组内相关
医学
可靠性(半导体)
物理疗法
同时有效性
图表
置信区间
疼痛评估
有效性
疼痛管理
外科
统计
心理测量学
内科学
内部一致性
患者满意度
物理
功率(物理)
临床心理学
量子力学
数学
作者
Letícia Amaral Corrêa,Juliana Valentim Bittencourt,Arthur de Sá Ferreira,Felipe José Jandre dos Reis,Renato Santos de Almeida,Leandro Alberto Calazans Nogueira
出处
期刊:Pain Practice
[Wiley]
日期:2020-01-21
卷期号:20 (5): 462-470
被引量:8
摘要
Abstract 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/m 2 ; 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]; ICC 2,1 : 0.995 [95% CI 0.991 to 0.998]) and the pain area [ICC 2,1 : 0.998 (95% CI 0.995 to 0.999); ICC 2,1 : 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 cm 2 (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.
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