Psychosocial Factors, Lifestyle and Central Pain Processing as Potential Predictors of Outcome for Rotator Cuff Repair

Overview

The influence of modifiable psychosocial and lifestyle factors and the role of central pain processing (CPP) on outcome after rotator cuff repair (RCR) is not well enough established to formulate holistic prognosis. Modern pain neuroscience emphasises to explain musculoskeletal shoulder pain biopsychosocially, which seems short when looking at the yearly RCR increase. This study will explore modifiable psychosocial and lifestyle factors and CPP as potential predictors for outcome after RCR.

Shoulder pain is the third most common musculoskeletal disorder seen in primary care with low recovery rates (50-60%) 12 to 18 months post onset. Rotator cuff (RC) disorders are the most common amongst shoulder pain patients with a life-time prevalence of around 70%. There is a lack of consensus concerning the cause of shoulder pain, as many people present with structural changes of their RC, yet they do not suffer pain. Reports from the United States acknowledge that only one third of RC lesions are symptomatic. RC degeneration measured in cadavers, increases rapidly from the age of 50 to 55, peaking at 80 years. Contrary to this observed increasing mechanistic change, the pain curve from the age of 65 onwards. This decrease in pain implies that shoulder pain is not solely based upon the presence of a RC tear, or other underlying structural changes. Patients who demonstrate structural changes of their RC, are still predominantly treated using biomedical reasoning. There was a reported 270,000 annual surgeries in the USA and an increase of 204% in rotator cuff repairs (RCR) between 1998 and 2011 in Finland. Satisfactory outcomes ranged from 38% to 95%. Biomedical prognostic indicators dominate the orthopaedic research on outcomes post RCR. Biomedical factors include; arm function (e.g. muscle strength), radiological findings (e.g. tear size) or demographics (e.g. age). This assertion was backed by a systematic review and meta-analysis regarding prognosis post RCR, where mainly anatomical and functional shoulder factors were analysed. Despite the reliance on biomedical indicators, there is a growing body of evidence about the impact of psychosocial factors on persistent shoulder pain, and on outcomes after RCR. The biopsychosocial model first described by Engel in the 1970's incorporates multiple dimensions and explains illness or disease based upon biomedical, psychological and social determinants of health. The perception of high job demand, poor social support, baseline high distress, maladaptive pain beliefs such as catastrophic thinking and pain self-efficacy can lead to persistent shoulder pain and disability. The absence of psychological distress is also associated with improved self-efficacy ("the capacity to produce important effects"), and lower levels of pain and disability. However, studies on the influence of psychosocial factors post RCR, demonstrate weak interactions. Patients with existing preoperative psychological conditions like depression and anxiety or cognitive psychological factors like pain catastrophizing and kinesiophobia, and psychological distress demonstrate higher pre-operative pain levels. High patients' expectations of a positive outcome post RCR show independent and strong associations to satisfactory outcomes after RCR, measured in pain and disability, and performance at one-year post-op. However, it is unclear which circumstances lead to high or low expectations and how one should measure these. Low expectations in conservative treatments like physiotherapy, can be influenced by the patients' biomedical oriented attitudes and beliefs towards pain and disability. High expectations on outcome post RCR may be further driven by the failure of conservative treatments (e.g. Physiotherapy). Sleep disturbance is highly prevalent in rotator cuff related shoulder pain patients and shoulder pain was found to be a strong predictor for sleep disturbance. RCR seems to reduce this vicious interplay between pain and sleep as findings demonstrate an overall post RCR improvement of sleep quality. The same study did not find any predictive power for insomnia on outcome post RCR. The relationship between CPP measures such as central sensitisation (CS), or quantitative sensory testing (QST) and prolonged shoulder pain have been established. To conclude, in the literature there is a lack of knowledge about modifiable psychosocial and lifestyle factors and CPP for predicting outcome after RCR. Clinicians need an improved explanatory model to predict successful outcomes post RCR. Neither the local tissue pathology-pain model nor the growing knowledge about local biochemical changes in the tendons, sufficiently describe the relationship between tissue changes and perceived shoulder pain. There is insufficient understanding to what extent cognitive psychological factors like pain catastrophizing, high perceived stress or low self-efficacy may influence outcome after RCR and whether or not they