Effects of statins on major adverse cardiovascular events, metabolic and inflammatory parameters in patients with hepatitis B virus comorbid with cardiovascular disease

Introduction

Coronary heart disease (CHD) is the primary cause of mortality in humans and accounts for approximately 9 million deaths annually worldwide (1). The definition of CHD encompasses cardiovascular conditions resulting from the narrowing or obstruction of the coronary arteries due to atherosclerosis, as well as myocardial ischemia, hypoxia, or necrosis caused by functional alterations in these arteries (2). There is a prevailing belief within the academic community that the presence of obesity, smoking, and alcohol consumption are critical contributors to the progression of CHD (3,4). Furthermore, hypertension, hyperlipidemia, hypercholesterolemia, and diabetes mellitus (DM) have also been identified as key risk factors for CHD (5-8). Among these, DM is particularly significant, as the elevated blood glucose levels experienced by individuals with this condition often induce oxidative stress and inflammatory harm, ultimately resulting in atherosclerosis, coronary artery dysfunction, myocardial infarction (MI), and cellular impairment, thereby fostering the progression of CHD (9). DM has also been linked to an unfavorable long-term prognosis in individuals diagnosed with CHD. In comparison to patients without DM, those with DM complicated by CHD exhibit a higher mortality rate over a span of 10 years (10). In particular, DM presents in more than 35% of elderly patients over 70 years old and those with abnormal lipids’ profile, contributing to adverse cardiovascular events and panvascular atherosclerosis (11).

The global prevalence of hepatitis B virus (HBV) infection is substantial and a significant concern for public health. Prolonged HBV infection can result in chronic hepatitis, cirrhosis, and hepatocellular carcinoma (12). Chronic HBV infection is characterized by a state of inflammation, which has been observed to elevate the likelihood of major adverse cardiovascular events (MACEs) and cerebrovascular disease in patients with other conditions featuring chronic low-grade inflammation (13,14). Several studies have examined the association between HBV infection and cardiovascular disease (CVD); however, the findings have been inconclusive (15-18). A study has identified a positive correlation between HBV infection and coronary artery disease (18), whereas others have indicated a negative correlation (15-17). In individuals diagnosed with chronic viral hepatitis, it has been observed that those with hepatitis C virus (HCV) infection exhibit a notably elevated susceptibility to composite arterial events and all-cause mortality when compared to those with HBV infection (19,20). Furthermore, no substantial association has been found between HBV infection status and the prevalence of macrovascular complications, microvascular complications of diabetes, diabetic ketosis, or diabetic ketoacidosis (21). Therefore, further investigation into the correlation between HBV infection and MACEs is critical.

Statins have demonstrated efficacy in mitigating the occurrence of CVD and are recommended as the primary therapeutic approach for hypercholesterolemia in clinical guidelines (22,23). Based on comprehensive analysis of statin’s lipid-lowering effects across various clinical trials and direct comparisons, the American College of Cardiology/American Heart Association guidelines for the management of blood cholesterol levels in minimizing the risk of atherosclerotic CVD (ASCVD) in adults classify statins into low, moderate, and high potency categories. High-potency statins, such as rosuvastatin administered at doses of 20 and 40 mg/d and atorvastatin at doses of 40 and 80 mg/d, can yield a marked decrease in low-density lipoprotein cholesterol (LDL-C) levels surpassing 50% (22). Additionally, statins’ lowering of cholesterol levels may impede the progression of hepatic fibrosis by ameliorating portal hypertension and reducing the excessive accumulation of hepatic triglycerides (24-26). Numerous clinical studies have demonstrated the efficacy of statin administration in patients with nonalcoholic fatty liver disease (NAFLD), which can lead to improvements in liver function tests (27-29). The independent association of statin use with reductions in hepatic steatosis and fibrosis stage in patients with NAFLD has also been reported (27,29). Finally, the pathogenesis of hepatic fibrosis is characterized by a multifaceted interaction between lipid metabolism and systemic chronic inflammatory response in patients with CVD (30,31).

This study aimed to collect clinical data from patients with comorbid HBV infection and CVD, as well as those with CVD alone, to clarify whether statin use improves MACEs. Furthermore, the effects of statins on hepatic fibrosis and systemic inflammation remain incompletely understood. Consequently, the identification of suitable biomarkers is critical for monitoring the progression of hepatic fibrosis and systemic inflammatory status in CVD patients undergoing statin therapy. We present this article in accordance with the STROBE reporting checklist (available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-63/rc).

Methods

Study design and participants

A prospective cohort study was conducted to examine the prevalence, incidence, and associated factors, such as HBV infection, in relation to CVD. The subjects were patients with CVD who were hospitalized at The First Affiliated Hospital of Xi’an Jiaotong University from June 2020 to August 2023. The average follow-up time was 1.5 years. This study was approved by the Ethics Committee of The First Affiliated Hospital of Xi’an Jiaotong University (No. XJTU1AF2024LSYY-054). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Informed consent was waived by the Institutional Review Board given the retrospective study design. Inclusion criteria: all subjects met the diagnostic criteria for CVD (22); with a clear diagnosis of HBV infection (32); and with complete clinical data. Exclusion criteria included: age <18 years; pregnant women; absence of hepatitis B surface antigen test; potential immune-related diseases such as leukemia, autoimmune diseases, or any other hematological disorders; infection with HCV, human immunodeficiency virus (HIV), or syphilis; malignant tumors, hepatic hemangiomas, thyroid dysfunction; chronic renal insufficiency; incomplete medication information.

Clinical data collection and measurements

The variables considered in this study included patient demographics, such as age and gender, and medical factors, such has hypertension, smoking/alcohol consumption, diabetes, disease status, biochemical indicators, blood cell indicators, HBV five-item quantitative test, the HBV-DNA quantitative test, statin use, antiviral therapy for hepatitis B, and MACEs. Clinical data were collected from the electronic medical record system. The ratios of platelet count (PLT) to lymphocyte count (PLR) and neutrophil count to lymphocyte count (NLR) were calculated to assess certain adverse cardiovascular events, such as recurrent angina pectoris (AP), hospitalization for unstable angina pectoris (UAP), acute MI (AMI), MI, severe arrhythmia, heart failure (HF), and death due to CHD. Primary clinical outcomes included recurrent AP, UAP requiring hospitalization, AMI, MI, severe arrhythmia, HF, and coronary-related death, among others, which were diagnosed according to the guidelines (33-37). Secondary clinical outcomes included Killip classification II–IV or New York Heart Association (NYHA) classification II–IV.

