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Establishment of a Charlson comorbidity index-based model for predicting the preterm premature rupture of the
Shu-Xin Zheng1, Xun Ren2, Qing-Qing Zhou3
1Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Insights
The Charlson Comorbidity Index (CCI) is a risk factor for preterm premature rupture of membranes (PPROM). A predictive model combining CCI and clinical factors shows good efficiency in forecasting PPROM.
Area of Science:
- Obstetrics and Gynecology
- Medical Informatics
- Epidemiology
Background:
- The Charlson Comorbidity Index (CCI) quantifies patient comorbidity severity.
- Preterm premature rupture of membranes (PPROM) is a significant obstetric complication.
- Understanding predictive factors for PPROM is crucial for clinical management.
Purpose of the Study:
- To evaluate the predictive capability of the CCI for PPROM.
- To develop and assess a risk prediction model for PPROM incorporating CCI and clinical variables.
Main Methods:
- Data sourced from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database.
- Statistical analyses included T-tests, ANOVA, chi-square tests, and collinearity analysis.
- Prediction efficiency was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and models like XGBoost, logistic regression, and Random Forest.
Main Results:
- The CCI was significantly higher in the PPROM group compared to the term premature rupture of membranes (TPROM) group.
- The CCI alone demonstrated limited predictive value for PPROM (AUC: 0.535).
- A multivariable model including CCI, platelet count, age, RDW, and CRP showed improved prediction efficiency for PPROM (AUC: 0.627).
Conclusions:
- The CCI is identified as a risk factor for PPROM.
- A risk prediction model integrating CCI with clinical features offers substantial predictive accuracy for PPROM.
Background:
The Charlson comorbidity index (CCI) is a tool used to quantitatively assess the severity of comorbidities in patients. This study aimed to explore the predictive value of the CCI in preterm premature rupture of the membrane (PPROM).
Methods:
Data were collected from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The continuous variables were analyzed using the T-test/one-way analysis of variance (ANOVA). Comparisons of categorical variables between groups were performed using the chi-square test. Colinearity analysis was used to exclude collinear variables. Receiver operating characteristic (ROC) and decision curve analysis (DCA) were used to assess the prediction efficiency. The prediction model was established by the extreme gradient boosting (XGBoost), logistic, and Random Forest on the independent impact factors, and the areas under the curve (AUC), accuracy, precision, specificity, and F1 were used to assess the prediction efficiency of the model.
Results:
CCI was significantly higher in the PPROM group than in the term premature rupture of membranes (TPROM) group. The ROC (AUC: 0.535) and DCA indicated that CCI was limited in predicting the PPROM in clinical practice. The results of the logistic analysis showed that the CCI, platelet, age, red blood cell distribution width (RDW), and C-reactive protein (CRP) were the independent influencing factors of PPROM. The ROC results showed that the CCI-based model had a better prediction efficiency in predicting the occurrence of PPROM (AUC: 0.627).
Conclusions:
CCI was a risk factor for the PPROM. In addition, a risk prediction model based on the CCI and clinical features had a good prediction efficiency for PPROM.
