Introduction

Abnormal blood glucose metabolism is common in patients with chronic hepatitis, with approximately 96% of patients with liver cirrhosis developing insulin resistance and 30% developing diabetes1. According to a previous study, high levels of glutamic-pyruvic transaminase (GPT) can increase the risk of diabetes, and the effects are independent of obesity or high triglyceride levels2. Common types of chronic hepatitis that are thought to be related to blood glucose metabolism are hepatic insulin resistance, non-alcoholic fatty liver disease (NAFLD), chronic hepatitis B, and chronic hepatitis C3. Researchers in Taiwan have found that fasting blood glucose level is related to abnormal hepatic function. Increased fasting blood glucose and impaired insulin sensitivity were significantly associated with elevated hepatic function indicators such as gluconic transaminase and GPT4. A study in patients with hepatitis B also found that high fasting blood glucose was correlated with obesity and increased GPT5.

There is substantial evidence for the correlation of hepatitis C with diabetes. A Taiwanese study found that patients with hepatitis C had a relatively high risk of abnormal blood glucose, with levels as high as 67.9% even without tissue structural abnormalities such as liver fibrosis6. Hepatitis C with viremia is a risk factor for the development of type 2 diabetes mellitus (T2DM)7.

Fatty liver/NAFLD is known to be associated with an increased risk of diabetes. Insulin resistance in the liver is one of the etiologies of diabetes8,9. A Taiwanese study found that the prevalence of NAFLD in the population of persons with diabetes was 31.8%, whereas the prevalence of diabetes in the NAFLD population was 20.2%, which was significantly higher than that in the population without NAFLD (7.5%)10. A study on the relationship between chronic hepatitis and insulin resistance found that fasting blood glucose, C-peptide, and insulin resistance differed significantly from those in the control group even after adjusting for sex, age, and the etiology of liver cirrhosis11. Although both hepatitis B and C cause increased insulin resistance, NAFLD causes the highest resistance12. Notably, NAFLD and diabetes in Asian populations may not always be a manifestation of obesity. According to one study, 23.5% of patients with NAFLD were non-obese, and patients with NAFLD had significant metabolic abnormalities compared with non-NAFLD patients; however, metabolic abnormality indicators such as blood lipid levels were similar between obese and non-obese NAFLD patients13.

Correlations between chronic hepatitis and cardiovascular disease with diabetes also exist. The evidence for NAFLD and hepatitis C is relatively abundant. Lipids/inflammation/fibrosis of the liver may be common mechanisms but are important determinants of cardiovascular disease in patients with T2DM and NAFLD or hepatitis C14,15. NAFLD was previously correlated with increased cardiovascular disease in patients with diabetes16. NAFLD is a multi-system disease related to diabetes and cardiovascular disease, resulting in hepatocyte injury, liver cirrhosis, and liver cancer. Although it directly impacts the liver, death is mainly related to cardiovascular disease17,18. Whether in patients with or without diabetes, the correlation of hepatitis C with atherosclerosis and cardiovascular disease has been supported by considerable empirical evidence19. Extrahepatic effects of hepatitis C virus infection are not uncommon and are correlated with the incidence and mortality of cardiovascular disease20. As for the influence of hepatitis B infection on cardiovascular disease, the results remain controversial. A meta-analysis pointed out that there is no significant correlation between hepatitis B and coronary heart disease21.

The pay-for-performance program (P4P) of diabetes was designed as an integrated team-care program consists of doctors, nurses, pharmacists, and other medical workers, to provide thorough and comprehensive medical care22,23. In the P4P program, service fees for biochemistry examinations (such as fasting glucose level, HbA1c, renal function, lipid profiles, and proteinuria), fundus examinations, and diabetes self-management education are reimbursed, aimed mainly at monitoring chronic vascular complications of diabetes. Both T2DM and chronic hepatitis are prevalent globally; concurrent diseases may worsen some chronic complications and cause premature death. At present, the prevention and treatment of chronic complications of diabetes focus on large and small blood vessels, as well as integration and connection with chronic nephropathy, without active intervention regarding chronic hepatitis. Taiwan has been implementing the P4P program for several years; however, research and evidence regarding the impact of chronic hepatitis on subsequent complications of diabetes are lacking.