All specimens were tested within 2 hours following their collection. In cases for which immediate testing was not feasible, specimens were stored at a temperature of –20 ℃ for a duration not exceeding 2 days. The fluorescence quantitative polymerase chain reaction (PCR) detection of HBV-DNA load was conducted with the 7500 fluorescence quantitative PCR instrument and associated reagents (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA). Quantitative determination of biochemical indicators was performed using the AU5600 automatic biochemical analyzer and its corresponding original reagents (Beckman Coulter, Inc., Brea, CA, USA). The quantification of the five components of serum hepatitis B was performed using an i2000SR system (Abbott Laboratories, Chicago, IL, USA). The detection of blood cell indicators was conducted in routine fashion with a CAL 8000 automatic flow cytometer (Mindray, Shenzhen, China). The cobas e 801 automatic immunoassay analyzer (Roche, Basel, Switzerland) along with original reagents, was used for the quantitative determination of B-type natriuretic peptide (BNP) in the anterior brain. All aforementioned measurements were performed in accordance with the manufacturer’s instructions.

Calculations of the albumin-bilirubin index (ALBI) score, fibrosis 4 index (FIB-4), complete blood count-derived inflammation index, and atherogenic indices

Noninvasive and nondestructive testing markers, including FIB-4, ALBI, complete blood count-derived inflammation indices (CBCIIs) [e.g., platelet-monocyte ratio (PMR), NLR, systemic immune inflammation index (SII), systemic inflammatory response index (SIRI), and the aggregate index of systemic inflammation (AISI)], and atherogenic indices [e.g., the atherogenic index of plasma (AIP), atherogenic index (AI), Castelli risk index-I (CRI-I), CRI-II, and triglyceride-rich lipoprotein cholesterol (TRL-C)] were used to evaluate the effects of statin use on hepatic fibrosis, systemic inflammation, and arteriosclerotic degree in patients with CVD. The formulae for calculating the hepatic fibrosis indicators, ALBI score, and FIB-4 index are described elsewhere (38). CBCIIs, including SIRI, SII, AISI, SIRI/HDL-C, and SIRI×LDL-C, were calculated as described previously (39,40), as were atherogenic indices, such as adjusted AIP, AIP, AI, CRI-I, CRI-II, LCI, and TRL-C (41-44).

Statistical analysis

Measurement data that conformed to a normal distribution were expressed as the mean ± standard deviation, and intergroup comparison were conducted via t-test. Conversely, measurement data that did not adhere to a normal distribution were expressed as the median and interquartile range [IQR; P₅₀ (P₂₅–P₇₅)], and an intergroup comparison was conducted via the Mann-Whitney nonparametric test. Count data were represented using frequency and percentage (%), and intergroup comparison was performed using either the Chi-squared test or the Fisher exact probability method. The Breslow-Day test was employed for conformance testing in hierarchical analysis, while the Mantel-Haenszel test was used for hierarchical chi-square testing. The Jonckheere-Terpstra (J-T) test is a nonparametric method for assessing trend across multiple ordered groups. To address potential confounding, logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for MACEs. All statistical analyses were conducted using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). A two-tailed P value of less than 0.05 was considered to be statistically significant.

Results

In total, 45,013 individuals participated in the baseline survey at The First Affiliated Hospital of Xi’an Jiaotong University (Xi’an, China) between June 2020 and August 2023. Of these, 43,750 cases were excluded due to HCV, HIV, syphilis infection, or incomplete basic data of test results and medical records. A total of 268 patients presenting with hepatic hemangioma, toxic diffuse goiter with hyperthyroidism, hypothyroidism, endometrial cancer, hemodialysis status of stage 5 chronic kidney disease, chronic renal insufficiency, skull osteoma, or right lobe cyst of thyroid gland were excluded from the study. Additionally, 499 cases with incomplete test data, including five quantitative variables (disease load, blood cells, blood lipid, and other information), and incomplete drug use information, were also excluded. Consequently, a final sample size of 496 participants was included in the study (refer to Figure 1). The patients were categorized into two groups according to their surface antigen status: patients with coexisting CVD and HBV (n=271) and patients with CVD alone (n=225). In addition, a sample of 494 CVD participants was selected from the final sample size of 496 patients included in the study, including those treated with statins (n=415) and those not treated with statins (n=79), to assess the effect of statin use on hepatic fibrosis, atherosclerotic burden, and systemic inflammation.

Figure 1 Flow diagram of cohort selection. A final sample size of 496 participants was included in the study. The patients were categorized into two groups according to their surface antigen status: patients with coexisting CVD and HBV (n=271) and patients with CVD alone (n=225). CVD, cardiovascular disease; HBV, hepatitis B virus; HCV, hepatitis C virus; HBsAg, hepatitis B surface antigen; HIV, human immunodeficiency virus.

Table 1 presents the demographic characteristics of the study participants. A total of 496 participants were included in the analysis, comprising 225 individuals with pure CVD and 271 individuals with CVD accompanied by HBV infection. Notably, the group with CVD and HBV infection had a significantly higher proportion of females (P=0.04) and AMI incidence (P<0.001) as compared to the CVD-alone group. Furthermore, in the comparison of patients with CVD alone to those with CVD combined with HBV, it was found that the latter group exhibited elevated levels of hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (HBsAb), and hepatitis B core antibody (HBcAb) (all P values <0.05). Conversely, the CVD-plus-HBV group had lower weight, medication dosage, triglyceride (TG), lipoprotein(a) [Lp(a)], PLR, and PLT in comparison to the CVD-alone group. Additionally, the proportions of diabetes and prehospital medication were relatively lower in the CVD-plus-HBV group. Notably, the other indicators presented in Table 1 did not demonstrate significant differences. The quantitative (Table S1) and qualitative (Table S2) baseline characteristics and statistical comparisons of individuals with CVD who were either using or not using statins were also documented. We found that there were statistically significant differences in height, weight, PLR, alanine aminotransferase levels (ALT), and aspartate aminotransferase (AST) levels among the three groups, no statins, atorvastatin and rosuvastatin groups (all P values <0.05). The use of statins resulted in lower TG (P<0.001), LDL-C (P<0.001), apolipoprotein B (ApoB) (P<0.001), and non-HDL-C (P<0.001) levels. As seen in Table S2, there were significant differences in gender, diabetes, and smoking history across the three groups, no statins, atorvastatin and rosuvastatin groups, with or without statin usage (all P values <0.05). Conversely, no statistically significant differences were observed in hypertension, alcohol history, or anti-HBV treatment among the three groups (all P values >0.05).

