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Parasitology International 2013-Jun

A simple noninvasive index to predict significant liver fibrosis in patients with advanced schistosomiasis japonica.

Només els usuaris registrats poden traduir articles
Inicieu sessió / registreu-vos
L'enllaç es desa al porta-retalls
Yi-ming Wu
Nuo Xu
Jie-yun Hu
Xiao-fei Xu
Wan-xin Wu
Shu-xing Gao
Wen-jun Zhu
Wen-lin Wu
Xi-zhong Shen
Ji-yao Wang

Paraules clau

Resum

BACKGROUND

Schistosoma japonicum causes marked liver fibrosis, while lethal syndromes present in advanced schistosomiasis patients. Its management depends on the degree of fibrosis present.

METHODS

Fifty-two patients were recruited to assess the diagnostic value of bio-markers in patients with advanced schistosomiasis japonica. Fibrosis was assessed in liver biopsies using METAVIR system. The correlation between conventional parameters and significant fibrosis (F2-F4) was assessed using univariate analysis and logistic regression. The method of area under receiver operating characteristic curves (AUROCs) was used as a measurement of diagnostic efficacy.

RESULTS

White blood cell counts, platelet counts and albumin (all P<0.05) were significantly lower, while prothrombin time, international normalized ratio (INR), hyaluronic acid (HA), IV collagen and ultrasound fibrosis scores (all P<0.01) were significantly elevated in F2-F4 patients compared with F0-F1 patients. HA and INR were identified as independent predictors by multivariate analysis (P=0.023 and P=0.013, respectively). Of the routine laboratory tests for the diagnosis of significant fibrosis, HA gave the best AUROC of 0.875 (95% confidence interval (CI): 0.701-0.997). We constructed a new simple index (INR×HA/100) to discriminate between F2-F4 patients and F0-F1 patients. It showed the highest AUROC of 0.921 (95% CI: 0.828-1.000), and had better diagnostic values than APRI and FIB-4.

CONCLUSIONS

HA and INR were reliable markers for differentiating significant liver fibrosis in patients with advanced schistosomiasis japonica. And the new simple index can easily predict significant liver fibrosis with a high degree of accuracy.

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