Therefore, we investigated the impact of chronic hepatitis on cardiovascular events to provide a reference for the development of comprehensive care strategies for preventable cardiovascular comorbidities among patients with T2DM.

Results

In this study, 152,709 patients with T2DM (age 59.32 ± 11.67 years) who joined P4P from 2008 to 2010 were selected as the study population after screening (Table 1). The proportion of women (50.35%) was slightly higher than that of men; the follow-up period was at least 7 years (according to a 2017 report of the Ministry of Health and Welfare, the enrollment rate in the P4P until 2017 only accounted for 26.3–29.3% of the population24). Three common types of chronic hepatitis were observed in 17.83% of the study population: fatty liver (7.86%), hepatitis B (6.66%), and hepatitis C (3.31%). The highest proportion of patients was aged 55–64 years (32.1%). The types of chronic hepatitis according to age range were as follows: the prevalence of hepatitis B and fatty liver was the highest among patients aged 40–54 years, whereas the prevalence of hepatitis C was the highest among patients aged 55–64 years. Overall, patients with hepatitis B were the youngest (55.57 ± 10.54 years), and those with hepatitis C were the oldest (61.13 ± 10.01 years).

Table 1 The baseline characteristics of the incident cardiovascular disease in patients with T2DM.

As for the recorded durations of diabetes, regardless of the status of chronic hepatitis, the highest proportion of patients had diabetes for 1–5 years. More than 60% of the patients (64.05%) had a Charlson comorbidity index of 0. Similarly, 61.45% of the patients had a score of 0 on the DCSI. Among all the patients, 56.7% had hypertension, 28.15% of the patients with body mass index (BMI) values were obese (BMI ≥ 27), and 5.36% had a history of smoking. The average HbA1c level was 7.92 ± 1.68% at the time of enrollment and reduced to 7.71 ± 1.30% in the first year after enrollment. The adjusted CV% of HbA1c of the entire population was 7.97%, with the highest value (9.03%) in the hepatitis C group and a value of 7.90% in the non-chronic hepatitis group. The average pre-meal blood glucose level was 151.03 ± 52.55 mg/dL at the time of enrollment and reduced to 148.69 ± 38.26 mg/dL in the first year after enrollment. The adjusted CV% of the pre-meal blood glucose level of the entire population was 17.78%, with the highest value (19.61%) in the hepatitis C group and the lowest value (17.22%) in the fatty liver group. About 40% of the patients had a low-density lipoprotein level of < 100 mg/dL at the time of enrollment, 75% of the patients had an estimated glomerular filtration rate of ≥ 60 mL/min/1.73 m2 at the time of enrollment, and 65% of the patients had a urine albumin-to-creatinine ratio < 30 mg/g.

Table 2 presents the incidence rate per 1000 person-years of cardiovascular disease in T2DM patients with chronic hepatitis. The incidence rate of cardiovascular disease was the highest (79.91/1000 person-years) in patients with diabetes and hepatitis C, followed by patients with fatty liver (66.76/1000 person-years), hepatitis B, and without chronic hepatitis. There was no significant difference between patients with diabetes and hepatitis B or without chronic hepatitis.

Table 2 The incident rate of cardiovascular disease in patients with T2DM.

Table 3 presents the Cox proportional hazard model indicating the relative risk of cardiovascular disease in T2DM patients with and without chronic hepatitis. After adjusting for confounding factors, patients with diabetes and fatty liver had the highest risk of cardiovascular disease (adjusted hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.07–1.13), followed by those with hepatitis C (adjusted HR: 1.09; 95% CI: 1.03–1.12), hepatitis B, and those without chronic hepatitis. There was no significant difference between patients with diabetes and hepatitis B or without chronic hepatitis.

Table 3 The risk and influencing factors of incident cardiovascular disease in patients with T2DM.

