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Zhang X, Yue P, Zhang J, Yang M, Chen J, Zhang B, Luo W, Wang M, Da Z, Lin Y, Zhou W, Zhang L, Zhu K, Ren Y, Yang L, Li S, Yuan J, Meng W, Leung JW, Li X. A novel machine learning model and a public online prediction platform for prediction of post-ERCP-cholecystitis (PEC). EClinicalMedicine 2022; 48:101431. [PMID: 35706483 PMCID: PMC9112124 DOI: 10.1016/j.eclinm.2022.101431] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 03/31/2022] [Accepted: 04/12/2022] [Indexed: 12/07/2022] Open
Abstract
BACKGROUND Endoscopic retrograde cholangiopancreatography (ERCP) is an established treatment for common bile duct (CBD) stones. Post- ERCP cholecystitis (PEC) is a known complication of such procedure and there are no effective models and clinical applicable tools for PEC prediction. METHODS A random forest (RF) machine learning model was developed to predict PEC. Eligible patients at The First Hospital of Lanzhou University in China with common bile duct (CBD) stones and gallbladders in-situ were enrolled from 2010 to 2019. Logistic regression analysis was used to compare the predictive discrimination and accuracy values based on receiver operation characteristics (ROC) curve and decision and clinical impact curve. The RF model was further validated by another 117 patients. This study was registered with ClinicalTrials.gov, NCT04234126. FINDINGS A total of 1117 patients were enrolled (90 PEC, 8.06%) to build the predictive model for PEC. The RF method identified white blood cell (WBC) count, endoscopic papillary balloon dilatation (EPBD), increase in WBC, residual CBD stones after ERCP, serum amylase levels, and mechanical lithotripsy as the top six predictive factors and has a sensitivity of 0.822, specificity of 0.853 and accuracy of 0.855, with the area under curve (AUC) value of 0.890. A separate logistic regression prediction model was built with sensitivity, specificity, and AUC of 0.811, 0.791, and 0.864, respectively. An additional 117 patients (11 PEC, 9.40%) were used to validate the RF model, with an AUC of 0.889 compared to an AUC of 0.884 with the logistic regression model. INTERPRETATION The results suggest that the proposed RF model based on the top six PEC risk factors could be a promising tool to predict the occurrence of PEC.
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Affiliation(s)
- Xu Zhang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
| | - Ping Yue
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Jinduo Zhang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Man Yang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Clinical Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
| | - Jinhua Chen
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
| | - Bowen Zhang
- State Key Laboratory of Applied Organic Chemistry, Lanzhou University, Lanzhou, 730030 , Gansu, China
| | - Wei Luo
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
| | - Mingyuan Wang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of Ultrasonography, The First Hospital of Lanzhou University, Lanzhou, 730030, Gansu, China
| | - Zijian Da
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
| | - Yanyan Lin
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Wence Zhou
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Lei Zhang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Kexiang Zhu
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
| | - Yu Ren
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
| | - Liping Yang
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
| | - Shuyan Li
- School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
- Corresponding author.
| | - Jinqiu Yuan
- Clinical Research Center, Big Data Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong, China
- Corresponding author.
| | - Wenbo Meng
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
- Corresponding author at: The First School of Clinical Medcine, Lanzhou University. Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
| | - Joseph W. Leung
- Division of Gastroenterology, UC Davis Medical Center and Sacramento VA Medical Center, Sacramento, 95817, CA, USA
| | - Xun Li
- The First School of Clinical Medicne, Lanzhou University, Lanzhou,730030, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730030,Gansu, China
- Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine Transformation, Lanzhou,730030, Gansu, China
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