JOURNAL ARTICLE
VALIDATION STUDY
Add like
Add dislike
Add to saved papers

Individualized assessment of preterm birth risk using two modified prediction models.

OBJECTIVES: To construct two prediction models for individualized assessment of preterm delivery risk within 48h and before completed 32 weeks of gestation and to test the validity of modified and previously published models.

STUDY DESIGN: Data on 617 consecutive women with preterm labor transferred to a tertiary care center for threatened preterm delivery between 22 and 32 weeks of gestation were analysed. Variables predicting the risk of delivery within 48h and before completed 32 weeks of gestation were assessed and applied to previously published prediction models. Multivariate analyses identified variables that were incorporated into two modified models that were subsequently validated.

RESULTS: Two modified prediction models were developed and internally validated, incorporating four and six of the following variables to predict the risk of delivery within 48h and before completed 32 weeks of gestation, respectively: presence of preterm premature rupture of membranes and/or vaginal bleeding, sonographic cervical length, week of gestation, fetal fibronectin, and serum C-reactive protein. The correspondence between the actual and the predicted preterm birth rates suggests excellent calibration of the models. Internal validation analyses for the modified 48h and 32 week prediction models revealed considerably high concordance-indices of 0.8 (95%CI: [0.70-0.81]) and 0.85 (95%CI: [0.82-0.90]), respectively.

CONCLUSIONS: Two modified prediction models to assess the risk of preterm birth were constructed and validated. The models can be used for individualized prediction of preterm birth and allow more accurate risk assessment than based upon a single risk factor. An online-based risk-calculator was constructed and can be assessed through: https://cemsiis.meduniwien.ac.at/en/kb/science-research/software/clinical-software/prematurebirth/.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app