PREDICTIVE MODEL FOR CONGENITAL MUSCULAR TORTICOLLIS: ANALYSIS OF 1021 INFANTS WITH SONOGRAPHY
Resource
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION v.86 n.11 pp.2199-2203
Journal
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Journal Volume
v.86
Journal Issue
n.11
Pages
2199-2203
Date Issued
2005
Date
2005
Author(s)
Chen, Miao-Ming
Chang, Huan-Cheng
Hsieh, Chuan-Fa
Yen, Ming-Fang
Chen, Tony Hsui-Hsi
Abstract
Objective To construct a predictive model to foretell congenital muscular torticollis (CMT) on the basis of clinical correlates. Design Correlation study. Setting Regional hospital. Participants A consecutive series of 1021 newborn infants. Interventions Not applicable. Main Outcome Measure Participants underwent portable ultrasonography to diagnose CMT. Significant clinical correlates were identified to construct a predictive model using the logistic regression model. Results Forty of 1021 infants were diagnosed with CMT using ultrasonography, yielding an overall incidence of 3.92%. Birth body length ( odds ratio [OR]=1.38; 95% confidence interval [CI], 1.49–2. 38), facial asymmetry (OR=21.75; 95% CI, 6.6–71.7), plagiocephaly (OR=22.3; 95% CI, 7.01–70.95), perineal trauma during delivery (OR=4.26; 95% CI, 1.25–14.52), and primiparity (OR=6.32; 95% CI, 2.34–17.04) were significant correlates. A predictive logistic regression model with the incorporation of these 4 correlates was developed. We used cross-validation with a receiver operating characteristic curve to validate the predictive model. Conclusions Our study successfully developed a quantitative predictive model for estimating the risk of CMT on the basis of clinical correlates only. This model has good discriminative ability for classifying CMT and non-CMT by yielding acceptable values of false-negative and false-positive cases.
Subjects
Ultrasonography
Torticollis
Rehabilitation
Projections and predictions
Type
journal article