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ORIGINAL RESEARCH

Early Magnetic Resonance Imaging Measurements and Prediction of Second Trimester Pregnancy Loss: a Nomogram Model Analysis

, , , , &
Pages 819-827 | Received 21 Dec 2023, Accepted 20 Apr 2024, Published online: 14 May 2024
 

Abstract

Objective

To investigate the magnetic resonance imaging (MRI) features of women with prior second-trimester pregnancy loss, and to establish a nomogram prediction model for subsequent miscarriage.

Methods

A retrospective cohort study of women with prior second-trimester pregnancy loss from January 2018 to December 2021 in Second Affiliated Hospital of Soochow University was performed. A total of 245 patients were included. Data from January 2018 to December 2019 were used to construct the model, and data from January 2020 to December 2021 were used to evaluate the model. Data on maternal demographic characteristics, MRI cervical measurements were extracted. The prediction model was constructed with independent variables determined by multivariate logistic regression analyses. Through receiver-operating characteristic (ROC) curve analysis, the predictive ability of the model for subsequent second trimester pregnancy loss in women was evaluated, and internal validation was performed through validation data.

Results

Thin cervix was observed in 77 (31.42%) women with prior second-trimester pregnancy loss, the mean longitudinal diameter of cervical canal on MRI was 11.76±2.75mm. The model reached a sensitivity of 80%, specificity of 75.90%, positive predictive value (PPV) of 55.80% and negative predictive value of 90.90%; ROC characteristics proved that the model was superior to any single parameter with an AUC of 0.826.

Conclusion

Our observations showed that thin cervix and longitudinal diameter of cervical canal reliably predicted second trimester pregnancy loss. We developed and validated a nomogram model to predict the individual probability of second trimester pregnancy loss in the next pregnancy and hopefully improve the prediction and indication of interventions.

Data Sharing Statement

The authors confirm that the data supporting the findings of this study are available within the article.

Ethics Approval and Consent to Participate

This study was approved by the Ethics Committee of the second affiliated hospital of Soochow university (JD-LK-2018-030-03) on August 6, 2018. The study was conducted according to the ethical principles stated in the Declaration of Helsinki. Informed consent was obtained from all subjects.

Acknowledgments

The authors would like to thank all the participants for their contributions to this study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This project was supported by National Natural Science Foundation of China (82071726) and Suzhou People’s Livelihood Technology-Medical and Health Application Basic Research (SYS2020133) and national natural science pre-research foundation of the Second Affiliated Hospital(SDFEYGZ2220).