Relationship of statin use with HBV infection and quantification

To examine the relationship between statin use and HBV infection, we conducted a study comparing HBV infection rates and quantitative parameters in patients both with and without statin use. Our analysis revealed a significant association between statin use and HBV infection rates (χ²=76.835; P<0.001; Table 2). Subsequent pairwise comparisons demonstrated that the HBV infection rate in the group not using statins was 97.5% (77/79), whereas the rate in the group on 20 mg of atorvastatin was 40.4% (91/225), indicating a protective effect with an OR of 0.018 (95% CI: 0.004–0.074). In the group treated with 10 mg of rosuvastatin, the HBV infection rate was 53.7% (102/190), with an OR of 0.030 (95% CI: 0.007–0.126). Furthermore, the HBV infection rate was 40.4% (91/225) in the atorvastatin group and 53.7% (102/190) in the rosuvastatin group, representing a statistically significant difference between the two groups (P=0.002; Table 2). This suggests that the HBV infection rate in the 10-mg rosuvastatin group was relatively higher, with an OR of 1.94 (95% CI: 1.28–2.94) (Table 2). The HBsAg levels ranged from less than 0.05 to 250, the median difference between no statin and atorvastatin was calculated to be 70 (95% CI: 26–125). Additionally, the median difference between no statin and rosuvastatin was found to be 63 (95% CI: 18–117). These findings indicate that the quantification of HBsAg in individuals using statins is notably reduced compared to those not using statins (Table 3). Furthermore, when compared to that of group not using statins, the levels of HBV-DNA and HbcAb were significantly lower in the group using statins. Conversely, the levels of HBsAb, HBeAg, and HBeAb were significantly higher in the group using statins (Table 3). In addition, there was a significant dose-effect relationship found between statin dosage and HBsAg levels (P<0.001) (Table 4), indicating that higher doses result in lower HBsAg levels, with the exception of a slight rebound observed at the highest dose of 20 mg of rosuvastatin.

The impact of HBV infection, stratified by statins use, on multiple clinical outcomes among patients with CVD

According to the findings depicted in Figure 2, HBV infection exhibited a protective effect against the occurrence of CHD (OR =0.27; 95% CI: 0.12–0.60; P=0.009) and AP (OR =0.56; 95% CI: 0.36–0.86; P=0.008). Conversely, HBV infection was identified as a risk factor for AMI (OR =2.24, 95% CI: 1.40–3.57; P=0.001). Furthermore, it was determined that HBV infection did not significantly impact the remaining 11 clinical outcomes in individuals with coronary artery disease (CAD).

Figure 2 The impact of HBV infection, stratified by no statin (n=79) or statin use (20 mg of atorvastatin =182 and 20 mg rosuvastatin =166), on multiple clinical outcomes among patients with CVD. AMI, acute myocardial infarction; AP, angina pectoris; CCU, coronary care unit; CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; DM, diabetes mellitus; HF, heart failure; MI, myocardial infarction; NYHA, New York Heart Association; UAP, unstable angina pectoris.

The effect of HBV infection, stratified by DM, on multiple clinical outcomes among patients with CVD

The prevalence of DM among patients with and without HBV infection was 48.7% and 62.7%, respectively (P=0.002; Table 1), and thus the baseline characteristics were not equivalent. Consequently, the presence of DM may exert an influence on cardiovascular outcomes. In this study, DM was employed as a stratified variable to examine the potential impact of HBV infection on clinical outcomes in patients with CVD. The results of our study indicate that the coexistence of DM and HBV infection may significantly increase the risk of AMI (OR =5.37; 95% CI: 2.91–9.92; P<0.001) and unfavorable secondary clinical outcomes (OR =4.34; 95% CI: 2.06–9.15; P<0.001) (Figure 3). These findings suggest the importance of implementing strict blood sugar control and anti-HBV therapy in patients with this comorbidity.

Figure 3 The impact of HBV infection, stratified by DM, on multiple clinical outcomes among patients with CVD. AMI, acute myocardial infarction; AP, angina pectoris; CCU, coronary care unit; CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; DM, diabetes mellitus; HF, heart failure; MI, myocardial infarction; NYHA, New York Heart Association; UAP, unstable angina pectoris.

Comparison of the effects of atorvastatin and rosuvastatin on multiple clinical outcomes in patients with CVD

Figure S1 presents a comparison of the effects of atorvastatin and rosuvastatin on 13 clinical outcomes in patients diagnosed with CVD. In comparison to patients prescribed atorvastatin, those prescribed rosuvastatin exhibited the higher susceptibility to CHD and coronary care unit (CCU) admission, with OR values of 2.1 (95% CI: 1.0–4.2; P=0.047) and 4.1 (95% CI: 2.5–6.6; P<0.001), respectively. Additionally, the proportion of patients with NYHA classification and a lower risk of UAP was 0.51 (95% CI: 0.32–0.79; P=0.003) and 0.62 (95% CI: 0.39–0.99; P=0.043), respectively. In comparison to atorvastatin, rosuvastatin resulted in a statistically significant decrease in the median duration of hospitalization by one day, with a 95% CI ranging from 0.0 to 1.0 day (P=0.001; Table S3).

