Background: Acute non-traumatic chest pain is one of the common complaints in the emergency department and is closely associated with fatal disease. Triage assessment urgently requires the use of simple, rapid tools to screen patients with chest pain for high-risk condition to improve patient outcomes.
Methods: After data preprocessing and feature selection, univariate and multiple logistic regression analyses were performed to identify potential predictors associated with acute non-traumatic chest pain. A nomogram was built based on the predictors, and an internal evaluation was performed using bootstrap resampling methods. The model was also externally validated in this center. Furthermore, the model results were risk-stratified using the decision tree analysis to explore the corresponding triage level. Subsequently, we developed an online visualization tool based on the model to assess the risk of high risk in patients with chest pain.
Results: Multiple logistic regression analysis showed that age, smoking, coronary heart disease, hypertension, diabetes, hyperlipidemia, pain site, concomitant symptoms, and electrocardiograph, all of which are independent predictors of high-risk chest pain patients. The AUC of our model in the development and validation groups was 0.919 (95%CI: 0.891 ~ 0.974) and 0.904 (95%CI: 0.855 ~ 0.952). Moreover, our model demonstrated better outcomes in terms of accuracy/sensitivity in both cohorts (81.9%/85.2% and 94.8%/78.5%). The calibration curve shows a high degree of agreement between the predicted and actual probabilities. Decision curve analysis clarified that our model had higher net gains across the entire range of clinical thresholds. Afterward, we developed an online tool, which is used in the triage link to facilitate nurses to screen people with high-risk chest pain.
Conclusion: We proposed an accurate model to predict the high-risk populations with chest pain, based on which a simple and rapid online tool was developed and provided substantial support for its application as a decision-making tool for the emergency department.
Registration: The study protocol was approved by the Ethics Committee Board of Fujian Provincial Hospital.
Clinical Trial Registration Number: ChiCTR2200061918.
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http://dx.doi.org/10.1186/s12873-025-01176-1 | DOI Listing |
World J Gastrointest Endosc
January 2025
Department of Gastroenterology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China.
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Front Immunol
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Front Cardiovasc Med
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Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, China.
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View Article and Find Full Text PDFJ Cardiothorac Surg
January 2025
Division of Thoracic Surgery, Department of Surgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo-ku, 602-8566, Kyoto, Japan.
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BMC Surg
January 2025
Department of Cardiothoracic Surgery, Heart Center, School of Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University, Shanghai, China.
Purpose: An anomalous aortic origin of the coronary artery (AAOCA) is a rare congenital heart disease. Some high-risk anatomical structures are at risk of inducing cardiogenic shock or even sudden death. This article summarizes our surgical experience with AAOCA in paediatric patients.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!