Predictive nomogram of ultrasound indicators for the termination outcome of caesarean scar pregnancy

To develop and validate a nomogram for predicting the risk of adverse events (intraoperative massive haemorrhage or retained products of conception) associated with the termination of Caesarean scar pregnancy (CSP). Data were retrospectively collected from patients diagnosed with CSP who underwent Dilation and Curettage (D&C) at two hospitals. This data was divided into internal and external cohorts for analysis. The internal cohort was randomly split, with 70% of the data designated for a training set and 30% for an internal validation set. The external cohort served exclusively as the external validation set. LASSO and logistic regression techniques were employed to select variables and construct the nomogram. The performance of the nomogram was evaluated using various methods, including C-index, calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CICA), to assess its identification, calibration, and clinical effectiveness. The prediction nomogram included several predictors, such as scar thickness, type of CSP, gestational sac diameter, and blood flow. It demonstrated strong discrimination, with a C-index of 0.83 (95% confidence interval: 0.77-0.89). Furthermore, in the internal validation set, a high C-index of 0.78 was achieved, while in the external validation set, it reached 0.83. Additional assessments using calibration curve analysis, DCA, and CICA indicated robust agreement between the nomogram's predictions and actual observations, highlighting its utility and reliability. The developed nomogram shows excellent discriminative ability and calibration, with the potential for effective local prediction of adverse events in CSP.

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Publication Details

Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82894-7
Citations
3
Primary Topic
Ectopic Pregnancy Diagnosis and Management
Type
article
Field-Weighted Citation Impact
1.63
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article

Predictive nomogram of ultrasound indicators for the termination outcome of caesarean scar pregnancy

Zhichao Feng, Xiaoyi Xiao, Ting Li, Hong Qiao et al.
3 citations
Scientific Reports
Ectopic Pregnancy Diagnosis and Management
1.63
article

Predictive nomogram of ultrasound indicators for the termination outcome of caesarean scar pregnancy

Zhichao Feng, Xiaoyi Xiao, Ting Li, Hong Qiao, Yun Zhu
article en
3 citations

Abstract

To develop and validate a nomogram for predicting the risk of adverse events (intraoperative massive haemorrhage or retained products of conception) associated with the termination of Caesarean scar pregnancy (CSP). Data were retrospectively collected from patients diagnosed with CSP who underwent Dilation and Curettage (D&C) at two hospitals. This data was divided into internal and external cohorts for analysis. The internal cohort was randomly split, with 70% of the data designated for a training set and 30% for an internal validation set. The external cohort served exclusively as the external validation set. LASSO and logistic regression techniques were employed to select variables and construct the nomogram. The performance of the nomogram was evaluated using various methods, including C-index, calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CICA), to assess its identification, calibration, and clinical effectiveness. The prediction nomogram included several predictors, such as scar thickness, type of CSP, gestational sac diameter, and blood flow. It demonstrated strong discrimination, with a C-index of 0.83 (95% confidence interval: 0.77-0.89). Furthermore, in the internal validation set, a high C-index of 0.78 was achieved, while in the external validation set, it reached 0.83. Additional assessments using calibration curve analysis, DCA, and CICA indicated robust agreement between the nomogram's predictions and actual observations, highlighting its utility and reliability. The developed nomogram shows excellent discriminative ability and calibration, with the potential for effective local prediction of adverse events in CSP.

Scientific ReportsVol. 14(1)
Central South University (CN), Hunan University of Traditional Chinese Medicine (CN), Hunan University (CN), Shanghai University of Traditional Chinese Medicine (CN), First Affiliated Hospital of Hunan University of Traditional Chinese Medicine (CN), Yueyang Second People's Hospital (CN), Yueyang Hospital (CN), Third Xiangya Hospital (CN)
Reduced inequalities
Openalex Percentile: Top 14%
Ectopic Pregnancy Diagnosis and Management
1.63
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