As for other variables, slightly more women (adjusted HR: 1.03; 95% CI: 1.01–1.04) developed cardiovascular disease. A higher risk of cardiovascular disease was associated with older age (adjusted HR of patients aged > 75 years: 3.18; 95% CI: 3.01–3.36), a longer disease duration, more complications, heavier bodyweight, (adjusted HR of patients with BMI > 27: 1.18; 95% CI: 1.16–1.21), hypertension, gout, and/or smoking history. Furthermore, patients with HbA1c > 9%, a higher visit-to-visit CV% of pre-meal blood glucose/HbA1c, worsening renal function (adjusted HR of patients with chronic kidney disease stage 5 and estimated glomerular filtration < 15: 1.68; 95% CI: 1.54–1.83), low-density lipoprotein > 130 mg/dL (adjusted HR: 1.06; 95% CI: 1.04–1.08), higher triglyceride levels, and severe proteinuria (measured by urine albumin-to-creatinine ratio of random urine specimen, UACR) also had a higher risk of cardiovascular disease (Table 3).

Discussion

After adjusting for confounding factors, we found that compared with T2DM patients without hepatitis, those with fatty liver had the highest risk of cardiovascular disease. The correlation between diabetes and liver diseases is universal across races and regions. A significant association between chronic hepatitis and insulin resistance was found even after adjusting for sex, age, and the etiology of chronic liver diseases11. Hepatitis C had a higher risk of increased blood glucose, and viremia is an independent risk factor for developing T2DM7. Both hepatitis B, C, and fatty liver increase insulin resistance; however, NAFLD have the most significant influence12.

This again confirmed the findings of several previous studies on the mechanisms and epidemiology of cardiovascular disease. NAFLD was correlated with increased cardiovascular and cancer mortality in patients with diabetes16. Steatosis and chronic inflammation of the liver progressing to fibrosis and abnormal metabolism are important determinants of cardiovascular disease as complications of T2DM21,22. NAFLD is correlated with metabolic syndrome and cardiovascular and cerebrovascular diseases25. Some researchers state that NAFLD with diabetes metabolic abnormality and atherosclerosis are like two sides of the same coin26.

Hepatitis C correlates with atherosclerosis and cardiovascular disease. The use of antiviral drugs for treating hepatitis C can reduce the risk of dyslipidemia and cardiovascular disease in patients with diabetes, hepatitis C27, and carotid atherosclerosis28, as well as reduce low-density lipoprotein and intima thickness in patients with diabetes and hepatitis C29. The treatment of chronic hepatitis is effective not only for the liver itself but also for correcting metabolic abnormalities and managing complications of diabetes caused by chronic hepatitis, which may be reversed and improved through the treatment of viral hepatitis. Therefore, early-stage screening and intervention for chronic hepatitis have significance for patients with diabetes.

There was a slightly higher risk of cardiovascular events among women in this study (adjusted HR: 1.01), which is not consistent with previous studies. Male sex has been identified as a risk factor for cardiovascular disease, irrespective of diabetes status30,31. This result is attributed to the protective effect of estrogen against cardiovascular disease. However, this protective effect declines with age in women because of menopause. Some studies have disagreed with this sentiment; maintaining that lifestyle and socio-economic pressure are the main factors31,32. Epidemiological research in Taiwan on causes of death in patients with T2DM found that the rate of female patients with diabetes who died because of cardiovascular disease in 2014 was 12.53%, which was slightly higher than that of male patients in the same year (12.00%)33. Therefore, cardiovascular disease in female patients with diabetes also poses an issue that should not be ignored.

The results of the analysis were consistent with those of previous studies on the traditional risk factors of cardiovascular disease. The older the patient, the longer the disease duration, the more complications, and the heavier the body weight (BMI > 27), the higher the risk of cardiovascular disease. Hypertension, gout, smoking history, poor renal function, and low-density lipoprotein > 130 mg/dL were also associated with a higher risk of cardiovascular disease.

Regarding abnormal blood glucose metabolism, patients with HbA1c > 9% and a higher visit-to-visit adjusted CV% of pre-meal blood glucose/HbA1c had a higher risk of cardiovascular disease. The correlation of blood glucose variation with cardiovascular disease and other complications of diabetes has received considerable attention recently. With improvements in blood glucose monitoring technology, research has found that aside from episodes of hyperglycemia and hypoglycemia and poor long-term control as reflected by high HbA1c, blood glucose variation is an important factor leading to disease deterioration and complications34. Variations in pre-meal blood glucose are significantly correlated with mortality from cardiovascular disease35. Furthermore, visit-to-visit variation of HbA1c is also correlated with macrovascular complications of newly diagnosed diabetes36. In the future, visit-to-visit variation of pre-meal blood glucose/HbA1c should receive more attention in blood glucose control among patients with diabetes. Reducing variations in blood glucose is an important goal in the treatment and prevention of high-risk cardiovascular complications.

