Value of a risk assessment model in predicting venous thromboembolism in patients with liver failure after artificial liver support therapy
10.3969/j.issn.1001-5256.2023.03.019
- VernacularTitle:风险评估模型预测人工肝治疗肝衰竭患者发生静脉血栓栓塞症的价值分析
- Author:
Sufang LU
1
;
Rui HUANG
1
;
Hongli ZHAO
1
;
Dandan WANG
1
;
Yuzhen DING
1
;
Hong ZHOU
1
Author Information
1. Department of Infectious Diseases, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China
- Publication Type:Original Article_Other Liver Disease
- Keywords:
Liver Failure;
Venous Thromboembolism;
Liver, Artificial;
Risk Factors;
Models, Statistical
- From:
Journal of Clinical Hepatology
2023;39(3):613-619
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of a risk assessment model in predicting venous thromboembolism (VTE) in patients with liver failure after artificial liver support therapy. Methods A retrospective analysis was performed for the clinical data of 124 patients with liver failure who received artificial liver support therapy in Affiliated Drum Tower Hospital of Nanjing University Medical School from March 2019 to December 2021, among whom there were 41 patients with VTE (observation group) and 143 patients without VTE (control group). Related clinical data were compared between the two groups, and the Caprini risk assessment model was used for scoring and risk classification of the patients in both groups. The t -test was used for comparison of continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups; the Mann-Whitney U rank sum test was used for comparison of ranked data between two groups. The logistic regression analysis was used to investigate the independent risk factors for VTE in patients with liver failure after artificial liver support therapy. The receiver operating characteristic (ROC) curve was used to investigate the value of Caprini score and the multivariate predictive model used alone or in combination in predicting VTE. Results The observation group had a significantly higher Caprini score than the control group (4.39±1.10 vs 3.12±1.04, t =6.805, P < 0.001). There was a significant difference between the two groups in risk classification based on Caprini scale ( P < 0.05), and the patients with high risk or extremely high risk accounted for a higher proportion among the patients with VTE. The univariate analysis showed that there were significant differences between the two groups in age ( t =6.400, P < 0.001), catheterization method ( χ 2 =14.413, P < 0.001), number of times of artificial liver support therapy ( Z =-4.720, P < 0.001), activity ( Z =-6.282, P < 0.001), infection ( χ 2 =33.071, P < 0.001), D-dimer ( t =8.746, P < 0.001), 28-day mortality rate ( χ 2 =5.524, P =0.022). The multivariate analysis showed that number of times of artificial liver support therapy (X 1 ) (odds ratio [ OR ]=0.251, 95% confidence interval [ CI ]: 0.111-0.566, P =0.001), activity (X 2 ) ( OR =0.122, 95% CI : 0.056-0.264, P < 0.001), D-dimer (X 3 ) ( OR =2.921, 95% CI : 1.114-7.662, P =0.029) were independent risk factors for VTE in patients with liver failure after artificial liver support therapy. The equation for individual predicted probability was P =1/[1+e -(7.425-1.384X 1 -2.103X 2 +1.072X 3 ) ]. The ROC curve analysis showed that Caprini score had an area under the ROC curve of 0.802 (95% CI : 0.721-0.882, P < 0.001), and the multivariate model had an area under the ROC curve of 0.768 (95% CI : 0.685-0.851, P < 0.001), while the combination of Caprini score and the multivariate model had an area under the ROC curve of 0.957 (95% CI : 0.930-0.984, P < 0.001). Conclusion The Caprini risk assessment model has a high predictive efficiency for the risk of VTE in patients with liver failure after artificial liver support therapy, and its combination with the multivariate predictive model can significantly improve the prediction of VTE.
