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.
| Original language | English |
|---|---|
| Pages (from-to) | 2199-2203 |
| Number of pages | 5 |
| Journal | Archives of Physical Medicine and Rehabilitation |
| Volume | 86 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - Nov 2005 |
| Externally published | Yes |
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Keywords
- Projections and predictions
- Rehabilitation
- Torticollis
- Ultrasonography
ASJC Scopus subject areas
- Rehabilitation
Cite this
Predictive model for congenital muscular torticollis : Analysis of 1021 infants with sonography. / Chen, Miao Ming; Chang, Huan Cheng; Hsieh, Chuan Fa; Yen, Ming Fang; Chen, Tony Hsui Hsi.
In: Archives of Physical Medicine and Rehabilitation, Vol. 86, No. 11, 11.2005, p. 2199-2203.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Predictive model for congenital muscular torticollis
T2 - Analysis of 1021 infants with sonography
AU - Chen, Miao Ming
AU - Chang, Huan Cheng
AU - Hsieh, Chuan Fa
AU - Yen, Ming Fang
AU - Chen, Tony Hsui Hsi
PY - 2005/11
Y1 - 2005/11
N2 - 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.
AB - 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.
KW - Projections and predictions
KW - Rehabilitation
KW - Torticollis
KW - Ultrasonography
UR - http://www.scopus.com/inward/record.url?scp=27644521363&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=27644521363&partnerID=8YFLogxK
U2 - 10.1016/j.apmr.2005.05.010
DO - 10.1016/j.apmr.2005.05.010
M3 - Article
C2 - 16271571
AN - SCOPUS:27644521363
VL - 86
SP - 2199
EP - 2203
JO - Archives of Physical Medicine and Rehabilitation
JF - Archives of Physical Medicine and Rehabilitation
SN - 0003-9993
IS - 11
ER -