Clinician and Patient-reported Outcomes Are Associated With Psychological Factors in Patients With Chronic Shoulder Pain.

Validated clinician outcome scores are considered less associated with psychosocial factors than patient-reported outcome measurements (PROMs). This belief may lead to misconceptions if both instruments are related to similar factors. We asked: In patients with chronic shoulder pain, what biopsychosocial factors are associated (1) with PROMs, and (2) with clinician-rated outcome measurements? All new patients between the ages of 18 and 65 with chronic shoulder pain from a unilateral shoulder injury admitted to a Swiss rehabilitation teaching hospital between May 2012 and January 2015 were screened for potential contributing biopsychosocial factors. During the study period, 314 patients were screened, and after applying prespecified criteria, 158 patients were evaluated. The median symptom duration was 9 months (interquartile range, 5.5-15 months), and 72% of the patients (114 patients) had rotator cuff tears, most of which were work injuries (59%, 93 patients) and were followed for a mean of 31.6 days (SD, 7.5 days). Exclusion criteria were concomitant injuries in another location, major or minor upper limb neuropathy, and inability to understand the validated available versions of PROMs. The PROMs were the DASH, the Brief Pain Inventory, and the Patient Global Impression of Change, before and after treatment (physiotherapy, cognitive therapy and vocational training). The Constant-Murley score was used as a clinician-rated outcome measurement. Statistical models were used to estimate associations between biopsychosocial factors and outcomes. Greater disability on the DASH was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale combined coefficient, 0.64; 95% CI, 0.25-1.03; p = 0.002) and social factors (language, professional qualification combined coefficient, -6.15; 95% CI, -11.09 to -1.22; p = 0.015). Greater pain on the Brief Pain Inventory was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale combined coefficient, 0.076; 95% CI, 0.021-0.13; p = 0.006). Poorer impression of change was associated with psychological factors (Hospital Anxiety and Depression Scale, Pain Catastrophizing Scale, Tampa Scale of Kinesiophobia coefficient, 0.93; 95% CI, 0.87-0.99; p = 0.026) and social factors (education, language, and professional qualification coefficient, 6.67; 95% CI, 2.77-16.10; p < 0.001). Worse clinician-rated outcome was associated only with psychological factors (Hospital Anxiety and Depression Scale (depression only), Pain Catastrophizing Scale, Tampa Scale of Kinesiophobia combined coefficient, -0.35; 95% CI, -0.58 to -0.12; p = 0.003). Depressive symptoms and catastrophizing appear to be key factors influencing PROMs and clinician-rated outcomes. This study suggests revisiting the Constant-Murley score. Level III, prognostic study

Event-related potential analyses via single-subject topographic classification.

Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research

Clinician and patient-reported outcomes are associated with psychological factors in chronic shoulder pain patients.

OBJECTIVE: Multiple factors are affecting outcomes after shoulder injuries and there is no general consensus on which are the most decisive. The research questions were: (1) In patients with chronic shoulder pain, what are the psychosocial and biological factors associated with patient-reported outcome measures? (2) What are the psychosocial and biological factors associated with clinician-rated outcome measures? MATERIAL/PATIENTS AND METHODS: In this retrospective cohort study, we collected the following biopsychosocial factors: biological (shoulder diagnosis category, Cumulative Illness Rating Scale (CIRS), Abbreviated Injury Scale (AIS) and INTERMED biological subscale), psychological (psychiatric comorbidity, Hospital Anxiety and Depression Scale (HADS), Pain Catastrophizing Scale (PCS), Tampa Scale of Kinesiophobia (TSK), and INTERMED psychological subscale) and Social (Native Language, educational level, professional qualification, and INTERMED social subscale). The patient-reported outcomes measures (PROMs) included the DASH, the Brief Pain Inventory (BPI), and Patient Global Impression of Change (PGIC). We used the Constant-Murley score as a clinician-rated outcome instrument. Linear and logistic regression models were used to estimate the association between these variables and outcomes. RESULTS: One hundred and fifty-eight patients (median age 47 years, 18% women) were included, predominantly suffering from rotator cuff tears (72%). Poor patient-reported outcomes are associated with psychological and social factors but not biological factors, where greater disability on the DASH was associated with psychological factors (HAD anxiety, Depression, PCS combined coefficient 0.64 [95% CI: 0.25, 1.03], P=0.002) and social factors (language, professional qualification combined coefficient-6.15 [-11.09, -1.22], P=0.015), greater pain on the BPI was associated with psychological factors (HAD anxiety, depression, PCS combined coefficient 0.076 [0.021, 0.13], P=0.006), and poorer impression of change was associated with psychological factors (HAD anxiety, depression, PCS, TSK coefficient 0.93 [0.87, 0.99], P=0.026) and social factors (education, language, and professional qualification coefficient 6.67 [2.77, 16.10], P<0.001). Similarly, worse clinician-rated outcomes were associated with psychological factors (HAD depression, PCS, TSK combined coefficient-0.35 [-0.58, -0.12], P=0.003). DISCUSSION - CONCLUSION: Psychological factors were associated with shoulder patient-reported and clinician-rated outcome instruments. Depressive symptoms, catastrophizing and the patient's social background appear to be key points requiring careful screening. This influence should be taken into account during outcome analysis