Literature DB >> 26002592

Predicting success or failure of brace treatment for adolescents with idiopathic scoliosis.

Eric Chalmers1, Lindsey Westover1,2, Johith Jacob2, Andreas Donauer2, Vicky H Zhao1, Eric C Parent1, Marc J Moreau2, James K Mahood2, Douglas M Hedden2, Edmond H M Lou3,4.   

Abstract

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity. Brace treatment is a common non-surgical treatment, intended to prevent progression (worsening) of the condition during adolescence. Estimating a braced patient's risk of progression is an essential part of planning treatment, so method for predicting this risk would be a useful decision support tool for practitioners. This work attempts to discover whether failure of brace treatment (progression) can be predicted at the start of treatment. Records were obtained for 62 AIS patients who had completed brace treatment. Subjects were labeled as "progressive" if their condition had progressed despite brace treatment and "non-progressive" otherwise. Wrapper-based feature selection selected two useful predictor variables from a list of 14 clinical measurements taken from the records. A logistic regression model was trained to classify patients as "progressive" or "non-progressive" using these two variables. The logistic regression model's simplicity and interpretability should facilitate its clinical acceptance. The model was tested on data from an additional 28 patients and found to be 75 % accurate. This accuracy is sufficient to make the predictions clinically useful. It can be used online: http://www.ece.ualberta.ca/~dchalmer/SimpleBracePredictor.html .

Entities:  

Keywords:  Clinical decision support; Prediction model; Scoliosis

Mesh:

Year:  2015        PMID: 26002592     DOI: 10.1007/s11517-015-1306-7

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  29 in total

1.  Prediction of scoliosis progression with serial three-dimensional spinal curves and the artificial progression surface technique.

Authors:  Hongfa Wu; Janet L Ronsky; Farida Cheriet; Jessica Küpper; James Harder; Deyi Xue; Ronald F Zernicke
Journal:  Med Biol Eng Comput       Date:  2010-07-09       Impact factor: 2.602

2.  A meta-analysis of the efficacy of non-operative treatments for idiopathic scoliosis.

Authors:  D E Rowe; S M Bernstein; M F Riddick; F Adler; J B Emans; D Gardner-Bonneau
Journal:  J Bone Joint Surg Am       Date:  1997-05       Impact factor: 5.284

3.  Individualized patient-centered lifestyle recommendations: an expert system for communicating patient specific cardiovascular risk information and prioritizing lifestyle options.

Authors:  Chih-Lin Chi; W Nick Street; Jennifer G Robinson; Matthew A Crawford
Journal:  J Biomed Inform       Date:  2012-08-08       Impact factor: 6.317

4.  Scoliometer measurements of patients with idiopathic scoliosis.

Authors:  Daniel M Coelho; Guilherme H Bonagamba; Anamaria S Oliveira
Journal:  Braz J Phys Ther       Date:  2013 Mar-Apr       Impact factor: 3.377

5.  Three-dimensional spine parameters can differentiate between progressive and nonprogressive patients with AIS at the initial visit: a retrospective analysis.

Authors:  Marie-Lyne Nault; Jean-Marc Mac-Thiong; Marjolaine Roy-Beaudry; Jacques deGuise; Hubert Labelle; Stefan Parent
Journal:  J Pediatr Orthop       Date:  2013-09       Impact factor: 2.324

Review 6.  Surgical rates after observation and bracing for adolescent idiopathic scoliosis: an evidence-based review.

Authors:  Lori A Dolan; Stuart L Weinstein
Journal:  Spine (Phila Pa 1976)       Date:  2007-09-01       Impact factor: 3.468

7.  Accuracy in the prediction and estimation of adherence to bracewear before and during treatment of adolescent idiopathic scoliosis.

Authors:  Anne Morton; Russ Riddle; Renee Buchanan; Don Katz; John Birch
Journal:  J Pediatr Orthop       Date:  2008 Apr-May       Impact factor: 2.324

8.  Brace treatment for adolescent idiopathic scoliosis.

Authors:  Edmond Lou; Douglas Hill; Jim Raso
Journal:  Stud Health Technol Inform       Date:  2008

9.  Transverse plane 3D analysis of mild scoliosis.

Authors:  Aurélien Courvoisier; Xavier Drevelle; Jean Dubousset; Wafa Skalli
Journal:  Eur Spine J       Date:  2013-06-13       Impact factor: 3.134

10.  Prediction of progression of the curve in girls who have adolescent idiopathic scoliosis of moderate severity. Logistic regression analysis based on data from The Brace Study of the Scoliosis Research Society.

Authors:  L E Peterson; A L Nachemson
Journal:  J Bone Joint Surg Am       Date:  1995-06       Impact factor: 5.284

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  5 in total

1.  The development of a novel knowledge-based weaning algorithm using pulmonary parameters: a simulation study.

Authors:  Hasan Guler; Ugur Kilic
Journal:  Med Biol Eng Comput       Date:  2017-08-02       Impact factor: 2.602

2.  Predictive factors for brace treatment outcome in adolescent idiopathic scoliosis: a best-evidence synthesis.

Authors:  Manon van den Bogaart; Barend J van Royen; Tsjitske M Haanstra; Marinus de Kleuver; Sayf S A Faraj
Journal:  Eur Spine J       Date:  2019-01-03       Impact factor: 3.134

3.  A new method to approximate load-displacement relationships of spinal motion segments for patient-specific multi-body models of scoliotic spine.

Authors:  Athena Jalalian; Francis E H Tay; Soheil Arastehfar; Gabriel Liu
Journal:  Med Biol Eng Comput       Date:  2016-09-26       Impact factor: 2.602

4.  Predicting curve progression for adolescent idiopathic scoliosis using random forest model.

Authors:  Ausilah Alfraihat; Amer F Samdani; Sriram Balasubramanian
Journal:  PLoS One       Date:  2022-08-11       Impact factor: 3.752

5.  Compliance monitor for scoliosis braces in clinical practice.

Authors:  Sabrina Donzelli; Fabio Zaina; Stefano Negrini
Journal:  J Child Orthop       Date:  2015-11-02       Impact factor: 1.548

  5 in total

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