Interaction of statin use with hepatic FIB-4, CBCIIs, and ALBI grade

In order to assess the potential impact of statin use on improving clinical outcomes related to CVD by inhibiting the progression of liver fibrosis, we examined the association of different statin drugs and doses with FIB-4 levels in patients with CVD. The findings indicated that atorvastatin use was associated with lower FIB-4 levels in comparison with non-statin use, whereas the use of rosuvastatin did not exhibit a significant difference in FIB-4 levels compared to non-statin use (Table S4). Our study also revealed that the use of statins was associated with a reduction in the levels of SIRI and SIRI/HDL-C ratio, in addition to an increase in PMR and SII in patients with CVD (Table S4). The findings of dose-stratification analysis in patients with CVD revealed that atorvastatin (20 mg) significantly reduced hepatic FIB-4 compared to patients without statin use (P=0.001). Other concentration stratification groups of atorvastatin had no significant effect on hepatic FIB-4. Similarly, the three concentration gradients of rosuvastatin showed no significant impact on hepatic FIB-4 compared to patients without statin use. Therefore, both atorvastatin and rosuvastatin do not exhibit a dose-effect relationship on hepatic FIB-4 (Figure S2). Concurrently, a FIB-4 stratification analysis was conducted, revealing that patients treated with atorvastatin exhibited a higher proportion of FIB-4 <1.45 and a lower proportion of FIB-4 >3.25. Nevertheless, the reduction in FIB-4 level with rosuvastatin was not as pronounced as that with atorvastatin (Table S5).

The ALBI grade is a liver function assessment tool that incorporates measurements of albumin and bilirubin levels. We examined the impact of statin medications on liver function markers and ALBI grade. Statin use was found to significantly decrease direct bilirubin (DBIL), AST, and ALT levels as compared to non-statin use but showed no significant effect on other liver function indices, including ALBI grade (Table S6). Stratified analysis based on ALBI grade revealed that none of the patients progressed to an ALBI grade >–1.39, indicative of the group with the poorest prognosis. Furthermore, statin drug use did not influence ALBI grade in the remaining two groups (Table S7).

Effect of statin use on atherogenic indices

As shown in Table S8, in comparison to the statin-free group, the group treated with statins exhibited a significant decrease in the levels of AI, CRI-I, CRI-II, and lipoprotein combine index (LCI), whereas adjusted AIP, AIP, and remnant-like particle cholesterol (RLP-C) did not show a statistically significant difference.

Discussion

In our study, the baseline data analysis revealed that individuals with both HBV and CVD exhibited notably reduced levels of TG and Lp(a) as compared to those with CVD alone. The use of statins has the capacity to reduce the prevalence of CHD and AP among individuals with CVD associated with HBV infection. These findings suggest that patients with both CVD and HBV infection should be judiciously administered with statins and should effectively manage the blood glucose levels.

HBV infection has the potential to precipitate a range of intrahepatic and extrahepatic ailments, including acute and chronic hepatitis, cirrhosis, hepatocellular carcinoma, metabolic syndrome, CVD, and renal injury (45-47). The pathogenesis of HBV infection is complex and multifaceted, essentially manifesting as a multisystem disorder. The underestimation of the influence of HBV infection on atherosclerosis has been identified. Multiple studies have demonstrated that the inflammation triggered by HBV infection serves as a significant contributing factor to the development of atherosclerosis (18,48). Conversely, atherosclerosis also exerts subsequent effects on the severity of chronic HBV infection, thereby establishing a vicious cycle (18). Patients with metabolic dysfunction-associated fatty liver disease (MAFLD) and concomitant HBV are with elevated overall risk of liver fibrosis while with protection against atherosclerosis as compared to those with MAFLD alone, which may be attributed to antiviral treatment (47). The findings of recent studies (18,47) and our research indicate that the implementation of either antiviral therapy or lipid-lowering statin therapy holds the potential to improve liver metabolism or liver injury, consequently reducing the susceptibility to CVD associated with HBV infection.

In our study, HBV infection emerged as a significant risk for AMI in patients with CVD (OR =2.24; 95% CI: 1.40–3.57; P=0.001). However, our findings did not indicate a significant association between HBV infection and MI (OR =1.08; 95% CI: 0.69–1.68; P=0.815). Analysis of baseline data demonstrated that the proportion of AMI in patients with both HBV infection and CVD was 39.1% (106/271), which was significantly higher than that in patients with CVD alone (23.1%) (52/225; P<0.001). Currently, there is a lack of pertinent research indicating that HBV infection serves as a risk factor for AMI. Furthermore, the underlying physiological and pathological mechanisms by which HBV infection may contribute to an increased risk of AMI in patients with CVD remain unclear. It is plausible that our findings may be attributed to potential data bias, as we did not conduct a multivariate regression analysis. Moreover, a comprehensive epidemiological investigation with larger sample sizes is necessary to ascertain the risk of HBV infection in relation to AMI.

It may be prudent to consider reducing or discontinuing statin therapy in patients with HBV infection who exhibit transaminase levels exceeding three times the upper limit of normal. Additionally, the administration of anti-HBV therapy to patients with HBV infection could potentially impact the outcome. The quantification of HBV infection in this study was based on HBsAg levels, and while statin use may reduce HBV-DNA levels until they become undetectable, it is unlikely to result in clearance of HBsAg. Multiple studies have documented the potential of statins to decrease the likelihood of progression to cirrhosis and hepatocellular carcinoma in individuals with HBV infection (49-54). This is attributed to the inhibition or eradication of HBV, which is believed to impede the progression to cirrhosis and liver cancer. van de Klundert et al. (54) reported that statins inhibit the replication of the HBV and decrease the viability of hepatoma cells by disrupting Rho-GTPases, which is line with our findings. Furthermore, the HBV viral load remains relatively constant in the absence of effective anti-HBV treatment, suggesting that factors other than statins have minimal impact. Therefore, the proposition that statins inhibit or eradicate HBV is likely valid.

To further clarify the potential mechanisms of statin therapy in patients with CVD to improve clinical outcomes, we conducted additional research on the impact of statin therapy on hepatic function, atherosclerotic burden, and systemic inflammation. The importance of FIB-4 and ALBI grade as noninvasive indicators for liver fibrosis in predicting CVD among patients with liver diseases or DM has been well documented (55-59). Schonmann et al. (58) found that individuals with advanced fibrosis (FIB-4 ≥2.67) had a significantly higher risk of CVD (HR =1.60; 95% CI: 1.27–2.01) compared to those with inconclusive fibrosis (HR =1.15, 95% CI: 1.01–1.31). Chun et al. (59) reported that there was a significant difference in the cumulative incidence of CVD among groups stratified by FIB-4. The severity of liver fibrosis was found to independently predict the occurrence of CVD in patients with type 2 diabetes mellitus (T2DM). Additionally, their study revealed that the use of statins may serve as a protective factor (HR =0.603) among individuals with T2DM, thereby mitigating the likelihood of developing CVD (59). FIB-4 may have utility in the identification of individuals at elevated risk of CVD within the population of those diagnosed with NAFLD. Conversely, the use of AST:PLT index for this purpose is not advised (60). Our findings indicate that FIB-4 may be more effective than ALBI in assessing liver function in patients undergoing atorvastatin therapy. This is primarily due to the ability of FIB-4 to accurately monitor patients with severe liver damage, which was notably reduced in those receiving atorvastatin treatment. Prior research has indicated that statins may impact the levels of AST and ALT in patients with NAFLD, suggesting that FIB-4 has an ability to noninvasively predict hepatic fibrosis (61).

