Quantification of Patient-Reported Pain Locations: Development of an Automated Measurement Method

量化患者自述疼痛部位:开发一种自动化测量方法

阅读:1

Abstract

Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease-associated pain completed PAIN Report It Ⓡ . This computer-based instrument includes a two-dimensional, digital body outline on which patients mark their pain location. Using the ImageJ software, we calculated the percentage of the body surface area marked as painful and summarized data with descriptive statistics and a pain frequency map. The painful body areas most frequently marked were the left leg-front (73%), right leg-front (72%), upper back (72%), and lower back (70%). The frequency of pain marks in each of the 48 body segments ranged from 3 to 79 (mean, 33.2 ± 21.9). The mean percentage of painful body surface area per segment was 10.8% ± 7.5% (ranging from 1.3% to 33.1%). Patient-reported pain locations can be easily analyzed from digital drawings using an algorithm created via the free ImageJ software. This method may enhance comprehensive pain assessment, facilitating research and personalized care over time for patients with various pain conditions.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。