corresponding Accreditation Council for Graduate Medical Education Milestone 2.0 subcompetencies.METHOD:Ten academic anesthesiologists analyzed 5,935 narrative evaluations on anesthesiology trainees at 4 graduate medical education (GME) programs between July 1, 2019, and June 30, 2021. Each sentence (n = 25,714) was labeled with the Milestone 2.0 subcompetency that best captured its content or was labeled as demographic or not useful. Inter-rater agreement was assessed by Fleiss' Kappa. The authors trained an NLP model to predict feedback subcompetencies using data from 3 sites and evaluated its performance at a fourth site. Performance metrics included area under the receiver operating characteristic curve (AUC), positive predictive value, sensitivity, F1, and calibration curves. The model was implemented at 1 site in a self-assessment exercise.RESULTS:Fleiss' Kappa for subcompetency agreement was moderate (0.44). Model performance was good for professionalism, interpersonal and communication skills, and practice-based learning and improvement (AUC 0.79, 0.79, and 0.75, respectively). Subcompetencies within medical knowledge and patient care ranged from fair to excellent (AUC 0.66-0.84 and 0.63-0.88, respectively). Performance for systems-based practice was poor (AUC 0.59). Performances for demographic and not useful categories were excellent (AUC 0.87 for both). In approximately 1 minute, the model interpreted several hundred evaluations and produced individual trainee reports with organized feedback to guide a self-assessment exercise. The model was built into a web-based application.CONCLUSIONS:The authors developed an NLP model that recognized the feedback language of anesthesiologists across multiple GME programs. The model was operationalized in a self-assessment exercise. It is a powerful tool which rapidly organizes large amounts of narrative feedback.

Background Hyponatremia and hypernatremia, as conventionally defined (<135 mEq/L and >145 mEq/L, respectively), are associated with increased perioperative morbidity and mortality. However, the effects of subtle deviations in serum sodium concentration within the normal range are not well-characterized. Objective The purpose of this analysis is to determine the association between borderline hyponatremia (135-137 mEq/L) and hypernatremia (143-145 mEq/L) on perioperative morbidity and mortality. Methods A retrospective cohort study was performed using data from the American College of Surgeons National Surgical Quality Improvement Program database. This database is a repository of surgical outcome data collected from over 600 hospitals across the United States. The National Surgical Quality Improvement Program database was queried to extract all patients undergoing elective, noncardiac surgery from 2015 to 2019. The primary predictor variable was preoperative serum sodium concentration, measured less than 5 days before the index surgery. The 2 primary outcomes were the odds of morbidity and mortality occurring within 30 days of surgery. The risk of both outcomes in relation to preoperative serum sodium concentration was modeled using weighted generalized additive models to minimize the effect of selection bias while controlling for covariates. Results In the overall cohort, 1,003,956 of 4,551,726 available patients had a serum sodium concentration drawn within 5 days of their index surgery. The odds of morbidity and mortality across sodium levels of 130-150 mEq/L relative to a sodium level of 140 mEq/L followed a nonnormally distributed U-shaped curve. The mean serum sodium concentration in the study population was 139 mEq/L. All continuous covariates were significantly associated with both morbidity and mortality (P<.001). Preoperative serum sodium concentrations of less than 139 mEq/L and those greater than 144 mEq/L were independently associated with increased morbidity probabilities. Serum sodium concentrations of less than 138 mEq/L and those greater than 142 mEq/L were associated with increased mortality probabilities. Hypernatremia was associated with higher odds of both morbidity and mortality than corresponding degrees of hyponatremia. Conclusions Among patients undergoing elective, noncardiac surgery, this retrospective analysis found that preoperative serum sodium levels less than 138 mEq/L and those greater than 142 mEq/L are associated with increased morbidity and mortality, even within currently accepted “normal” ranges. The retrospective nature of this investigation limits the ability to make causal determinations for these findings. Given the U-shaped distribution of risk, past investigations that assume a linear relationship between serum sodium concentration and surgical outcomes may need to be revisited. Likewise, these results question the current definition of perioperative eunatremia, which may require future prospective investigations.

