A classification algorithm for prioritizing surgery in Pediatric patients with idiopathic scoliosis when Long Surgical delays are expected
Author:
Funder
Bourse de jumelage de fonds du CHU Sainte-Justine
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00586-024-08405-4.pdf
Reference36 articles.
1. Nault ML, Beauséjour M, Roy-Beaudry M et al (2020) A predictive model of progression for adolescent idiopathic scoliosis based on 3D spine parameters at first visit. Spine (Phila Pa 1976) 45(9):605–611. https://doi.org/10.1097/BRS.0000000000003316. Erratum in: Spine (Phila Pa 1976). 2020;45(12):E753
2. Konieczny MR, Senyurt H, Krauspe R (2013) Epidemiology of adolescent idiopathic scoliosis. J Child Orthop 7(1):3–9
3. Parent S, Newton PO, Wenger DR (2005) Adolescent idiopathic scoliosis: etiology, anatomy, natural history, and bracing. Instr Course Lect 54:529–536
4. Reames DL, Smith JS, Fu KM et al (2011) Scoliosis Research Society Morbidity and Mortality Committee. Complications in the surgical treatment of 19,360 cases of pediatric scoliosis: a review of the Scoliosis Research Society Morbidity and Mortality database. Spine (Phila Pa 1976) 36(18):1484–1491
5. Ahn H, Kreder H, Mahomed N, Beaton D, Wright JG (2011) Empirically derived maximal acceptable wait time for surgery to treat adolescent idiopathic scoliosis. CMAJ 183(9):E565–E570. https://doi.org/10.1503/cmaj.101511
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