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A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage

OBJECTIVE: To develop a nomogram to predict preterm birth before 28 weeks in pregnant women undergoing cervical cerclage. STUDY DESIGN: We retrospectively studied the medical records on pregnant women who underwent cervical cerclage in January 2016 to September 2020. We developed the model from a de...

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Autores principales: Lv, Min, Chen, Cheng, Qiu, Liping, Jin, Neng, Wang, Minmin, Zhao, Baihui, Chen, Danqing, Luo, Qiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561736/
https://www.ncbi.nlm.nih.gov/pubmed/36247114
http://dx.doi.org/10.1016/j.heliyon.2022.e10731
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author Lv, Min
Chen, Cheng
Qiu, Liping
Jin, Neng
Wang, Minmin
Zhao, Baihui
Chen, Danqing
Luo, Qiong
author_facet Lv, Min
Chen, Cheng
Qiu, Liping
Jin, Neng
Wang, Minmin
Zhao, Baihui
Chen, Danqing
Luo, Qiong
author_sort Lv, Min
collection PubMed
description OBJECTIVE: To develop a nomogram to predict preterm birth before 28 weeks in pregnant women undergoing cervical cerclage. STUDY DESIGN: We retrospectively studied the medical records on pregnant women who underwent cervical cerclage in January 2016 to September 2020. We developed the model from a development cohort in Women's Hospital, Zhejiang university, School of medicine, which randomly divided by 7:3 into training cohort for nomogram development, and internal validation cohort to confirm the model's performance. We then tested the nomogram in an external validation cohort over a similar period. The Harrell's C-index, calibration curve, decision curve analyses (DCA) were performed to assess the model. RESULTS: 528 patients formed the development cohort, and 97 patients formed the external validation cohort. The model initially incorporated 10 baseline variables, while 5 variables were estimated in the nomogram at last: history of prior second-trimester loss, use of in-vitro fertilization (IVF), cervical dilation at cerclage, C-reactive protein (CRP) and platelet-lymphocyte ratio (PLR). The nomogram achieved good concordance indexes of 0.82(95%CI 0.77–0.88), 0.80(95%CI 0.72–0.88) and 0.79 (95%CI 0.68–0.90) in the training, internal and external validation cohort, respectively. And the nomogram had well-fitted calibration curves. Decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSIONS: The well-performed nomogram graphically represents the risk factors and a pre-operative predicted model in predicting the risk of preterm birth at <28 weeks in singleton pregnant women undergoing cervical cerclage. The model can provide a useful guide for clinicians and patients in making appropriate clinical decisions.
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spelling pubmed-95617362022-10-15 A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage Lv, Min Chen, Cheng Qiu, Liping Jin, Neng Wang, Minmin Zhao, Baihui Chen, Danqing Luo, Qiong Heliyon Research Article OBJECTIVE: To develop a nomogram to predict preterm birth before 28 weeks in pregnant women undergoing cervical cerclage. STUDY DESIGN: We retrospectively studied the medical records on pregnant women who underwent cervical cerclage in January 2016 to September 2020. We developed the model from a development cohort in Women's Hospital, Zhejiang university, School of medicine, which randomly divided by 7:3 into training cohort for nomogram development, and internal validation cohort to confirm the model's performance. We then tested the nomogram in an external validation cohort over a similar period. The Harrell's C-index, calibration curve, decision curve analyses (DCA) were performed to assess the model. RESULTS: 528 patients formed the development cohort, and 97 patients formed the external validation cohort. The model initially incorporated 10 baseline variables, while 5 variables were estimated in the nomogram at last: history of prior second-trimester loss, use of in-vitro fertilization (IVF), cervical dilation at cerclage, C-reactive protein (CRP) and platelet-lymphocyte ratio (PLR). The nomogram achieved good concordance indexes of 0.82(95%CI 0.77–0.88), 0.80(95%CI 0.72–0.88) and 0.79 (95%CI 0.68–0.90) in the training, internal and external validation cohort, respectively. And the nomogram had well-fitted calibration curves. Decision curve analysis demonstrated that the nomogram was clinically useful. CONCLUSIONS: The well-performed nomogram graphically represents the risk factors and a pre-operative predicted model in predicting the risk of preterm birth at <28 weeks in singleton pregnant women undergoing cervical cerclage. The model can provide a useful guide for clinicians and patients in making appropriate clinical decisions. Elsevier 2022-09-22 /pmc/articles/PMC9561736/ /pubmed/36247114 http://dx.doi.org/10.1016/j.heliyon.2022.e10731 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Lv, Min
Chen, Cheng
Qiu, Liping
Jin, Neng
Wang, Minmin
Zhao, Baihui
Chen, Danqing
Luo, Qiong
A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title_full A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title_fullStr A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title_full_unstemmed A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title_short A nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
title_sort nomogram to predict extremely preterm birth in women with singleton pregnancies undergoing cervical cerclage
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561736/
https://www.ncbi.nlm.nih.gov/pubmed/36247114
http://dx.doi.org/10.1016/j.heliyon.2022.e10731
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