Affiliation:
1. Department of Anesthesiology & Pain Medicine Nationwide Children's Hospital and The Ohio State University Columbus Ohio USA
2. Center for Clinical and Translational Research Nationwide Children's Hospital and The Ohio State University Columbus Ohio USA
Abstract
AbstractIntroductionTonsillectomies are among the most common surgical procedures in children, with over 500 000 cases annually in the United States. Despite universal administration of intraoperative opioid analgesia, three out of five children undergoing tonsillectomy report moderate‐to‐severe pain upon recovering from anesthesia. The underlying molecular mechanisms of post‐tonsillectomy pain are not well understood, limiting the development of targeted treatment strategies. Our study aimed to identify candidate serum metabolites associated with varying severity of post‐tonsillectomy pain.MethodsVenous blood samples and pain scores were obtained from 34 children undergoing tonsillectomy ± adenoidectomy, and metabolomic analysis was performed. Supervised orthogonal projections to latent structures discriminant analysis were employed to identify differentially expressed metabolites between children with severe and mild pain, as well as between moderate and mild pain.ResultsPain scores differentiated children as mild (n = 6), moderate (n = 14), or severe (n = 14). Four metabolites (fatty acid 18:0(OH), thyroxine, phosphatidylcholine 38:5, and branched fatty acids C27H54O3) were identified as candidate biomarkers that differentiated severe vs. mild post‐tonsillectomy pain, the combination of which yielded an AUC of 0.91. Similarly, four metabolites (sebacic acid, dicarboxylic acids C18H34O4, hydroxy fatty acids C18H34O3, and myristoleic acid) were identified as candidate biomarkers that differentiated moderate vs. mild post‐tonsillectomy pain, with AUC values ranging from 0.85 to 0.95.ConclusionThis study identified novel candidate biomarker panels that effectively differentiated varying severity of post‐tonsillectomy pain. Further research is needed to validate these data and to explore their clinical implications for personalized pain management in children undergoing painful surgeries.
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