More importantly, our study revealed that both atorvastatin and rosuvastatin exhibited a dose-dependent reduction in FIB-4 levels among patients with CVD. A notable increase in the number of patients with FIB-4 grade <1.45 and a decrease in those with FIB-4 grade >3.25, particularly those administered atorvastatin, were observed. Simon et al. (62) found that the use of statins was linked to a dose-dependent decrease in incident cirrhosis. Mohanty et al. (63) reported that statin use in patients with HCV was correlated with an over 40% reduction in the risk of cirrhosis. The prevalence of cirrhosis was found to be 8% lower in the group receiving statin treatment compared to that in the statin-free group (64). Furthermore, the use of statins was correlated with a reduced progression of liver fibrosis and occurrence of hepatocellular carcinoma in a substantial population of veterans with HCV infection (64). Collectively, the findings of these studies (62-64) and our own research indicate that statins may possess potential anti-fibrotic properties.

CBCIIs is an important predictor of chronic noninfectious inflammatory response, which is associated with the development of various metabolic system disorders such as fibrosis, hypertension, hyperlipidemia, and hyperglycemia (65-67). SIRI and SII are the two important peripheral blood cell count–based inflammation indicators (39,68). Prospective investigations have identified a correlation between elevated levels of white blood cells and their subtypes, such as NE, MO, and lymphocytes, and a heightened susceptibility to CHD and stroke. Neutrophils are capable of releasing a variety of inflammatory mediators, chemokines, and oxygen-free radicals, thereby inducing endothelial cell damage and consequent tissue ischemia, and thus figure prominently in the inflammatory response of atherosclerosis (39,68,69). The activation and differentiation of MO into lipid-laden macrophages is a critical step in the pathogenesis of atherosclerotic plaques (39,68,69). Consequently, novel systemic inflammatory markers, such as the SII and SIRI, which are derived from neutrophil counts and other parameters, are likely to be correlated with unfavorable cardiovascular outcomes. In our study, conflicting outcomes were observed between SIRI and SII in their assessment of statin efficacy among patients with CVD. Specifically, we found increases in SIRI levels and SII levels in patients with CVD following statin therapy. Li et al. (70) demonstrated that SIRI is a strong predictor of all-cause mortality in patients with CAD and low residual inflammatory risk. Numerous studies have indicated that the SII may serve as a potential biomarker for the development of CVD, with elevated levels of SII being linked to an increased risk of CVD (71-73). SII and SIRI have been associated with CVD, yet the impact of statin therapy on these indices remains inconclusive. In our study, following statin therapy, SII levels significantly increased whereas SIRI levels significantly decreased. Consequently, the influence of statin therapy on the systemic inflammatory response in patients with CVD remains uncertain and warrants further validation in a larger cohort.

Our study determined that the use of statins resulted in a significant decrease in TC and LDL-C levels. Additionally, we conducted a thorough examination of the impact of statin use on atherogenic indices among individuals diagnosed with CVD. Higher values of atherogenic indices, including AIP, CRI-I, CRI-II, and LCI, have been found to be significantly associated with an increased risk of CAD as compared to lower values (42). Several studies have indicated that AIP can serve as a novel marker for CVD, with elevated AIP being an independent prognostic factor in patients with CAD (74-77). In one study, AI was independently associated with all-cause and CVD mortality among patients undergoing peritoneal dialysis (44). Following adjustments for potential confounders, the highest AI value exhibited a notably increased hazard ratio for both all-cause mortality and CVD mortality when compared to the lowest AI value (44). Hence, the majority of atherogenicity indicators hold significant implications for the diagnosis and prognosis of CVD risk events. Currently, there is a lack of relevant literature examining the relationship between statin use and atherogenicity indicators. Our research indicates that the use of statins can significantly reduce levels of AI, CRI-I, CRI-II, and LCI. These findings suggest that statins may have a positive effect on liver fibrosis by improving lipid metabolism. Additionally, atherogenic indices such as AI, CRI-I, CRI-II, and LCI could serve as valuable markers for assessing liver fibrosis in patients undergoing statin therapy for CVD.

It is important to acknowledge that there are several limitations in our study. First, the recruitment of patients was limited to a single center, and the sample size was moderate. Second, there is a deficiency of information pertaining to the duration of hyperlipidemia, hypertension, and diabetes. Consequently, in the assessment of the impact of diabetes and its complications, the potential influence of unmeasured confounding factors cannot be discounted. Third, this study is inherently limited by its retrospective design, which may introduce selection bias and restrict causal inference. Furthermore, only inpatient data were analyzed, precluding the assessment of long-term follow-up.

Conclusions

Our study indicates that patients with CVD who also have HBV infection may have a reduced risk of MACEs when treated with statins. The implementation of statins has demonstrated the potential to reduce the incidence of CHD and AP in individuals with CVD. Our findings also indicate that FIB-4 could serve as a potential indicator for assessing liver function in individuals undergoing treatment with statins. Statin therapy resulted in reduction in TC and LDL-C levels, as well as the improvement of atherogenicity markers such as AI, CRI-I, CRI-II, and LCI. Our findings also suggest that statins may potentially ameliorate liver fibrosis through the enhancement of lipid metabolism. Furthermore, atherogenic indices including AI, CRI-I, CRI-II, and LCI may serve as useful indicators for evaluating liver fibrosis in individuals receiving statin treatment for CVD. The observed improvements in hepatic function, atherosclerotic burden, and systemic inflammation associated with statin therapy may contribute to achieving favorable outcomes among individuals with CVD.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-63/rc

Data Sharing Statement: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-63/dss

Peer Review File: Available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-63/prf

Funding: The study was supported by the Natural Science Foundation of Shaanxi Province, China (No. 2022SF-243).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cdt.amegroups.com/article/view/10.21037/cdt-2025-63/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of the First Affiliated Hospital of Xi’an Jiaotong University (No. XJTU1AF2024LSYY-054). Informed consent was waived by the Institutional Review Board given the retrospective study design.

