BMJ Open (Mar 2024)

Longitudinal Resilience and Risk Factors in Pediatric Postoperative Pain (LORRIS): Protocol for a Prospective Longitudinal Swiss University Children’s Hospitals-Based Study

  • Cosima Locher,
  • Ulrike Held,
  • Helen Koechlin,
  • Jana Hochreuter,
  • Thomas Dreher,
  • Carol-Claudius Hasler,
  • Sandro Canonica,
  • Jennifer Rabbitts

DOI
https://doi.org/10.1136/bmjopen-2023-080174
Journal volume & issue
Vol. 14, no. 3

Abstract

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Introduction Chronic postsurgical pain (CPSP) is defined as pain that persists after a surgical procedure and has a significant impact on quality of life. Previous studies show the importance of psychological factors in CPSP, yet the majority of studies focused solely on negative emotions. This longitudinal observational study aims to broaden this knowledge base by examining the role of emotional state, emotion variability, emotion regulation and emotion differentiation on the child and the parent level for the development CPSP, and to describe pain and emotion-related trajectories following surgery.Methods and analysis We intend to include 280 children and adolescents aged 8–18 years with a planned orthopaedic surgery and their parents. A total of five assessment time points is planned: 3 weeks before surgery (baseline), 2 weeks after surgery (post) and 3 months (follow-up (FU) 1), 6 months and 12 months after surgery. At baseline and post only, children and parents are asked to complete a daily diary thrice a day for a week where they rate their current emotional state and their pain severity (children only). Emotional state ratings will be used to calculate indices of emotion variability, emotion regulation and emotion differentiation. Children and parents will complete questionnaires at each time point, including measures on quality of life, social support, sleep, and symptoms of anxiety and depression.To predict development of CPSP, generalised linear regression models will be used, resulting in ORs and 95% CIs. Pearson product-moment correlations between predictors and outcomes will be evaluated at each time point. The primary outcome of the prediction model is CPSP at FU1. For the trajectory analysis, the classification method K-means for longitudinal data will be used to determine clusters in the data.Ethics and dissemination The Ethics Committee of the Canton of Zurich, Switzerland, has approved the study (ID: 2023-01475). Participants will be compensated, and a dissemination workshop will be held.Trial registration number NCT05816174.