Abstract
Chen M-M, Chang H-C, Hsieh C-F, Yen M-F, Chen TH. Predictive model for congenital
muscular torticollis: analysis of 1021 infants with sonography.
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.
Key Words
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Article info
Footnotes
No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author(s) or upon any organization with which the author(s) is/are associated.
Identification
Copyright
© 2005 American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.
