Oral and topical analgesia in pediatric electrodiagnostic studies.

Bisma Aziz,Sajid Hameed,Haris Hakeem,Fazal Ur Rehman,Marib Ghulam Rasool Malik, Saadia Sattar, Pinin Baig, Safoora Ibraheem Zuberi,Sara Khan

Muscle & nerve(2024)

引用 0|浏览0
暂无评分
摘要
INTRODUCTION/AIMS:Electrodiagnostic examinations, such as nerve conduction studies (NCS) and needle electromyography (EMG), are perceived as painful by children and their parents/guardians. Methods to reduce peri-procedural pain improve compliance and have neurocognitive and neuropsychiatric benefits. This study aimed to assess the efficacy of combined oral and topical analgesics (COTA), oral analgesics (OA), and placebo in reducing pain during NCS/EMG in children. METHODS:We performed a double-blind, randomized, placebo-controlled trial on children presenting to our neurophysiology lab. Patients were stratified into two age groups (6M-6Y and 7Y-18Y) and randomized into three arms: COTA, OA, and placebo. Pain scores post-NCS/EMG were assessed using the Modified Behavioral Pain Scale (MBPS) and Faces Pain Scale-Revised (FPS-R). RESULTS:One hundred thirteen participants were enrolled. A comparison of participants from both age groups combined revealed no significant differences in guardian FPS-R scores across all arms for NCS and EMG. A significant difference in the distribution of post-NCS FPS-R score severities in children aged 7Y-18Y was noted between OA and placebo (p = .007). EMG was more painful than NCS across all arms (p < .05). In children aged 6M-6Y undergoing at least 10 muscle samplings during EMG, those receiving COTA had significantly lower pain scores (p = .014). DISCUSSION:This study reveals the complexity of pediatric pain perception during NCS/EMG and highlights that other methods to reduce experienced pain are required. Our findings suggest that procedural characteristics, such as number of muscles sampled, may influence the effectiveness of analgesia and serve as a foundation for future research aimed at optimizing pain management strategies.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要