Department of Anaesthesiology and Pain Medicine, Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
School of Mechanical Engineering, Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju, South Korea.
Anaesthesia. 2018 Sep;73(9):1123-1130. doi: 10.1111/anae.14327. Epub 2018 May 23.
Although surrogate measures to quantify pain intensity have been commercialised, there is a need to develop a new index with improved accuracy. The aim of this study was to develop a new analgesic index using nasal photoplethysmography data. The specially designed sensor was placed between the columella and the nasal septum to acquire nasal photoplethysmography in surgical patients. Nasal photoplethysmography and Surgical Pleth Index (GE Healthcare) data were obtained for 14 min both in the absence (pre-operatively) or presence (postoperatively) of pain in a group of surgical patients, each patient acting as their own control. Various dynamic photoplethysmography variables were extracted to quantify pain intensity; the most accurate index was selected using logistic regression as a classifier. The area under the curve of the receiver-operating characteristic curve was measured to evaluate the accuracy of final model predictions. In total, 12,012 heart beats from 89 patients were used to develop a new Nasal Photoplethysmography Index for analgesic depth quantification. The two-variable model (a combination of diastolic peak point variation and heart beat interval variation) was most accurate in discriminating between the presence and absence of pain (numerical rating scale (NRS) ≥ 3). The accuracy and area under the curve of the receiver-operating characteristic curve for the Nasal Photoplethysmography Index were 75.3% and 0.8018, respectively, and 64.8% and 0.7034, respectively, for the Surgical Pleth Index. The Nasal Photoplethysmography Index clearly distinguished pain (NRS ≥ 3) in awake surgical patients with postoperative pain. The Nasal Photoplethysmography Index performed better than the Surgical Pleth Index. Further validation studies are needed to evaluate its feasibility to quantify pain intensity during general anaesthesia.
尽管已经商业化了用于量化疼痛强度的替代指标，但仍需要开发一种新的准确性更高的指数。本研究旨在利用鼻光体积描记术数据开发一种新的镇痛指数。该专用传感器放置在鼻中隔和鼻隔之间，以获取手术患者的鼻光体积描记术数据。在一组手术患者中，无论是否存在疼痛（术前和术后），均获得 14 分钟的鼻光体积描记术和 Surgical Pleth Index（GE Healthcare）数据，每个患者都作为自己的对照。提取了各种动态光体积描记术变量来量化疼痛强度；使用逻辑回归作为分类器选择最准确的指数。接收者操作特性曲线下的面积用于评估最终模型预测的准确性。总共使用了 89 名患者的 12012 次心跳，开发了一种新的鼻光体积描记术镇痛深度量化指数。在区分疼痛存在与否（数字评分量表（NRS）≥3）时，两变量模型（舒张压峰点变化和心跳间隔变化的组合）最准确。鼻光体积描记术指数的准确性和接收者操作特性曲线下的面积分别为 75.3%和 0.8018，Surgical Pleth Index 分别为 64.8%和 0.7034。鼻光体积描记术指数可清晰区分有术后疼痛的清醒手术患者的疼痛（NRS≥3）。鼻光体积描记术指数的性能优于 Surgical Pleth Index。需要进一步的验证研究来评估其在全身麻醉期间量化疼痛强度的可行性。