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References

1. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1736-88. [Crossref] [PubMed]
2. Stone PH, Libby P, Boden WE. Fundamental Pathobiology of Coronary Atherosclerosis and Clinical Implications for Chronic Ischemic Heart Disease Management-The Plaque Hypothesis: A Narrative Review. JAMA Cardiol 2023;8:192-201. [Crossref] [PubMed]
3. Kamstrup PR. Lipoprotein(a) and Cardiovascular Disease. Clin Chem 2021;67:154-66. [Crossref] [PubMed]
4. Ference BA, Graham I, Tokgozoglu L, et al. Impact of Lipids on Cardiovascular Health: JACC Health Promotion Series. J Am Coll Cardiol 2018;72:1141-56. [Crossref] [PubMed]
5. Vujkovic M, Keaton JM, Lynch JA, et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat Genet 2020;52:680-91. [Crossref] [PubMed]
6. Clarke R, Von Ende A, Schmidt LE, et al. Apolipoprotein Proteomics for Residual Lipid-Related Risk in Coronary Heart Disease. Circ Res 2023;132:452-64. [Crossref] [PubMed]
7. Huang Y, Ren Y, Yang H, et al. Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment. Comput Biol Med 2022;151:106297. [Crossref] [PubMed]
8. Grandhi GR, Mirbolouk M, Dardari ZA, et al. Interplay of Coronary Artery Calcium and Risk Factors for Predicting CVD/CHD Mortality: The CAC Consortium. JACC Cardiovasc Imaging 2020;13:1175-86. [Crossref] [PubMed]
9. Brown A, Reynolds LR, Bruemmer D. Intensive glycemic control and cardiovascular disease: an update. Nat Rev Cardiol 2010;7:369-75. [Crossref] [PubMed]
10. Nauta ST, Deckers JW, Akkerhuis KM, et al. Short- and long-term mortality after myocardial infarction in patients with and without diabetes: changes from 1985 to 2008. Diabetes Care 2012;35:2043-7. [Crossref] [PubMed]
11. Piechocki M, Przewłocki T, Pieniążek P, et al. A Non-Coronary, Peripheral Arterial Atherosclerotic Disease (Carotid, Renal, Lower Limb) in Elderly Patients-A Review: Part I-Epidemiology, Risk Factors, and Atherosclerosis-Related Diversities in Elderly Patients. J Clin Med 2024;13:1471. [Crossref] [PubMed]
12. Zhang YY, Hu KQ. Rethinking the pathogenesis of hepatitis B virus (HBV) infection. J Med Virol 2015;87:1989-99. [Crossref] [PubMed]
13. Cacoub P, Asselah T, Hepatitis B. Virus Infection and Extra-Hepatic Manifestations: A Systemic Disease. Am J Gastroenterol 2022;117:253-63. [Crossref] [PubMed]
14. Hamilton EM, Yang L, Wright N, et al. Chronic Hepatitis B Virus Infection and Risk of Stroke Types: A Prospective Cohort Study of 500 000 Chinese Adults. Stroke 2023;54:3046-53. [Crossref] [PubMed]
15. Kuo CS, Chen YT, Hsu CY, et al. The impact of chronic hepatitis B infection on major adverse cardiovascular events and all-cause mortality in patients with diabetes: a nationwide population-based study from Taiwan. BMJ Open 2017;7:e016179. [Crossref] [PubMed]
16. Ke ZP, Gong M, Zhao G, et al. Association between HBV Infection and the Prevalence of Coronary Artery Disease in the US Population. Comput Math Methods Med 2022;2022:5062798. [Crossref] [PubMed]
17. Kumar A, Shariff M, Doshi R. Association Between Past Hepatitis B Infection and Ischemic Heart Disease: An Analysis From the 2007-2016 NHANES Data. Am J Med Sci 2020;360:372-7. [Crossref] [PubMed]
18. Ranković I, Milivojević V, Pavlović Marković A, et al. Interplay between chronic hepatitis B and atherosclerosis: Innovative perspectives and theories. World J Gastroenterol 2022;28:497-9. [Crossref] [PubMed]
19. Wu VC, Chen TH, Wu M, et al. Comparison of cardiovascular outcomes and all-cause mortality in patients with chronic hepatitis B and C: A 13-year nationwide population-based study in Asia. Atherosclerosis 2018;269:178-84. [Crossref] [PubMed]
20. Kim D, Adejumo AC, Yoo ER, et al. Trends in Mortality From Extrahepatic Complications in Patients With Chronic Liver Disease, From 2007 Through 2017. Gastroenterology 2019;157:1055-1066.e11. [Crossref] [PubMed]
21. Liu XY, Zhou Y. Influence of hepatitis B virus on the prevalence of diabetes complications in patients with type 2 diabetes. J Diabetes Investig 2023;14:429-34. [Crossref] [PubMed]
22. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019;140:e596-646. [Crossref] [PubMed]
23. Lu Y, Zhang H, Lu J, et al. Prevalence of Dyslipidemia and Availability of Lipid-Lowering Medications Among Primary Health Care Settings in China. JAMA Netw Open 2021;4:e2127573. [Crossref] [PubMed]
24. Sharpton SR, Loomba R. Emerging role of statin therapy in the prevention and management of cirrhosis, portal hypertension, and HCC. Hepatology 2023;78:1896-906. [Crossref] [PubMed]
25. Cho Y, Rhee H, Kim YE, et al. Ezetimibe combination therapy with statin for non-alcoholic fatty liver disease: an open-label randomized controlled trial (ESSENTIAL study). BMC Med 2022;20:93. [Crossref] [PubMed]
26. Shaffer LR, Mahmud N. Statins in Cirrhosis: Hope or Hype? J Clin Exp Hepatol 2023;13:1032-46. [Crossref] [PubMed]
27. Dongiovanni P, Petta S, Mannisto V, et al. Statin use and non-alcoholic steatohepatitis in at risk individuals. J Hepatol 2015;63:705-12. [Crossref] [PubMed]
28. Tessier CM, Polyzos SA, Athyros VG, et al. Long-term statin treatment for hepatic fibrosis in patients with nonalcoholic fatty liver disease: Is it time to give the emperor a statin robe? Metabolism 2021;121:154796. [Crossref] [PubMed]
