The Role of Elbow Tender Point Examination in the Diagnosis of Lateral Epicondylitis.

OBJECTIVE: To quantify sensitivity and specificity of the tender points and demonstrate how variability in case definition impacts prevalence of lateral epicondylitis (LE). METHODS: Baseline data analyzed from 1216 workers from the WISTAH study, a multicenter prospective cohort study of upper extremity musculoskeletal disorders. All workers completed computerized questionnaires, structured interviews, and two independent physical examinations in accordance with an established protocol. RESULTS: The prevalence of LE differed based on case definition ranging from 4.7% to 12.1%. Sensitivity was low for tender points 1 to 4 ranging from 6.8% to 34.6%. Specificity was high for tender points 1 to 4 ranging from 95.2% to 97.9%. CONCLUSIONS: The prevalence of lateral epicondylitis differs markedly based on case definition used, ranging more than two-fold. Standardization of a case definition is essential to allow for comparisons across studies.

Opioid use: Case-control analyses of worker's compensation data.

OBJECTIVES: Working-age adults are disproportionately impacted by opioid misuse. Factors associated with opioid misuse in people with workers compensation (WC) claims are not well studied. WC in some states is a "captured" market making it a more efficient site for researching the opioids epidemic. A pilot study was conducted to identify factors associated with opioid use using a large WC insurer's claims in Utah. METHODS: This was a case-control study using a large WC insurer's database. We conducted secondary data analyses of a de-identified dataset originally obtained from the WC insurer. Cases were defined as claims with a morphine equivalent dose (MED)≥50 mg/d in the 30 days after the claim was filed while controls = 0 mg/d. RESULTS: A total of 76 patient's claims (28 cases and 48 controls) were included in the final data analyses. The majority of claimants were male (N = 50, 65.8 percent), worked full time (N = 58, 76.3 percent) and had a mean age of 37.0±11.4 years. The majority of controls filed medical only claims (N = 40, 83.3 percent) while the majority of cases filed indemnity claims (N = 19, 67.9 percent). Cases were prescribed a mean MED of 126.4 (SD = 93.3) within the first month after filing the claim. Most cases visited>3 medical providers (N = 13, 46.4 percent) in the first month after filing the claim while the majority of controls only visited one provider (N = 28, 58.3 percent). Remarkably, the mean number of providers visited within the first month for the cases was 3.8, which was 2-fold greater than the control group. Exploratory multivariate analyses showed that cases were 4.6 times more likely to have visited 2-3 medical providers (p = 0.025), and 41.8 times more likely to have visited more than three medical providers (p < 0.001). Cases had 3.6 higher odds of having been prescribed nonsteroidal anti-inflammatory prescription within the first month as compared to controls (p = 0.014). CONCLUSION: This pilot study found risk factors, some of which may be modifiable. We aim to conduct a large study using existing WC data to create a scoring system that identifies those claimants at higher risk of adverse opioid-related events that may have preventive applications at a systems-level.

The Association Between Cardiovascular Disease Risk Factors and Motor Vehicle Crashes Among Professional Truck Drivers.

OBJECTIVE: This study assesses relationships between the Framingham cardiovascular disease risk (CVD risk) score and prevalence of US Department of Transportation (DOT)-reportable crashes in commercial motor vehicle (CMV) drivers, after controlling for potential confounders. METHODS: Data were analyzed from CMV drivers (N = 797) in a large cross-sectional study. CVD risk was calculated for each driver. Adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) between CVD risk and DOT-reportable crashes were calculated. RESULTS: Drivers in the two highest CVD risk groups had significantly higher likelihood of crash (OR = 2.08, 95% CI = 1.20 to 3.63 and OR = 1.99, 95% CI = 1.05 to 3.77, respectively) after adjusting for confounders. There was a significant trend of increasing prevalence of crashes with an increasing CVD risk score (P = 0.0298). CONCLUSION: Drivers with a high CVD risk had a higher likelihood of a crash after controlling for confounders.