-
摘要: 近年来,随着数字化医疗在医学麻醉领域应用逐渐广泛,其在儿童术后疼痛管理中的作用日益受到关注。数字化医疗不仅为儿童术后疼痛的术前预测、术后监测评估及治疗管理提供了新思路,同时为麻醉医生制定最佳术后疼痛管理策略提供了新方案。本文通过回顾数字化医疗及其在临床麻醉中的应用,对该疗法在儿童术后疼痛管理方面的应用前景进行综述,以期加深临床医师的认知。Abstract: In recent years, with the gradual and extensive application of digital medical treatment in the field of medica anesthesia, its role in the postoperative pain management of children has attracted increasing attention. It provides new ideas for the preoperative prediction, postoperative monitoring and evaluation, and treatment management of postoperative pain in children, as well as a new scheme for anesthesiologists to formulate the best postoperative pain management strategy for children. This article reviews digital medical treatment and its application in clinical anesthesia, and reviews the application prospects of this therapy in postoperative pain in children, in order to deepen clinicians' knowledge.
-
作者贡献:陈斐负责文献收集、论文撰写;张羽冠负责论文修订;朱波负责拟定写作思路,指导论文撰写并最终定稿。利益冲突:所有作者均声明不存在利益冲突
-
-
[1] Cachemaille M, Grass F, Fournier N, et al. Pain intensity in the first 96 hours after abdominal surgery: a prospective cohort study[J]. Pain Med, 2020, 21(4): 803-813. DOI: 10.1093/pm/pnz156
[2] Elshazly M, Shaban A, Gouda N, et al. Ultrasound-guided lumbar erector spinae plane block versus caudal block for postoperative analgesia in pediatric hip and proximal femur surgery: a randomized controlled study[J]. Korean J Anesthesiol, 2023, 76(3): 194-202. DOI: 10.4097/kja.22421
[3] Aulenkamp J L, Mosch L, Meyer-Frieβem C H, et al. Application possibilities of digital tools in postoperative pain therapy[J]. Schmerz, 2023, 37(4): 234-241. DOI: 10.1007/s00482-023-00732-7
[4] Lin B Y, Wu S J. Digital transformation in personalized medicine with artificial intelligence and the Internet of medical things[J]. OMICS, 2022, 26(2): 77-81. DOI: 10.1089/omi.2021.0037
[5] Zhou Y D, Wang F, Tang J, et al. Artificial intelligence in COVID-19 drug repurposing[J]. Lancet Digit Health, 2020, 2(12): e667-e676. DOI: 10.1016/S2589-7500(20)30192-8
[6] Pomari E, Piubelli C, Perandin F, et al. Digital PCR: a new technology for diagnosis of parasitic infections[J]. Clin Microbiol Infect, 2019, 25(12): 1510-1516. DOI: 10.1016/j.cmi.2019.06.009
[7] Liu K P G, Tan W L B, Yip W L J, et al. Making a traditional spine surgery clinic telemedicine-ready in the "new normal" of coronavirus disease 2019[J]. Asian Spine J, 2021, 15(2): 164-171. DOI: 10.31616/asj.2020.0508
[8] Bera K, Schalper K A, Rimm D L, et al. Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology[J]. Nat Rev Clin Oncol, 2019, 16(11): 703-715. DOI: 10.1038/s41571-019-0252-y
[9] Dang A, Arora D, Rane P. Role of digital therapeutics and the changing future of healthcare[J]. J Family Med Prim Care, 2020, 9(5): 2207-2213. DOI: 10.4103/jfmpc.jfmpc_105_20
[10] 刘子嘉, 黄宇光, 罗爱伦. 麻醉与加速术后康复[J]. 中华麻醉学杂志, 2016, 36(8): 909-912. DOI: 10.3760/cma.j.issn.0254-1416.2016.08.001 Liu Z J, Huang Y G, Luo A L. Anesthesia and accelerated postoperative rehabilitation[J]. Chin J Anesthesiol, 2016, 36(8): 909-912. DOI: 10.3760/cma.j.issn.0254-1416.2016.08.001
[11] Pan S, Rong L Q. Mobile applications in clinical and perioperative care for anesthesia: narrative review[J]. J Med Internet Res, 2021, 23(9): e25115. DOI: 10.2196/25115
[12] Makhlouf M M, Garibay E R, Jenkins B N, et al. Postoperative pain: factors and tools to improve pain management in children[J]. Pain Manag, 2019, 9(4): 389-397. DOI: 10.2217/pmt-2018-0079
[13] Richardson P A, Harrison L E, Heathcote L C, et al. mHealth for pediatric chronic pain: state of the art and future directions[J]. Expert Rev Neurother, 2020, 20(11): 1177-1187. DOI: 10.1080/14737175.2020.1819792
[14] Lalloo C, Shah U, Birnie K A, et al. Commercially available smartphone apps to support postoperative pain self-management: scoping review[J]. JMIR Mhealth Uhealth, 2017, 5(10): e162. DOI: 10.2196/mhealth.8230
[15] 朱剑锟, 倪坤, 朱慧杰, 等. 术前焦虑与围术期不良事件相关性的研究进展[J]. 临床麻醉学杂志, 2022, 38(5): 536-539. https://www.cnki.com.cn/Article/CJFDTOTAL-LCMZ202205017.htm Zhu J K, Ni K, Zhu H J, et al. Research advances of correlation between preoperative anxiety and perioperative adverse events[J]. J Clin Anesthesiol, 2022, 38(5): 536-539. https://www.cnki.com.cn/Article/CJFDTOTAL-LCMZ202205017.htm
[16] Wood M D, Correa K, Ding P J, et al. Identification of requirements for a postoperative pediatric pain risk communication tool: focus group study with clinicians and family members[J]. JMIR Pediatr Parent, 2022, 5(3): e37353. DOI: 10.2196/37353
[17] Niu T C, Liu M J, Fang Y, et al. Post-operative pain in children: comparison of pain scores between parents and children[J]. J Paediatr Child Health, 2023, 59(8): 943-947. DOI: 10.1111/jpc.16420
[18] 李玉静. 基于Gabor小波变换和LBP结合的新生儿疼痛表情识别研究[D]. 南京: 南京邮电大学, 2014. Li Y J. Neonatal pain expression recognition based on Gabor wavelet and local binary pattern[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2014.
