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A prediction model to predict in-hospital mortality in patients with acute type B aortic dissection
Meng-Meng Wang1,2, Min-Tao Gai2,3, Bao-Zhu Wang1
1Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Insights
A new prediction model for acute type B aortic dissection (ABAD) identifies key factors to assess in-hospital death risk. This tool aids clinicians in evaluating patient outcomes for this critical cardiovascular condition.
Area of Science:
- Cardiovascular Medicine
- Medical Prediction Modeling
- Thoracic Surgery
Background:
- Acute type B aortic dissection (ABAD) is a severe cardiovascular condition requiring effective risk stratification.
- There is a clinical need for a reliable model to predict in-hospital mortality in ABAD patients.
- This study focuses on developing such a predictive tool.
Purpose of the Study:
- To construct and validate a prediction model for in-hospital death risk in patients diagnosed with ABAD.
- To identify independent predictors of mortality in ABAD.
- To provide a practical tool for clinical risk assessment.
Main Methods:
- Retrospective analysis of 715 ABAD patients from April 2012 to May 2021.
- Logistic regression, ROC curve analysis, and nomogram construction were used to develop the prediction model.
- Model performance was validated using ROC curves and calibration plots.
Main Results:
- In-hospital death occurred in 7.41% of patients.
- Significant differences in DBP, platelets, heart rate, neutrophil-lymphocyte ratio, D-dimer, CRP, WBC, hemoglobin, LDH, procalcitonin, and LVEF were observed between survival and death groups.
- LVEF, WBC, hemoglobin, LDH, and procalcitonin were identified as independent predictors of in-hospital death, with the model showing good discriminative ability (C-index = 0.745).
Conclusions:
- A novel prediction model incorporating WBC, hemoglobin, LDH, procalcitonin, and LVEF is a valuable tool for predicting in-hospital mortality in ABAD patients.
- This model offers a practical approach to risk stratification and clinical decision-making in ABAD management.
- Further validation and implementation in clinical practice are warranted.
Background:
Acute type B aortic dissection (ABAD) is a life-threatening cardiovascular disease. A practicable and effective prediction model to predict and evaluate the risk of in-hospital death for ABAD is required. The present study aimed to construct a prediction model to predict the risk of in-hospital death in ABAD patients.
Methods:
A total of 715 patients with ABAD were recruited in the first affiliated hospital of Xinjiang medical university from April 2012 to May 2021. The information on the demographic and clinical characteristics of all subjects was collected. The logistic regression analysis, receiver operating characteristic (ROC) curve analysis, and nomogram were applied to screen the appropriate predictors and to establish a prediction model for the risk of in-hospital mortality in ABAD. The receiver operator characteristic curve and calibration plot were applied to validate the performance of the prediction model.
Results:
Of 53 (7.41%) subjects occurred in-hospital death in 715 ABAD patients. The variables including diastolic blood pressure (DBP), platelets, heart rate, neutrophil-lymphocyte ratio, D-dimer, C-reactive protein (CRP), white blood cell (WBC), hemoglobin, lactate dehydrogenase (LDH), procalcitonin, and left ventricular ejection fraction (LVEF) were shown a significant difference between the in-hospital death group and the in-hospital survival group (all P < 0.05). Furthermore, all these factors which existed differences, except CRP, were associated with in-hospital deaths in ABAD patients (all P < 0.05). Then, parameters containing LVEF, WBC, hemoglobin, LDH, and procalcitonin were identified as independent risk factors for in-hospital deaths in ABAD patients by adjusting compound variables (all P < 0.05). In addition, these independent factors were qualified as predictors to build a prediction model (AUC > 0.5, P < 0.05). The prediction model was shown a favorable discriminative ability (C index = 0.745) and demonstrated good consistency.
Conclusions:
The novel prediction model combined with WBC, hemoglobin, LDH, procalcitonin, and LVEF, was a practicable and valuable tool to predict in-hospital deaths in ABAD patients.
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