BACKGROUNDIn 2018, a set of entrustable professional activities (EPAs) and procedural skills assessments were developed for anesthesiology training, but they did not assess all the Accreditation Council for Graduate Medical Education (ACGME) milestones. The aims of this study were to (1) remap the 2018 EPA and procedural skills assessments to the revised ACGME Anesthesiology Milestones 2.0, (2) develop new assessments that combined with the original assessments to create a system of assessment that addresses all level 1 to 4 milestones, and (3) provide evidence for the validity of the assessments.METHODSUsing a modified Delphi process, a panel of anesthesiology education experts remapped the original assessments developed in 2018 to the Anesthesiology Milestones 2.0 and developed new assessments to create a system that assessed all level 1 through 4 milestones. Following a 24-month pilot at 7 institutions, the number of EPA and procedural skill assessments and mean scores were computed at the end of the academic year. Milestone achievement and subcompetency data for assessments from a single institution were compared to scores assigned by the institution's clinical competency committee (CCC).RESULTSNew assessment development, 2 months of testing and feedback, and revisions resulted in 5 new EPAs, 11 nontechnical skills assessments (NTSAs), and 6 objective structured clinical examinations (OSCEs). Combined with the original 20 EPAs and procedural skills assessments, the new system of assessment addresses 99% of level 1 to 4 Anesthesiology Milestones 2.0. During the 24-month pilot, aggregate mean EPA and procedural skill scores significantly increased with year in training. System subcompetency scores correlated significantly with 15 of 23 (65.2%) corresponding CCC scores at a single institution, but 8 correlations (36.4%) were <30.0, illustrating poor correlation.CONCLUSIONSA panel of experts developed a set of EPAs, procedural skill assessment, NTSAs, and OSCEs to form a programmatic system of assessment for anesthesiology residency training in the United States. The method used to develop and pilot test the assessments, the progression of assessment scores with time in training, and the correlation of assessment scores with CCC scoring of milestone achievement provide evidence for the validity of the assessments.

INTRODUCTION:While civilian opioid prescriptions have seen a dramatic decline in recent years, there are few studies investigating trends in opioid prescription in the active duty military population. We evaluated oral opioid prescribing patterns to active duty military personnel in the Military Health System (MHS) from 2017 to 2020 to determine the incidence of opioid prescriptions as well as demographic and military-specific risk factors for receiving an oral opioid prescription. METHODS:The MHS Data Repository was queried from 2017 to 2020 to identify all outpatient oral opioid prescriptions to active duty military personnel in August of each year as well as demographic information on the study population. Data were evaluated in a logistic regression model, and ORs of receiving an oral opioid prescription were calculated for each factor. RESULTS:The proportion of active duty military personnel receiving an oral opioid prescription declined from 2.71% to 1.26% (53% relative reduction) over the study period. Within the logistic regression model, female military personnel were significantly more likely to receive opioid prescriptions compared with men, and there was a stepwise increase in likelihood of an opioid prescription with increasing age. Army and Marine personnel, personnel without a history of military deployment and those stationed within the continental USA were significantly more likely to receive an opioid prescription. DISCUSSION:The substantial decrease in oral opioid prescriptions to active duty military personnel mirrors data published in the civilian community. The identified risk factors for receiving an opioid prescription may be potential targets for future interventions to further decrease prescribing.

BACKGROUND:Hemorrhage is a major cause of preventable death worldwide, and early identification can be lifesaving. Pulse wave contour analysis has previously been used to infer hemodynamic variables in a variety of settings. We hypothesized that pulse arrival time (PAT), a form of pulse wave contour analysis which is assessed via electrocardiography (ECG) and photoplethysmography (PPG), is associated with hemorrhage volume.METHODS:Yorkshire-Cross swine were randomized to hemorrhage (30 mL/kg over 20 minutes) vs. control. Continuous ECG and PPG waveforms were recorded with a novel monitoring device, and algorithms were developed to calculate PAT and PAT variability throughout the respiratory cycle, termed "PAT index" or "PAT_I." Mixed effects models were used to determine associations between blood loss and PAT and between blood loss and PAT_I to account for clustering within subjects and investigate inter-subject variability in these relationships.RESULTS:PAT and PAT_I data were determined for ∼150 distinct intervals from five subjects. PAT and PAT_I were strongly associated with blood loss. Mixed effects modeling with PAT alone was substantially better than PAT_I alone (R2 0.93 vs. 0.57 and Akaike information criterion (AIC) 421.1 vs. 475.5, respectively). Modeling blood loss with PAT and PAT_I together resulted in slightly improved fit compared to PAT alone (R2 0.96, AIC 419.1). Mixed effects models demonstrated significant inter-subject variability in the relationships between blood loss and PAT.CONCLUSIONS:Findings from this pilot study suggest that PAT and PAT_I may be used to detect blood loss. Because of the simple design of a single-lead ECG and PPG, the technology could be packaged into a very small form factor device for use in austere or resource-constrained environments. Significant inter-subject variability in the relationship between blood loss and PAT highlights the importance of individualized hemodynamic monitoring.

