Reliability measures of subcutaneous pressure pain threshold measurements: A proposed method of assessing painful musculoskeletal disorders.

摘要

Background: Pressure algometry is a widely used method aiming to investigate deep tissue mechanical pain threshold in painful musculoskeletal disorders. Considering from the literature the input of skin and subcutaneous tissue in the determination of pressure pain threshold, and the distinctive role in clinical setting of the subcutaneous pressure threshold measurement (sPPT), it becomes necessary to investigate the reliability of the sPPT measurements. This study examines the short and longer-term intra-examiner reliability of sPPT measurements. Methods: Thirty subjects were examined at 3 pre-determined time intervals, in various parts of the body, by the same examiner in the same clinical setting. Short (between days) and longer-term (after a week) test-retest reliability was investigated. A number of statistical procedures was computed: ICC, ANOVA, standard error of measurement (SEM), smallest detectable difference (SDD) and confirmatory scatterplots. Results: The ICC statistic reached good to excellent levels for both types of reliability (0.70 – 0.97). ANOVA produced non-significant differences at all measurements. SEM gave a satisfactory overall mean value of 6.07 kPa (short-term) for all measuring sites (range: 3.2-10.1) and similarly for the longer-term reliability (Mean=6.2, range: 3.1-11.2). SDD were satisfactory in the majority of the measurements [short: Mean=11.76, range: 5.9-20, longer: Mean=12.0, range: 6.5-22] but relatively high in some measuring sites, nevertheless fully acceptable and safely within the pressure algometry limits as defined in the literature. Conclusions: Subcutaneous pressure threshold measurement is a reliable to reproduce with stable results procedure, either for short or longer periods of time (from 1 to 7 days), across the whole body (upper – lower body), by the same examiner. Its fluctuation in absolute values is within the literature limits of deep pressure algometry.