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Advanced statistical approaches for predicting pain after pediatric thoracotomy: a cross-sectional study using zero-inflated and Poisson models

  • Alessandro Vittori,
  • Marco Cascella,
  • Piergiacomo Di Gennaro,
  • Giuliano Marchetti,
  • Elisa Francia,
  • Ilaria Mascilini,
  • Riccardo Tarquini,
  • Massimo Antonio Innamorato,
  • Emiliano Petrucci,
  • Franco Marinangeli,
  • Sergio Coluccia,
  • Sergio Giuseppe Picardo

摘要

Background

Thoracotomy is one of the surgical procedures most burdened by chronic post-operative pain. There is poor evidence regarding the possibility that even in pediatric patients, thoracotomy can be followed by post-operative pain. The primary objective of this analysis is to identify associations with home pain therapy, pain intensity, and possible protective factors acting on chronic pain in this population.

Methods

A retrospective cross-sectional study was conducted at Ospedale Pediatrico Bambino Gesù IRCCS. The study included pediatric patients undergoing thoracotomy. For statistical analyses, a logistic model and a zero-inflated strategy were implemented to explore associations and predict factors related to home-based analgesic therapy and pain intensity.

Results

Gender and age were identified as significant factors in the assignment of home therapy, with males having over seven times the risk compared to females (OR = 7.06, 95% CI = [2.11, 29.7]). At the last measurement, pain intensity was positively associated with age and the number of pain events during the week.

Conclusions

The study highlights significant factors influencing post-thoracotomy pain management in pediatric patients. These findings underscore the importance of tailored pain management strategies that consider gender and age to improve post-operative care and outcomes in pediatric thoracotomy patients.