Introduction:Remotely delivered pain management programmes have been offered in place of in-person programmes by many chronic pain services since the onset of the COVID-19 pandemic. There is a lack of evidence regarding the acceptability of these programmes. In this evaluation, we have explored patients' acceptability of a remotely delivered pain management programme for patients with persistent musculoskeletal pain.Methods:Qualitative data were collected using focus groups with participants who had previously attended the remote pain management programme. Data were analysed using abductive analysis.Results:Three focus groups were conducted with a total of 13 participants. The programmme was either entirely acceptable, had some acceptable components or was not acceptable to patients. Factors leading to the programme being acceptable include learning to manage pain from home, receiving high quality care from home, enhancing the potential of rehabilitation using technology, enabling attendance on a pain management programme from home, overcoming social distancing requirements of COVID-19 using technology, and virtual peer support. Factors leading to the programme not being acceptable include having an inappropriate home environment for virtual therapy, communication challenges with virtual therapy, technological issues and concerns regarding the quality of care.Conclusions:There is a spectrum of acceptability with respect to the remote programme. The factors that influence this are dynamic, individual and situational. Hybrid programmes have the potential to enhance access to pain management programmes and improve patient experience and programme outcomes in the future.

The Yorkshire-cross swine model is a valuable translational model commonly used to study cardiovascular physiology and response to insult. Although the effects of vasoactive medications have been well described in healthy swine, the effects of these medications during hemorrhagic shock are less studied. In this study, we sought to expand the utility of the swine model by characterizing the hemodynamic changes that occurred after the administration of commonly available vasoactive medications during euvolemic and hypovolemic states. To this end, we anesthetized and established femoral arterial, central venous, and pulmonary arterial access in 15 juvenile Yorkshire-cross pigs. The pigs then received a series of rapidly metabolized but highly vasoactive medications in a standard dosing sequence. After completion of this sequence, each pig underwent a 30-mL/kg hemorrhage over 10 min, and the standard dosing sequence was repeated. We then used standard statistical techniques to compare the effects of these vasoactive medications on a variety of hemodynamic parameters between the euvolemic and hemorrhagic states. All subjects completed the study protocol. The responses in the hemorrhagic state were often attenuated or even opposite of those in the euvolemic state. For example, phenylephrine decreased the mean arterial blood pressure during the euvolemic state but increased it in the hemorrhagic state. These results clarify previously poorly defined responses to commonly used vasoactive agents during the hemorrhagic state in swine. Our findings also demonstrate the need to consider the complex and dynamic physiologic state of hemorrhage when anticipating the effects of vasoactive drugs and planning study protocols.

Background: The COVID-19 pandemic interrupted the delivery of face-to-face pain services including pain management programmes in the United Kingdom with considerable negative impact on patients with chronic musculoskeletal pain. We aimed to develop and implement a remotely delivered pain management programme (PMP) using video-conferencing technology that contains all the core components of a full programme: the ‘virtual PMP’ (vPMP). By reporting on the process of this development, we endeavour to help address the paucity of literature on the development of remote pain management programmes. Methods: The vPMP was developed by an inter-disciplinary group of professionals as a quality improvement (QI) project. The Model for Improvement Framework was employed with patient involvement at the design phase and at subsequent improvements. Improvement was measured qualitatively with frequent and repeated qualitative data collection leading to programme change. Quantitative patient demographic comparisons were made with a patient cohort who had been on a face-to-face PMP pathway. Results: Sixty-one patients on the PMP waiting list were contacted and 43 met the criteria for the programme. Fourteen patients participated in three vPMP cycles. Patient involvement and comprehensive stakeholder consultation were essential to a robust design for the first vPMP. Continued involvement of patient partners during the QI process led to rapid resolution of implementation problems. The most prominent issues that needed action were technical challenges including training needs, participant access to physical and technological resources, participant fatigue and concerns about adequate communication and peer support. Conclusion: This report demonstrates how a remotely delivered PMP, fully in line with national guidance, was rapidly developed and implemented in a hospital setting for patients with chronic musculoskeletal pain. We also discuss the relevance of our findings to the issues of cost, patient experience, patient preferences and inequities of access in delivering telerehabilitation for chronic pain.

