The Reliability and Concurrent Validity of PainMAP Software for Automated Quantification of Pain Drawings on Body Charts of Patients With Low Back Pain.

Background: The 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 clinica...

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Publicado en:Pain Practice Vol. 20; no. 5; pp. 462 - 471
Autores principales: Corrêa, Leticia Amaral, Bittencourt, Juliana Valentim, Ferreira, Arthur de Sá, Reis, Felipe José Jandre dos, Almeida, Renato Santos, Nogueira, Leandro Alberto Calazans
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell Jun2020
Acceso en línea:Ver este registro en EBSCOhost
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        atl: The Reliability and Concurrent Validity of PainMAP Software for Automated Quantification of Pain Drawings on Body Charts of Patients With Low Back Pain.
      aug:
        au:
          Corrêa, Leticia Amaral
          Bittencourt, Juliana Valentim
          Ferreira, Arthur de Sá
          Reis, Felipe José Jandre dos
          Almeida, Renato Santos
          Nogueira, Leandro Alberto Calazans
        affil: Rehabilitation Science Postgraduation Program, Augusto Motta University Center (UNISUAM), Rio de Janeiro Brazil
      sug:
        subj:
          Interrater Reliability
          Intrarater Reliability
          Concurrent Validity
          Software
          Automation
          Low Back Pain Diagnosis
          Pain Measurement
          Human
          Male
          Female
          Middle Age
          Body Mass Index
          Disease Duration
          Low Back Pain Therapy
          Physical Therapy
          Outpatient Service
          Intraclass Correlation Coefficient
          Confidence Intervals
          Data Analysis, Statistical
          Middle Aged: 45-64 years
          Male
          Female
      ab: Background: The 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. Purpose: To test the inter‐ and intra‐rater reliabilities and concurrent validity of software (PainMAP) for quantification of pain drawings in patients with low back pain. Methods: Thirty‐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. Results: The 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]). Conclusion: PainMAP software is reliable and valid for quantification of the number of pain sites and the pain area in patients with low back pain.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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