AST to Platelet Ratio Index (APRI) is an easy-to-use predictor score for cardiovascular risk in metabolic subjects

Abstract

Visceral obesity is characterized by a low-grade inflammatory systemic state that contributes to the genesis of non-alcoholic fatty liver disease (NAFLD), frequently associated with liver fibrosis. Non-invasive serum markers have recently emerged as reliable, easy-to-use scores to predict liver fibrosis. NAFLD is often linked to metabolic and cardiovascular risk. Thus, in this cross-sectional study, we investigated in a population of 1225 subjects if AST to Platelet Ratio Index (APRI), one of the non-invasive liver fibrosis serum markers, can predict cardiovascular risk (CVR). APRI has been previously validated as an efficient score to predict liver fibrosis in viral hepatitis patients with a cut-off of 0.5 for fibrosis and 1.5 for cirrhosis. Our study showed that APRI significantly correlates with CVR and determines, when elevated, a significant increase in CVR for both genders, especially females. This spike in CVR, observed when APRI is elevated, is relatively high in patients in the age of 51-65 years, but it is significantly higher in younger and premenopausal women, approaching risk values usually typical of men at the same age. Taken together, our data highlighted the role of APRI as a reliable predictor easy-to-use score for CVR in metabolic patients.

Figure 1

Flowchart of study population and graphic representation of APRI score values. (a) Flowchart of the study population. (b) T-Test comparison of entire study population. Subjects categorized based on Metabolic Syndrome (MetS) diagnosis; non-metabolic (MetS NO) subjects = n.685, MetS (MetS YES) patients = n.540. Data is presented as mean ± SEM; **p < 0.01. (c) Comparison of APRI levels. Subjects were categorized based on positivity for MetS criteria. 0 criteria = n.186, 1 criterion = n.240, 2 criteria = n.259, 3 criteria = n.283, 4 criteria = n.171, 5 criteria = n.86. Data is presented as mean ± SEM. Comparison of groups was performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Data from groups sharing the same lowercase letter were not significantly different, whereas data from groups with different case letter were significantly different (p < 0.05).

Figure 2

APRI score levels analyzed by single MetS criterion and BMI cut-offs. (a) Comparison of APRI values according to BMI definition. Subjects were divided in three different categories. Healthy = n. 412, Overweight = n. 421, Obese = n.305. Data is presented as mean ± SEM. Comparison of groups was performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Data from groups sharing the same lowercase letters were not significantly different, whereas data from groups with different case letters were significantly different (p < 0.05). (b–f) T-Test comparison of APRI values in subjects divided by positivity for each MetS criterion according to IDF definition. Data is presented as mean ± SEM. *p < 0.05, **p < 0.01.

Figure 3

Correlation between APRI score and cardiovascular risk in general population and classification by age. (a) Correlation analysis of APRI and cardiovascular risk (CVR) in the entire study population. (b) Classification of entire study population in age ranges; subjects were divided by APRI levels with a cut-off of 0.5 to identify elevated APRI. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (*p < 0.05, **p < 0.01). Multipliers are shown to identify difference in CVR in subjects with APRI > 0.5 compared to subjects with APRI < 0.5 of the same age. (c) Correlation of APRI and CVR after removal of patients ongoing anticoagulant or antiplatelet treatment.

Figure 4

Correlation between APRI > 0.5 and cardiovascular risk in non-metabolic and metabolic subjects, classification by age and comparison in prediabetes and Diabetes Mellitus subjects. (a,b) Correlation analysis of APRI and cardiovascular risk (CVR) in non-metabolical (MetS NO) and MetS (MetS YES) subjects with APRI > 0.5. (c) Classification of MetS subjects in age ranges; subjects were divided by APRI levels with a cut-off of 0.5 to identify elevated APRI. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (**p < 0.01). Multipliers are shown to identify difference in CVR in subjects with APRI > 0.5 compared to subjects with APRI < 0.5 of the same age. (d) Comparison of CVR in healthy and Diabetes Mellitus (DM) subjects divided by APRI levels. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (*p < 0.05, **p < 0.01). Multipliers are shown to identify difference in CVR in subjects with APRI > 0.5 compared to subjects with APRI < 0.5 of the same age. (e) Comparison of CVR in PreDiabetes (preDM), Diabetes Mellitus (DM) and Metabolic (MetS) subjects divided by APRI levels. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (*p < 0.05, **p < 0.01). Multipliers are shown to identify difference in CVR in subjects with APRI > 0.5 compared to subjects with APRI < 0.5 of the same group.

Figure 5

Gender-based comparison of cardiovascular risk in different groups. (a–d) T-Test comparison of CVR in non-metabolic (MetS NO) (a), MetS (MetS YES) (b), non-metabolic (MetS NO) with APRI > 0.5 (c) and MetS (MetS YES) subjects with APRI > 0.5 (d). Subjects were divided based on gender. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (**p < 0.01). Multipliers are shown to identify difference in CVR in males compared to females.

Figure 6

Cardiovascular risk analysis by gender and age. (a–d) T-Test comparison of CVR in non-metabolic (MetS NO) subjects (a), MetS (MetS YES) subjects (b), non-metabolic (MetS NO) subjects with APRI > 0.5 (c) and MetS (MetS YES) subjects with APRI > 0.5 (d). Subjects were divided based on gender and age. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (*p < 0.05, **p < 0.01).. Multipliers are shown to identify difference in CVR in males compared to females.

Figure 7

Characterization of cardiovascular risk in adults age 18–50 based on gender and APRI score levels. T-Test analysis of CVR in females and males age 18–50. Subjects were divided based on MetS diagnosis and APRI levels. Data is presented as mean ± SEM. Statistical significance was assessed by Student T-test (*p < 0.05, **p < 0.01). Multipliers are shown to identify difference in CVR in males compared to females.