drive high or low patients' expectations (psychosocial factor) for surgery. The role of sleep on outcome after RCR remains obscure. Finally, the association of CPP with prolonged recovery post RCR is unknown. This study aims to support the understanding of psychosocial factors and their influence on outcome after RCR. The investigators hypothesise that psychosocial factors, lifestyle factors and CPP do play a role in individual prognosis for outcome after RCR. If modifiable psychosocial or lifestyle related factors such as patients' expectations on surgery, catastrophic pain thinking, high perceived stress, altered injury perceptions, sleep disturbance or altered central pain processing are identified as predictors for post RCR outcome, clinicians might tailor treatment and potentially patient selection for RCR based upon improved factors and hypothetically reduce the number of persistent shoulder pain patients one year after onset. This study aims to answer the following questions: 1. Is there an association between psychosocial factors including expectations, lifestyle factors such as sleep and CPP with outcome (quality of life, pain and disability) after RCR at 12 weeks and 12 months? 2. To what extent do these pre-interventional variables predict post-operative RCR outcome at 12 weeks and 12 months? Methods Study Design and setting The study will be implemented and reported in line with the STROBE statement for observational studies. Data are obtained monocentric in the shoulder and elbow surgery unit in the clinic of orthopaedic surgery and traumatology in alliance with the institute of therapy and rehabilitation of the acute care hospital, "Kantonsspital Winterthur" in Switzerland. The current research project will analyze data from three selected time points of this clinical routine of the RCR management; 2-3 weeks preoperative (T1), 12 weeks postoperative (T2) and 12 months postoperative (T3). Data from January 2019 will be considered. Data collection will be stopped after the inclusion of 141 individual datasets with 12 months follow up, estimated to be completed in late Spring 2022. Demographic variables such as age, gender, and profession and comorbidities, including diabetes, rheumatological disease, cardiovascular disease, and neurological disease, will be registered. The investigators will use a mixed-effects regression model for repeated measures. This will have the power to detect a moderate effect size that is still clinically relevant (15% difference in WORC score) with confidence level α=0.5, (two-tailed) and a desired power of 90%. The required total sample size was calculated to be 125 subjects (Edland). Mixed models do not require complete datasets to produce accurate results, but the statistical analysts have accounted for potential attrition. Given an expected drop-out rate of approximately 12.5%, a total number of 141 patients is needed. The power is set at 90% to minimize the chance of making a type II error. Statistical Methods and Analysis Statistical analyses will be performed using RStudio. Level of significance is set at p = 0.05. Appropriate descriptive statistics will be performed. Measurements will take place at three time points in the perioperative management, as described above (T1 = at baseline 2-3 weeks prior to RCR, T2 = at 12 weeks post RCR and T3 = at 12 months post RCR as follow-up). The primary outcome (WORC) will be analysed using multilevel linear regression models for repeated (longitudinal) measures, using an unstructured covariance matrix. Dependent variables are the primary and secondary outcomes. Continuous secondary outcomes will be assessed in a similar way to the primary outcome. The models will be developed by stepwise reduction of the potential predictors (for, psychosocial factors, sleep and CPP). Categorical data (e.g. EQ-5D-5L) will be analysed using logistic models. For non-repeated continuous and binary measurements, ordinary linear regression and logistic models will be used, respectively. Six predictors as clustered variables will be studied. The psychosocial variables are: 1) expectation, 2) pain catastrophizing, 3) perceived stress, 4) illness perceptions; the lifestyle factor; 5) sleep and 6) central pain processing (see table 2 for more detail). Data security and management Data generation, transmission, storage and analysis within this project strictly follow Swiss legal requirements for data protection. The electronic data capture (EDC) software REDCap (www.project---redcap.org) will be used for data processing and management. Appropriate coded identification (e.g. pseudonymisation) is used in order to enter subject data into the database. The coding list of target data is saved in a secured folder on the hospital's server. Ethics The study underlies the principles of the Helsinki Declaration. Only data of patients who gave general consent to the hospital or informed written consent to the project will be considered for analysis. Ethical approval received January 2019 (ID 2018-02089) by the Ethical Committee of the Canton of Zurich, Switzerland.