Introduction The Accreditation Council for Graduate Medical Education (ACGME) offers descriptions of competencies and milestones but does not provide standardized assessments to track trainee competency. Entrustable professional activities (EPAs) and special assessments (SAs) are emerging methods to assess the level of competency obtained by regional anesthesiology and acute pain medicine (RAAPM) fellows. Methods A panel of RAAPM physicians with experience in education and competency assessment and one medical student were recruited to participate in a modified Delphi method with iterative rounds to reach consensus on: a list of EPAs, SAs, and procedural skills; detailed definitions for each EPA and SA; a mapping of the EPAs and SAs to the ACGME milestones; and a target level of entrustment for graduating US RAAPM fellows for each EPA and procedural skill. A gap analysis was performed and a heat map was created to cross-check the EPAs and SAs to the ACGME milestones. Results Participants in EPA and SA development included 19 physicians and 1 medical student from 18 different programs. The Delphi rounds yielded a final list of 23 EPAs, a defined entrustment scale, mapping of the EPAs to ACGME milestones, and graduation targets. A list of 73 procedural skills and 7 SAs were similarly developed. Discussion A list of 23 RAAPM EPAs, 73 procedural skills, and 7 SAs were created using a rigorous methodology to reach consensus. This framework can be utilized to help assess RAAPM fellows in the USA for competency and allow for meaningful performance feedback.

Article| August 2022 Using Big Data to Analyze ASA's Twitter Presence: @ASALifeline Engagement Depends on Tweet Topic and Influencers Gregory J. Booth, MD; Gregory J. Booth, MD Search for other works by this author on: This Site PubMed Google Scholar Nolan Martin, BS; Nolan Martin, BS Search for other works by this author on: This Site PubMed Google Scholar Henry DeYoung, MD; Henry DeYoung, MD Search for other works by this author on: This Site PubMed Google Scholar Trevor Elam, MD; Trevor Elam, MD Search for other works by this author on: This Site PubMed Google Scholar Scott Hughey, MD; Scott Hughey, MD Search for other works by this author on: This Site PubMed Google Scholar A. Steven Bradley, MD A. Steven Bradley, MD Search for other works by this author on: This Site PubMed Google Scholar ASA Monitor August 2022, Vol. 86, 32–33. https://doi.org/10.1097/01.ASM.0000855696.55126.70 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Cite Icon Cite Get Permissions Search Site Citation Gregory J. Booth, Nolan Martin, Henry DeYoung, Trevor Elam, Scott Hughey, A. Steven Bradley; Using Big Data to Analyze ASA's Twitter Presence: @ASALifeline Engagement Depends on Tweet Topic and Influencers. ASA Monitor 2022; 86:32–33 doi: https://doi.org/10.1097/01.ASM.0000855696.55126.70 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll PublicationsASA Monitor Search Advanced Search Topics: big data Twitter is a powerful tool for ASA (@ASALifeline) and has the power to drive substantial change in our field, such as improving engagement in conferences and enhancing resident physician recruitment (Anesth Analg 2020;130:333-40; ASA Monitor 2021;85:40). It is important to analyze social media strategies to assess whether an individual or organization is providing value through their messaging. To identify topics ASA members value, who ASA's influencers are, and areas for potential ASA audience growth, we explored whether specific tweet topics and the society's social network structure impact tweet engagement. How can we analyze topics from thousands of ASA tweets? In the era of big data, we often characterize data as structured or unstructured. Structured data, such as patient risk factors, demographic variables, or outcomes, drives most traditional statistics we've learned in our evidence-based medicine curricula and is the engine for the vast majority of ongoing... You do not currently have access to this content.