[19] Sun T, West N, Ansermino J M, et al. A smartphone version of the Faces Pain Scale-Revised and the Color Analog Scale for postoperative pain assessment in children[J]. Paediatr Anaesth, 2015, 25(12): 1264-1273. DOI: 10.1111/pan.12790
[20] Aydin AI, Özyazicioğlu N. Assessment of postoperative pain in children with computer assisted facial expression analysis[J]. J Pediatr Nurs, 2023, 71: 60-65. DOI: 10.1016/j.pedn.2023.03.008
[21] Rawe I M, Lowenstein A, Barcelo C R, et al. Control of postoperative pain with a wearable continuously operating pulsed radiofrequency energy device: a preliminary study[J]. Aesthetic Plast Surg, 2012, 36(2): 458-463. DOI: 10.1007/s00266-011-9828-3
[22] Manickam P, Mariappan S A, Murugesan S M, et al. Artificial intelligence (AI) and Internet of medical things (IoMT) assisted biomedical systems for intelligent healthcare[J]. Biosensors (Basel), 2022, 12(8): 562.
[23] 中华医学会麻醉学分会"智能化病人自控镇痛管理专家共识"工作小组. 智能化病人自控镇痛管理专家共识[J]. 中华麻醉学杂志, 2018, 38(10): 1161-1165. DOI: 10.3760/cma.j.issn.0254-1416.2018.10.002 Chinese Society of Anesthesiology Task Force on Management of Artificial Intelligent Patient-Controlled Analgesia. Expert consensus on management of artificial intelli-gent patient-controlled analgesia[J]. Chin J Anesthesiol, 2018, 38(10): 1161-1165. DOI: 10.3760/cma.j.issn.0254-1416.2018.10.002
[24] Wang R, Wang S S, Duan N, et al. From patient-controlled analgesia to artificial intelligence-assisted patient-controlled analgesia: practices and perspectives[J]. Front Med (Lausanne), 2020, 7: 145.
[25] 王韶双, 段娜, 李小刚, 等. 智能化病人自控镇痛对术后镇痛患者不良反应与满意度的影响[J]. 广东医学, 2020, 41(11): 1097-1100. https://www.cnki.com.cn/Article/CJFDTOTAL-GAYX202011006.htm Wang S S, Duan N, Li X G, et al. Effects of artificial intelligent patient-controlled analgesia on the adverse reactions and satisfaction for postoperative patients[J]. Guangdong Med J, 2020, 41(11): 1097-1100. https://www.cnki.com.cn/Article/CJFDTOTAL-GAYX202011006.htm
[26] Haisley K R, Straw O J, Müller D T, et al. Feasibility of implementing a virtual reality program as an adjuvant tool for peri-operative pain control; results of a randomized control-led trial in minimally invasive foregut surgery[J]. Complement Ther Med, 2020, 49: 102356. DOI: 10.1016/j.ctim.2020.102356
[27] Ding L Y, Hua H X, Zhu H F, et al. Effects of virtual reality on relieving postoperative pain in surgical patients: a systematic review and meta-analysis[J]. Int J Surg, 2020, 82: 87-94.
[28] Xiang H, Shen J B, Wheeler K K, et al. Efficacy of smartphone active and passive virtual reality distraction vs standard care on burn pain among pediatric patients: a randomized clinical trial[J]. JAMA Netw Open, 2021, 4(6): e2112082. DOI: 10.1001/jamanetworkopen.2021.12082
[29] Olbrecht V A, O'Conor K T, Williams S E, et al. Transient reductions in postoperative pain and anxiety with the use of virtual reality in children[J]. Pain Med, 2021, 22(11): 2426-2435. DOI: 10.1093/pm/pnab209
[30] Arane K, Behboudi A, Goldman RD. Virtual reality for pain and anxiety management in children[J]. Can Fam Physician, 2017, 63(12): 932-934.