Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study
Background Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and establish a predictive model for diagnosis of venous th...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2025.2457521 |
| _version_ | 1826851171315220480 |
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| author | Jie Yang Xu Zhang Jia Chen Xianghong Hou Minghong Shi Longlong Yin Longchun Hua Cheng Wang Xiaolong Han Shuyan Zhao Guolan Kang Ping Mai Rui Jiang Hongwei Tian |
| author_facet | Jie Yang Xu Zhang Jia Chen Xianghong Hou Minghong Shi Longlong Yin Longchun Hua Cheng Wang Xiaolong Han Shuyan Zhao Guolan Kang Ping Mai Rui Jiang Hongwei Tian |
| author_sort | Jie Yang |
| collection | DOAJ |
| description | Background Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and establish a predictive model for diagnosis of venous thrombosis clinical by routine blood tests and endoscopic characteristics.Methods Patients from Gansu Provincial Hospital from October 2019 to December 2023 were enrolled. The retrospective modelling cohort was screened by propensity score matching (PSM) at a 1:1 ratio from the baseline characteristics before endoscopic diagnosis. Variables were collected from blood test and endoscopic signs using machine learning method (ML). Logistic regression determined risk factors. The predictive performance was evaluated by receiver operation curve (ROC), calibration curve, clinical decision analysis (DCA) and influence curve (CIC). Furthermore, external cohort was used for validation, an online nomogram was established.Results A total of 1,058 patients were enrolled, and 470 patients were included after PSM 1: 1. The model identified 7 factors, including splenectomy, blood urea nitrogen (BUN), serum sodium, activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and degree of oesophageal varices. The area under the curve (AUC) was 0.907 (95% CI, 0.877–0.931). The calibration curve, decision and clinical impact curves showed the model demonstrated a good predictive accuracy and clinical benefits. The validation got an AUC of 0.890 (95% CI, 0.831–0.934), A nomogram tool was finally established for application.Conclusion Blood test combined endoscopic characters could preliminarily predict the liver cirrhosis with portal vein thrombosis for cirrhotic patients undergoing endoscopic examination. |
| first_indexed | 2025-02-16T16:36:06Z |
| format | Article |
| id | doaj.art-c61955a397f045c5b901b8e0a4a1274b |
| institution | Directory Open Access Journal |
| issn | 0785-3890 1365-2060 |
| language | English |
| last_indexed | 2025-02-16T16:36:06Z |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj.art-c61955a397f045c5b901b8e0a4a1274b2025-01-30T06:17:34ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602025-12-0157110.1080/07853890.2025.2457521Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort studyJie Yang0Xu Zhang1Jia Chen2Xianghong Hou3Minghong Shi4Longlong Yin5Longchun Hua6Cheng Wang7Xiaolong Han8Shuyan Zhao9Guolan Kang10Ping Mai11Rui Jiang12Hongwei Tian13Endoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaDepartment of Gastroenterology, Third People’s Hospital of Yuzhong County, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaEndoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou, Gansu, ChinaBackground Liver cirrhosis complicated by portal vein thrombosis (PVT) is a fatal complication with no specific manifestations but often misdiagnosed, it crucially increases the mortality worldwide. This study aimed to identify risk factors and establish a predictive model for diagnosis of venous thrombosis clinical by routine blood tests and endoscopic characteristics.Methods Patients from Gansu Provincial Hospital from October 2019 to December 2023 were enrolled. The retrospective modelling cohort was screened by propensity score matching (PSM) at a 1:1 ratio from the baseline characteristics before endoscopic diagnosis. Variables were collected from blood test and endoscopic signs using machine learning method (ML). Logistic regression determined risk factors. The predictive performance was evaluated by receiver operation curve (ROC), calibration curve, clinical decision analysis (DCA) and influence curve (CIC). Furthermore, external cohort was used for validation, an online nomogram was established.Results A total of 1,058 patients were enrolled, and 470 patients were included after PSM 1: 1. The model identified 7 factors, including splenectomy, blood urea nitrogen (BUN), serum sodium, activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and degree of oesophageal varices. The area under the curve (AUC) was 0.907 (95% CI, 0.877–0.931). The calibration curve, decision and clinical impact curves showed the model demonstrated a good predictive accuracy and clinical benefits. The validation got an AUC of 0.890 (95% CI, 0.831–0.934), A nomogram tool was finally established for application.Conclusion Blood test combined endoscopic characters could preliminarily predict the liver cirrhosis with portal vein thrombosis for cirrhotic patients undergoing endoscopic examination.https://www.tandfonline.com/doi/10.1080/07853890.2025.2457521Liver cirrhosisportal vein thrombosisendoscopicprediction model |
| spellingShingle | Jie Yang Xu Zhang Jia Chen Xianghong Hou Minghong Shi Longlong Yin Longchun Hua Cheng Wang Xiaolong Han Shuyan Zhao Guolan Kang Ping Mai Rui Jiang Hongwei Tian Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study Annals of Medicine Liver cirrhosis portal vein thrombosis endoscopic prediction model |
| title | Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study |
| title_full | Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study |
| title_fullStr | Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study |
| title_full_unstemmed | Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study |
| title_short | Development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data: a retrospective propensity score matching (PSM) cohort study |
| title_sort | development and validation of an integrated model for the diagnosis of liver cirrhosis with portal vein thrombosis combined with endoscopic characters and blood biochemistry data a retrospective propensity score matching psm cohort study |
| topic | Liver cirrhosis portal vein thrombosis endoscopic prediction model |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2025.2457521 |
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