Murine translational models are an important tool to understand pain pathophysiology. One procedure used frequently in murine research is the sciatic nerve block. This study sought to demonstrate the use of ultrasound-guided sciatic nerve block in a cadaveric murine model. A total of 40 injections were performed in 20 Sprague-Dawley male 18-month-old rat cadavers. Necropsy was performed to identify staining of the sciatic nerve. Staining with methylene blue occurred in 40 of 40 ultrasound-guided injections. The extremely accurate nature of this block under ultrasound guidance is favorable for future translational studies in rats undergoing sciatic nerve blocks. This method may represent a significant improvement in current methods.

This systematic review and meta-analysis investigated the effectiveness of physical activity (PA) and sedentary behavior (SB) interventions on PA and SB levels in people with persistent musculoskeletal pain. We explored the effectiveness of behavior change techniques (BCTs), the use of behavior change theory and non-PA/SB outcomes. Randomized controlled trials of PA or SB interventions for people with persistent musculoskeletal pain were eligible. Twenty-three studies were included. Quality of evidence was assessed using the GRADE approach. Meta-analysis demonstrated a small effect for PA post-intervention (Hedge's g = .321, CI .136-.507, P = .001, very low-quality evidence). There was no effect for longer-term follow-up PA (low quality evidence) or SB outcomes (very low-quality evidence). There was a small effect for studies with low risk-of-bias at longer-term follow-up PA. Self-report PA outcomes, PA and education interventions, non-self-selected PA, a combination of supervised and unsupervised PA and a combination of individual and group-based interventions had larger effects. Heterogeneity was moderate to considerable. Risk-of-bias, assessed using Cochrane risk-of-bias tool (version two), was generally low. Five promising BCTs were identified: "adding objects to the environment," "goal setting (outcome)," "action planning," "monitoring outcome(s) of behaviour by others without feedback" and "feedback on outcome(s) of behaviour." In conclusion, there is evidence for a modest benefit for PA interventions immediately post-intervention, however the quality of evidence is very low. There was no evidence for longer-term follow-up PA or SB. Higher quality studies of PA and SB interventions that use objective measures are needed. PROSPERO registration: CRD42020180260. Perspective: This review investigated the effects of physical activity and sedentary behavior interventions on physical activity and sedentary behavior levels in people with persistent musculoskeletal pain. Current evidence shows a modest benefit for interventions on physical activity post-intervention but not at longer-term follow-up or on sedentary behavior at any time-point, however quality of evidence is low to very low. (C) 2021 by United States Association for the Study of Pain, Inc.

Purpose: To develop a machine-learning algorithm and clinician-friendly tool predicting the likelihood of prolonged opioid use (>90 days) following hip arthroscopy. Methods: The Military Data Repository was queried for all adult patients undergoing arthroscopic hip surgery between 2012 and 2017. Demographic, health history, and prescription records were extracted for all included patients. Opioid use was divided into preoperative use (30-365 days before surgery), perioperative use (30 days before surgery through 14 days after surgery), postoperative use (14-90 days after surgery), and prolonged postoperative use (90-365 days after surgery). Six machine-learning algorithms (Naive Bayes, Gradient Boosting Machine, Extreme Gradient Boosting, Random Forest, Elastic Net Regularization, and artificial neural network) were developed. Area under the receiver operating curve and Brier scores were calculated for each model. Decision curve analysis was applied to assess clinical utility. Local-Interpretable Model-Agnostic Explanations were used to demonstrate factor weights within the selected model. Results: A total of 6,760 patients were included, of whom 2,762 (40.9%) filled at least 1 opioid prescription >90 days after surgery. The artificial neural network model showed superior discrimination and calibration with area under the receiver operating curve = 0.71 (95% confidence interval 0.68-0.74) and Brier score = 0.21 (95% confidence interval 0.20-0.22). Postsurgical opioid use, age, and preoperative opioid use had the most influence on model outcome. Lesser factors included the presence of a psychological comorbidity and strong history of a substance use disorder. Conclusions: The artificial neural network model shows sufficient validity and discrimination for use in clinical practice. The 5 identified factors (age, preoperative opioid use, postoperative opioid use, presence of a mental health comorbidity, and presence of a preoperative substance use disorder) accurately predict the likelihood of prolonged opioid use following hip arthroscopy.