29. Boutari C, Pappas PD, Anastasilakis D, et al. Statins' efficacy in non-alcoholic fatty liver disease: A systematic review and meta-analysis. Clin Nutr 2022;41:2195-206. [Crossref] [PubMed]
30. Navarro P, Gutiérrez-Ramírez L, Tejera-Muñoz A, et al. Systematic Review and Meta-Analysis: Prevalence of Non-Alcoholic Fatty Liver Disease and Liver Fibrosis in Patients with Inflammatory Bowel Disease. Nutrients 2023;15:4507. [Crossref] [PubMed]
31. Martínez-Domínguez SJ, García-Mateo S, Laredo V, et al. Liver Fibrosis in Non-Alcoholic Fatty Liver Disease and Progression to Hepatocellular Carcinoma in Patients with Inflammatory Bowel Disease: A Systematic Review. Cancers (Basel) 2023;15:3367. [Crossref] [PubMed]
32. Sarin SK, Kumar M, Lau GK, et al. Asian-Pacific clinical practice guidelines on the management of hepatitis B: a 2015 update. Hepatol Int 2016;10:1-98. [Crossref] [PubMed]
33. Hicks KA, Tcheng JE, Bozkurt B, et al. 2014 ACC/AHA Key Data Elements and Definitions for Cardiovascular Endpoint Events in Clinical Trials: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards). J Am Coll Cardiol 2015;66:403-69. [Crossref] [PubMed]
34. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J 2020;41:407-77. [Crossref] [PubMed]
35. Al-Khatib SM, Stevenson WG, Ackerman MJ, et al. 2017 AHA/ACC/HRS Guideline for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol 2018;72:e91-e220. [Crossref] [PubMed]
36. Ponikowski P, Voors AA, Anker SD, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 2016;18:891-975. [Crossref] [PubMed]
37. Thygesen K, Alpert JS, Jaffe AS, et al. Fourth Universal Definition of Myocardial Infarction (2018). J Am Coll Cardiol 2018;72:2231-64. [Crossref] [PubMed]
38. Tian YB, Niu H, Xu F, et al. ALBI score combined with FIB-4 index to predict post-hepatectomy liver failure in patients with hepatocellular carcinoma. Sci Rep 2024;14:8034. [Crossref] [PubMed]
39. Li J, He D, Yu J, et al. Dynamic Status of SII and SIRI Alters the Risk of Cardiovascular Diseases: Evidence from Kailuan Cohort Study. J Inflamm Res 2022;15:5945-57. [Crossref] [PubMed]
40. Xiu J, Lin X, Chen Q, et al. The aggregate index of systemic inflammation (AISI): a novel predictor for hypertension. Front Cardiovasc Med 2023;10:1163900. [Crossref] [PubMed]
41. Gaggini M, Gorini F, Vassalle C. Lipids in Atherosclerosis: Pathophysiology and the Role of Calculated Lipid Indices in Assessing Cardiovascular Risk in Patients with Hyperlipidemia. Int J Mol Sci 2022;24:75. [Crossref] [PubMed]
42. Mahdavi-Roshan M, Mozafarihashjin M, Shoaibinobarian N, et al. Evaluating the use of novel atherogenicity indices and insulin resistance surrogate markers in predicting the risk of coronary artery disease: a case‒control investigation with comparison to traditional biomarkers. Lipids Health Dis 2022;21:126. [Crossref] [PubMed]
43. Vargas HO, Nunes SO, Barbosa DS, et al. Castelli risk indexes 1 and 2 are higher in major depression but other characteristics of the metabolic syndrome are not specific to mood disorders. Life Sci 2014;102:65-71. [Crossref] [PubMed]
44. Deng J, Tang X, Tang R, et al. Atherogenic index predicts all-cause and cardiovascular mortality in incident peritoneal dialysis patients. Atherosclerosis 2023;387:117389. [Crossref] [PubMed]
45. Tian T, Song C, Jiang L, et al. Hepatitis B virus infection and the risk of cancer among the Chinese population. Int J Cancer 2020;147:3075-84. [Crossref] [PubMed]
46. Motamed-Gorji N, Eghtesad S, Sharafkhah M, et al. All-Cause and Cause-Specific Mortality in Middle-Aged Individuals with Positive HBsAg: Findings from a Prospective Cohort Study. Arch Iran Med 2022;25:139-47. [Crossref] [PubMed]
47. Cheng YM, Hsieh TH, Wang CC, et al. Impact of HBV infection on clinical outcomes in patients with metabolic dysfunction-associated fatty liver disease. JHEP Rep 2023;5:100836. [Crossref] [PubMed]
48. Ghamar Talepoor A, Doroudchi M. Immunosenescence in atherosclerosis: A role for chronic viral infections. Front Immunol 2022;13:945016. [Crossref] [PubMed]
49. Vell MS, Loomba R, Krishnan A, et al. Association of Statin Use With Risk of Liver Disease, Hepatocellular Carcinoma, and Liver-Related Mortality. JAMA Netw Open 2023;6:e2320222. [Crossref] [PubMed]
50. Yun B, Ahn SH, Yoon JH, et al. Statin use and risk of progression to liver cirrhosis in chronic hepatitis B independent of conventional risk factors: A nationwide study. Hepatol Commun 2022;6:2455-64. [Crossref] [PubMed]
51. Hsiang JC, Wong GL, Tse YK, et al. Statin and the risk of hepatocellular carcinoma and death in a hospital-based hepatitis B-infected population: A propensity score landmark analysis. J Hepatol 2015;63:1190-7. [Crossref] [PubMed]
52. Singh S, Singh PP, Singh AG, et al. Statins are associated with a reduced risk of hepatocellular cancer: a systematic review and meta-analysis. Gastroenterology 2013;144:323-32. [Crossref] [PubMed]
53. Cheung KS, Mak LY, Lam LK, et al. Statins associate with better clinical outcomes in chronic hepatitis B patients with HBsAg seroclearance. Hepatol Int 2021;15:881-91. [Crossref] [PubMed]
