Sex Differences in Pain Sensitivity in a Dutch Cohort: Cross-Sectional and Web-Based Multidimensional Study.

BACKGROUND: Sex is an important factor influencing the development and treatment of chronic pain, but the extent of its influence is still unclear. Other demographic factors as well as nonpharmacological interventions might influence pain sensitivity differently in men and women. OBJECTIVE: In this study, we aimed to investigate the influence of sex and other demographic, lifestyle, behavioral, clinical, and environmental factors on pain sensitivity in the Dutch population. Different films were used to investigate how they would impact pain sensitivity and what influence sex and other variables have on the effect of this simple intervention. METHODS: We performed a study consisting of 2 parts: (1) a cross-sectional research to investigate pain sensitivity differences between men and women and the influence of other demographic variables on the pain sensitivity in a Dutch cohort and (2) an internet intervention study to determine whether a short film could skew pain sensitivity. RESULTS: All respondents filled in a web-based demographic questionnaire and were randomized into 4 groups. The control group filled in the Pain Sensitivity Questionnaire without watching a preliminary film. A cross-sectional analysis was performed in the control group (n=1746). The other 3 groups watched short films: one group watched a film with scenes of nature (n=2650), another group watched a film on laughing people (n=2735), and the last group watched a film on physically painful events (n=2708). Immediately after the film viewing, participants were directed to the Pain Sensitivity Questionnaire to measure their pain sensitivity. The Pain Sensitivity Questionnaire score was stated as a mean per question on the numeric rating scale from 0-1. The cross-sectional study revealed no significant differences between men and women but showed male-female differences in the Pain Sensitivity Questionnaire when specific background factors were present. Watching a short film had a positive impact on the pain sensitivity of the respondents who had chronic pain, with a higher effect observed in female respondents. CONCLUSIONS: Scientists performing pain research need to account for factors that can influence the outcome of their study and be aware that these factors can be sex-dependent, and pain sensitivity should be analyzed accordingly. Even relatively small interventions such as watching a film can impact pain sensitivity, especially in respondents with current chronic pain. This effect can vary as well when different background factors are present. Our findings warrant further explorations of the possibilities that simple interventions bring for patients in personalized medicine. TRIAL REGISTRATION: Landelijk Trial Register NTR-new NL8182; https://onderzoekmetmensen.nl/en/trial/29537.

Development and Performance of a Web-Based Tool to Adjust Urine Toxicology Testing Frequency: Retrospective Study.

BACKGROUND: Several pain management guidelines recommend regular urine drug testing (UDT) in patients who are being treated with chronic opioid analgesic therapy (COAT) to monitor compliance and improve safety. Guidelines also recommend more frequent testing in patients who are at high risk of adverse events related to COAT; however, there is no consensus on how to identify high-risk patients or on the testing frequency that should be used. Using previously described clinical risk factors for UDT results that are inconsistent with the prescribed COAT, we developed a web-based tool to adjust drug testing frequency in patients treated with COAT. OBJECTIVE: The objective of this study was to evaluate a risk stratification tool, the UDT Randomizer, to adjust UDT frequency in patients treated with COAT. METHODS: Patients were stratified using an algorithm based on readily available clinical risk factors into categories of presumed low, moderate, high, and high+ risk of presenting with UDT results inconsistent with the prescribed COAT. The algorithm was integrated in a website to facilitate adoption across practice sites. To test the performance of this algorithm, we performed a retrospective analysis of patients treated with COAT between June 2016 and June 2017. The primary outcome was compliance with the prescribed COAT as defined by UDT results consistent with the prescribed COAT. RESULTS: 979 drug tests (867 UDT, 88.6%; 112 oral fluid testing, 11.4%) were performed in 320 patients. An inconsistent drug test result was registered in 76/979 tests (7.8%). The incidences of inconsistent test results across the risk tool categories were 7/160 (4.4%) in the low risk category, 32/349 (9.2%) in the moderate risk category, 28/338 (8.3%) in the high risk category, and 9/132 (6.8%) in the high+ risk category. Generalized estimating equation analysis demonstrated that the moderate risk (odds ratio (OR) 2.1, 95% CI 0.9-5.0; P=.10), high risk (OR 2.0, 95% CI 0.8-5.0; P=.14), and high risk+ (OR 2.0, 95% CI 0.7-5.6; P=.20) categories were associated with a nonsignificantly increased risk of inconsistency vs the low risk category. CONCLUSIONS: The developed tool stratified patients during individual visits into risk categories of presenting with drug testing results inconsistent with the prescribed COAT; the higher risk categories showed nonsignificantly higher risk compared to the low risk category. Further development of the tool with additional risk factors in a larger cohort may further clarify and enhance its performance.