• Leticia Amaral Corrêa, Juliana Valentim Bittencourt, Arthur de Sá Ferreira, Felipe José Jandre Dos Reis, de Almeida Renato Santos RS 0000-0003-2148-334X Rehabilitation Science Postgraduation Program, Augusto Motta University Center (UNISUAM), Rio de Janei, and Leandro Alberto Calazans Nogueira.
• Rehabilitation Science Postgraduation Program, Augusto Motta University Center (UNISUAM), Rio de Janeiro, Brazil.
• Pain Pract. 2020 Jun 1; 20 (5): 462-470.

BackgroundThe assessment of painful areas through printed body charts is a simple way for clinicians to identify patients with widespread pain in primary care. However, there is a lack in the literature about a simple and automated method designed to analyze pain drawings in body charts in clinical practice.PurposeTo test the inter- and intra-rater reliabilities and concurrent validity of software (PainMAP) for quantification of pain drawings in patients with low back pain.MethodsThirty-eight participants (16 [42.10%] female; mean age 50.24 [11.54] years; mean body mass index 27.90 [5.42] kg/m2 ; duration of pain of 94.35 [96.11] months) with a current episode of low back pain were recruited from a pool of physiotherapy outpatients. Participants were instructed to shade all their painful areas on a body chart using a red pen. The body charts were digitized by separate raters using smartphone cameras and twice for one rater to analyze the intra-rater reliability. Both the number of pain sites and the pain area were calculated using ImageJ software (reference method). The PainMAP software used image processing methods to automatically quantify the data from the same digitized body charts.ResultsThe reliability analyses revealed that PainMAP has excellent inter- and intra-rater reliabilities to quantify the number of pain sites (intraclass correlation coefficient [ICC]2,1 : 0.998 [95% confidence interval (CI) 0.996 to 0.999]; ICC2,1 : 0.995 [95% CI 0.991 to 0.998]) and the pain area [ICC2,1 : 0.998 (95% CI 0.995 to 0.999); ICC2,1 : 0.975 (95% CI 0.951 to 0.987)], respectively. The standard error of the measurement was 0.22 (4%) for the number of pain sites and 0.03 cm2 (4%) for the pain area. The Bland-Altman analyses revealed no substantive differences between the 2 methods for the pain area (mean difference = 0.007 [95% CI -0.053 to 0.067]).ConclusionPainMAP software is reliable and valid for quantification of the number of pain sites and the pain area in patients with low back pain.© 2020 World Institute of Pain.

19 keywords...

hide…