54. van de Klundert M, Ringelhan M, Protzer U. Statins suppress hepatitis B virus replication and reduce hepatoma cell viability by interfering with Rho-GTPases. Journal of Hepatology 2018;68:S782.
55. Guan L, Li L, Zou Y, et al. Association between FIB-4, all-cause mortality, cardiovascular mortality, and cardiovascular disease risk among diabetic individuals: NHANES 1999-2008. Front Cardiovasc Med 2023;10:1172178. [Crossref] [PubMed]
56. Seo YG, Polyzos SA, Park KH, et al. Fibrosis-4 Index Predicts Long-Term All-Cause, Cardiovascular and Liver-Related Mortality in the Adult Korean Population. Clin Gastroenterol Hepatol 2023;21:3322-35. [Crossref] [PubMed]
57. Roca-Fernandez A, Banerjee R, Thomaides-Brears H, et al. Liver disease is a significant risk factor for cardiovascular outcomes - A UK Biobank study. J Hepatol 2023;79:1085-95. [Crossref] [PubMed]
58. Schonmann Y, Yeshua H, Bentov I, et al. Liver fibrosis marker is an independent predictor of cardiovascular morbidity and mortality in the general population. Dig Liver Dis 2021;53:79-85. [Crossref] [PubMed]
59. Chun HS, Lee JS, Lee HW, et al. Association between the severity of liver fibrosis and cardiovascular outcomes in patients with type 2 diabetes. J Gastroenterol Hepatol 2021;36:1703-13. [Crossref] [PubMed]
60. Yi M, Peng W, Teng F, et al. The role of noninvasive scoring systems for predicting cardiovascular disease risk in patients with nonalcoholic fatty liver disease: a systematic review and meta-analysis. Eur J Gastroenterol Hepatol 2022;34:1277-84. [Crossref] [PubMed]
61. Al-Karaghouli M, Fuentes S, Davyduke T, et al. Impact of statin treatment on non-invasive tests based predictions of fibrosis in a referral pathway for NAFLD. BMJ Open Gastroenterol 2022;9:e000798. [Crossref] [PubMed]
62. Simon TG, Bonilla H, Yan P, et al. Atorvastatin and fluvastatin are associated with dose-dependent reductions in cirrhosis and hepatocellular carcinoma, among patients with hepatitis C virus: Results from ERCHIVES. Hepatology 2016;64:47-57. [Crossref] [PubMed]
63. Mohanty A, Tate JP, Garcia-Tsao G. Statins Are Associated With a Decreased Risk of Decompensation and Death in Veterans With Hepatitis C-Related Compensated Cirrhosis. Gastroenterology 2016;150:430-40.e1. [Crossref] [PubMed]
64. Butt AA, Yan P, Bonilla H, et al. Effect of addition of statins to antiviral therapy in hepatitis C virus-infected persons: Results from ERCHIVES. Hepatology 2015;62:365-74. [Crossref] [PubMed]
65. Yousaf H, Khan MIU, Ali I, et al. Emerging role of macrophages in non-infectious diseases: An update. Biomed Pharmacother 2023;161:114426. [Crossref] [PubMed]
66. Cho S, Ying F, Sweeney G. Sterile inflammation and the NLRP3 inflammasome in cardiometabolic disease. Biomed J 2023;46:100624. [Crossref] [PubMed]
67. Zinellu A, Paliogiannis P, Sotgiu E, et al. Blood Cell Count Derived Inflammation Indexes in Patients with Idiopathic Pulmonary Fibrosis. Lung 2020;198:821-7. [Crossref] [PubMed]
68. Kong F, Huang J, Xu C, et al. System inflammation response index: a novel inflammatory indicator to predict all-cause and cardiovascular disease mortality in the obese population. Diabetol Metab Syndr 2023;15:195. [Crossref] [PubMed]
69. Wang P, Guo X, Zhou Y, et al. Monocyte-to-high-density lipoprotein ratio and systemic inflammation response index are associated with the risk of metabolic disorders and cardiovascular diseases in general rural population. Front Endocrinol (Lausanne) 2022;13:944991. [Crossref] [PubMed]
70. Li T, Wang P, Wang X, et al. Prognostic significance of inflammation in patients with coronary artery disease at low residual inflammatory risk. iScience 2023;26:108060. [Crossref] [PubMed]
71. Ye Z, Hu T, Wang J, et al. Systemic immune-inflammation index as a potential biomarker of cardiovascular diseases: A systematic review and meta-analysis. Front Cardiovasc Med 2022;9:933913. [Crossref] [PubMed]
72. Ma J, Li K. Systemic immune-inflammation index is associated with coronary heart disease: a cross-sectional study of NHANES 2009-2018. Front Cardiovasc Med 2023;10:1199433. [Crossref] [PubMed]
73. Zhao Z, Zhang X, Sun T, et al. Prognostic value of systemic immune-inflammation index in CAD patients: Systematic review and meta-analyses. Eur J Clin Invest 2024;54:e14100. [Crossref] [PubMed]
74. Rabiee Rad M, Ghasempour Dabaghi G, Darouei B, et al. The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: A systematic review and meta-analysis. Cardiovasc Diabetol 2024;23:119. [Crossref] [PubMed]
75. Min Q, Wu Z, Yao J, et al. Association between atherogenic index of plasma control level and incident cardiovascular disease in middle-aged and elderly Chinese individuals with abnormal glucose metabolism. Cardiovasc Diabetol 2024;23:54. [Crossref] [PubMed]
76. Wang Y, Wang S, Sun S, et al. The predictive value of atherogenic index of plasma for cardiovascular outcomes in patients with acute coronary syndrome undergoing percutaneous coronary intervention with LDL-C below 1.8mmol/L. Cardiovasc Diabetol 2023;22:150. [Crossref] [PubMed]
77. Fernández-Macías JC, Ochoa-Martínez AC, Varela-Silva JA, et al. Atherogenic Index of Plasma: Novel Predictive Biomarker for Cardiovascular Illnesses. Arch Med Res 2019;50:285-94. [Crossref] [PubMed]