Hoti Kreshnik, Chivers Paola Teresa, Hughes Jeffery David
Faculty of Medicine, University of Prishtina, Pristina, Kosovo.
Institute for Health Research, The University of Notre Dame Australia, Fremantle, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
Lancet Digit Health. 2021 Oct;3(10):e623-e634. doi: 10.1016/S2589-7500(21)00129-1. Epub 2021 Sep 1.
The management of procedural pain in infants is suboptimal, in part, compounded by the scarcity of a simple, accurate, and reliable method of assessing such pain. In this study, we aimed to evaluate the psychometric properties of the PainChek Infant, a point-of-care mobile application that uses automated facial evaluation and analysis in the assessment of procedural pain in infants.
Video recordings of 40 infants were randomly chosen from a purposely assembled digital library of 410 children undergoing immunisation as part of their standard care in Prishtina, Kosovo, between April 4, 2017, and July 11, 2018. For each infant recording, four 10 s video segments were extracted, corresponding to baseline, vaccine preparation, during vaccination, and recovery. Four trained assessors did pain assessments on the video segments of 30 infants, using PainChek Infant standard, PainChek Infant adaptive, the Neonatal Facial Coding System-Revised (NFCS-R) single, the NFCS-R multiple, and the Observer administered Visual Analogue Scale (ObsVAS), on two separate occasions. PainChek Infant's performance was compared to NFCS-R and ObsVAS using correlation in changes in pain scores, intra-rater and inter-rater reliability, and internal consistency.
4303 pain assessments were completed in two separate testing sessions, on Aug 31, and Oct 19, 2020. The study involved videos of 40 infants aged 2·2-6·9 months (median age 3·4 months [IQR 2·3-4·5]). All pain assessment tools showed significant changes in the recorded pain scores across the four video segments (p≤0·0006). All tools were found to be responsive to procedure-induced pain, with the degree of change in pain scores not influenced by pre-vaccination pain levels. PainChek Infant pain scores showed good correlation with NFCS-R and ObsVAS scores (r=0·82-0·88; p<0·0001). PainChek Infant also showed good to excellent inter-rater reliability (ICC=0·81-0·97, p<0·001) and high levels of internal consistency (α=0·82-0·97).
PainChek Infant's use of automated facial expression analysis could offer a valid and reliable means of assessing and monitoring procedural pain in infants. Its clinical utility in clinical practice requires further research.
PainChek.
婴儿程序性疼痛的管理并不理想，部分原因是缺乏一种简单、准确且可靠的疼痛评估方法。在本研究中，我们旨在评估PainChek Infant的心理测量特性，这是一款即时护理移动应用程序，在评估婴儿程序性疼痛时使用自动面部评估和分析。
从2017年4月4日至2018年7月11日在科索沃普里什蒂纳作为标准护理一部分接受免疫接种的410名儿童的专门组建的数字库中随机选择40名婴儿的视频记录。对于每个婴儿记录，提取四个10秒的视频片段，分别对应基线、疫苗准备、接种期间和恢复阶段。四名经过培训的评估人员在两个不同的场合，使用PainChek Infant标准、PainChek Infant自适应、修订后的新生儿面部编码系统（NFCS-R）单一评分、NFCS-R多重评分以及观察者实施的视觉模拟量表（ObsVAS），对30名婴儿的视频片段进行疼痛评估。使用疼痛评分变化的相关性、评估者内和评估者间的可靠性以及内部一致性，将PainChek Infant的表现与NFCS-R和ObsVAS进行比较。
在2020年8月31日和10月19日的两个单独测试阶段完成了4303次疼痛评估。该研究涉及40名年龄在2.2 - 6.9个月（中位年龄3.4个月[四分位间距2.3 - 4.5]）的婴儿的视频。所有疼痛评估工具在四个视频片段中的记录疼痛评分均显示出显著变化（p≤0.0006）。发现所有工具对程序诱导的疼痛都有反应，疼痛评分的变化程度不受接种前疼痛水平的影响。PainChek Infant疼痛评分与NFCS-R和ObsVAS评分显示出良好的相关性（r = 0.82 - 0.88；p < 0.0001）。PainChek Infant还显示出良好至优秀的评估者间可靠性（组内相关系数ICC = 0.81 - 0.97，p < 0.001）和高水平的内部一致性（α = 0.82 - 0.97）。
PainChek Infant使用自动面部表情分析可以提供一种有效且可靠的手段来评估和监测婴儿的程序性疼痛。其在临床实践中的临床效用需要进一步研究。
PainChek。
