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  • Title: [Analysis of the predictive value of plateletcrit for the degree of liver fibrosis in patients with chronic HBV infection with ALT less than two times the upper limit of normal].
    Author: Wang B, Li Y, Xiao L, Xu HT, Xian JC.
    Journal: Zhonghua Gan Zang Bing Za Zhi; 2023 Aug 20; 31(8):862-868. PubMed ID: 37723069.
    Abstract:
    Objective: Plateletcrit (PCT) is considered a new potential index to predict the degree of liver fibrosis in patients with chronic hepatitis B (CHB). This study aimed to explore the predictive value of PCT for the degree of liver fibrosis in patients with chronic hepatitis B virus (HBV) infection with alanine aminotransferase (ALT) < 2× upper limit of normal (ULN). Measurement data were compared using the t-test, ANOVA, or non-parametric test (Mann-Whitney U test). Categorical variables were compared using χ (2) test or Fisher's exact test. Methods: 140 cases with chronic HBV infection who underwent liver biopsy and ALT < 2×ULN were enrolled from January 2016 to March 2021. Univariate and multivariate logistic regression and the area under the receiver operating characteristic curve (AUC) were used to determine the predictive value of PCT for the degree of liver fibrosis. The likelihood ratio (LR) was used to optimize the selection of the diagnostic cut-off. Results: (1) Among the 140 cases, there were 34 (24.3%) cases in the S0 stage, 47 (33.6%) cases in the S1 stage, 16 (11.4%) cases in the S2 stage, 19 (13.6%) cases in the S3 stage, and 24 (17.1%) cases in the S4 stage. The overall mean PCT level was 0.19 ± 0.06%. (2) Univariate analysis revealed that PCT between patients with stages of liver fibrosis was S(0-1) and S(2-4) (0.20% ± 0.05% vs. 0.16% ± 0.06%, t = 3.955, P < 0.001), S(0 -2) and S(3-4) (0.20% ± 0.05% vs. 0.15% ± 0.06%, t = 5.631, P < 0.001) and S(0-3) and S4 (0.20% ± 0.05% vs. 0.12% ± 0.05%, t = 7.113, P < 0.001), respectively, and the differences were statistically significant. Multivariate logistic regression analysis showed that PCT was an independent risk factor for liver fibrosis stages S(2-4), S(3-4), and S4 (OR = 0.925, 95% CI: 0.859 - 0.997, P = 0.042; OR = 0.867, 95% CI: 0.789 - 0.954, P = 0.003; OR = 0.708, 95% CI: 0.593 - 0.846; P < 0.001). (3) The AUCs of PCT were 0.702, 0.777, and 0.885 for diagnosing liver fibrosis stages S(2-4), S(3-4), and S4 in patients with chronic HBV infection with ALT < 2×ULN. PCT was superior for the cirrhosis (S4) diagnosis. 92 (65.7%) cases were diagnosed as cirrhosis or non-cirrhosis according to the LR optimized diagnostic and exclusion diagnostic cut-offs (≤0.09%, ≤0.17%), with an accuracy of 97.8%. Conclusion: PCT has a high diagnostic and exclusion value for cirrhotic patients with chronic HBV infection with ALT < 2×ULN. Furthermore, it can be used as a non-invasive diagnostic index for determining and assisting the diagnosis of cirrhosis in resource-constrained areas, reducing the need for pathological examination of liver biopsies, and it has the advantage of being simple and intuitive without complex calculations. 目的: 探讨血小板压积(PCT)对丙氨酸转氨酶(ALT)<2×正常值上限(ULN)慢性乙型肝炎病毒(HBV)感染者肝纤维化程度的预测价值。 方法: 入组患者:2016年1月至2021年3月行肝活检且ALT<2×ULN的慢性HBV感染者140例,收集患者血清学和病理学检查结果。采用单因素、多因素logistic回归及受试者操作特征曲线下面积(AUC)判断PCT对肝纤维化程度的预测价值,并运用似然比(LR)优化诊断界值的选择。计量资料用t检验、方差分析或非参数检验(Mann-Whitney U检验)进行比较;分类变量用χ(2)检验或确切概率法进行比较。 结果: (1)140例患者中,S0期34例(24.3%),S1期47例(33.6%),S2期16例(11.4%),S3期19例(13.6%),S4期24例(17.1%),总体平均PCT水平为0.19%±0.06%。(2)单因素分析显示PCT在肝纤维化分期S(0~1)和S(2~4)患者间(0.20%±0.05%与0.16%±0.06%,t = 3.955,P < 0.001)、S(0~2)和S(3~4)患者间(0.20%±0.05%与0.15%±0.06%,t = 5.631,P < 0.001)以及S(0~3)和S4患者间(0.20%±0.05%与0.12%±0.05%,t = 7.113,P < 0.001)的差异均具有统计学意义。多因素logistic回归分析表明PCT为肝纤维化S(2~4)、S(3~4)及S4期的独立危险因素(OR = 0.925,95% CI: 0.859~0.997,P = 0.042;OR = 0.867,95% CI: 0.789~0.954,P = 0.003;OR = 0.708,95% CI: 0.593~0.846;P < 0.001)。(3)PCT在诊断ALT<2×ULN慢性HBV感染者肝纤维化S(2~4)、S(3~4)及S4期的AUC分别为0.702、0.777、0.885。PCT在诊断肝硬化(S4)中表现最佳,根据LR优化的诊断及排除诊断界值(≤0.09%、≤0.17%)可以使92例(65.7%)患者诊断为肝硬化或非肝硬化,准确性可达97.8%。 结论: PCT对ALT<2×ULN慢性HBV感染者肝硬化具有较高的诊断及排除诊断价值,可作为资源受限地区辅助判断肝硬化的无创诊断指标,减少了对肝活检的需求,且具备简便直观、无需复杂计算的优势。.
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