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- Title
Risk Factors of Significant Pain Syndrome 90 Days After Minor Thoracic Injury: Trajectory Analysis Factores de Riesgo del Síndrome Doloroso Clínicamente Significativo a los 90 Días tras un Traumatismo Torácico Menor: Análisis de la Trayectoria
- Authors
Daoust, Raoul; Émond, Marcel; Bergeron, Éric; LeSage, Natalie; Camden, Stéphanie; Guimont, Chantal; Vanier, Laurent; Chauny, Jean‐Marc; Bird, Steven B.
- Abstract
Objectives The objective was to identify the risk factors of clinically significant pain at 90 days in patients with minor thoracic injury ( MTI) discharged from the emergency department ( ED). Methods A prospective, multicenter, cohort study was conducted in four Canadian EDs from November 2006 to November 2010. All consecutive patients aged 16 years or older with MTI were eligible at discharge from EDs. They underwent standardized clinical and radiologic evaluations at 1 and 2 weeks, followed by standardized telephone interviews at 30 and 90 days. A pain trajectory model characterized groups of patients with different pain evolutions and ascertained specific risk factors in each group through multivariate analysis. Results In this cohort of 1,132 patients, 734 were eligible for study inclusion. The authors identified a pain trajectory that characterized 18.2% of the study population experiencing clinically significant pain (>3 of 10) at 90 days after a MTI. Multivariate modeling found two or more rib fractures, smoking, and initial oxygen saturation below 95% to be predictors of this group of patients. Conclusions To the authors' knowledge, this is the first prospective study of trajectory modeling to detect risk factors associated with significant pain at 90 days after MTI. These factors may help in planning specific treatment strategies and should be validated in another prospective cohort.
- Subjects
COMPLEX regional pain syndromes; DIAGNOSIS of bone fractures; PATIENT selection; RIB injuries; ASPIRIN; CHEST injuries; EMERGENCY medicine; LONGITUDINAL method; SMOKING; WARFARIN; DATA analysis; DATA analysis software; DIAGNOSIS; DISEASE risk factors
- Publication
Academic Emergency Medicine, 2013, Vol 20, Issue 11, p1139
- ISSN
1069-6563
- Publication type
Article
- DOI
10.1111/acem.12248