Study limitations

This study has some limitations. First, National Health Insurance Research Database and ICD diagnosis codes were used to define relevant diseases. Thus, a relatively strict diagnostic definition was adopted (patients who had been hospitalized once or had more than three outpatient visits within 365 days and who were diagnosed with diabetes or chronic hepatitis with ICD diagnosis codes were included); however, the definition had been validated in a previous study with a sensitivity of 96.9% and a positive predictive value of 93.9%37 to avoid coding bias. Additionally, the medications of the patients were not analyzed, since it is a confounding factor extremely challenging to control. Each study participant may receive inconsistent prescriptions in the follow-up period, including drug type, drug dose, drug adherence, and medication duration. Therefore, we analyzed clinical data to evaluate the conditions of traditional risk control. We adjusted the biochemistry exam, including LDL-C, and triglycerides to evaluate the situation of treatment to targets, instead of the complicated situation of medication use; however, the pleiotropic effects of medications were not evaluated. As a disadvantage of all retrospective studies, some clinical data were not available and could not be analyzed. Since this is a nationwide study, the laboratory methods of each hospital are not available; however, the principles of quality assurance, quality control, and quality management should be confirmed while the hospitals upload their data to the Data Science Center of the National Health Insurance Administration. Notably, this study focused on adult patients with T2DM in Taiwan who joined P4P. The contents of the P4P include regular follow-up laboratory tests, clinical examinations, and health education, which could explain the involvement of a relatively young population. Moreover, male patients might be less available for follow-up visits due to work restrictions, explaining why we observed a slightly higher number of women in the study population38.

Study strengths

The strengths of the study were that unlike most previous nationwide studies, clinical data were available in the National Health Insurance Research Database, and our study combined large and representative nationwide databases with laboratory data in Taiwan.

In conclusion, chronic hepatitis has varying effects on cardiovascular events in adult patients with T2DM. The variability of fasting blood glucose and HbA1c are independent risk factors for cardiovascular events in patients with T2DM. Patients with diabetes and fatty liver or hepatitis C should be educated on the risk factors for cardiovascular disease actively and as early as possible. In addition to controlling the traditional risk factors, such as blood glucose and blood lipid control, weight loss, smoking cessation, and reduction of glucose variation are also important goals.

Methods

Research subjects

Patients with T2DM who joined the P4P from 2008 to 2010 were enrolled. Patients with a confirmed diagnosis of T2DM were defined as those who were hospitalized at least once or came in for outpatient visits at least three times within 1 year and had a primary or secondary diagnosis International Classification of Diseases (ICD) code “250,” “250.00,” or “250.02”38,39. Among them, patients with type 1 DM “250.x1” * or “250.x3;” gestational DM “648.0” or “648.8;” neonatal DM “775.1;” abnormal glucose tolerance test “790.2;” age < 20 years or > 100 years; and those who died within 1 year of joining P4P were excluded. Finally, 283,793 patients were included (Fig. 1). Based on the status of comorbid chronic hepatitis at enrollment, the patients were divided into four groups: no comorbid chronic hepatitis, named as “No chronic hepatitis”; comorbid liver B, named as “Hepatitis B” group; comorbid liver, named as “Hepatitis C” group; patients without viral hepatitis and with comorbid fatty liver were named as the “Fatty liver disease” group and were followed-up until the end of 2017. The “no comorbid chronic hepatitis” group was used as the reference group to analyze the correlation between different types of chronic hepatitis and the risk of cardiovascular disease.

Figure 1
figure 1

Flowchart for study subject selection. DM diabetes mellitus, P4P pay-for-performance, HBV hepatitis B virus, HCV hepatitis C virus.

Ethics statements

The National Health Insurance Research Database (NHIRD) is derived from Taiwan’s mandatory National Health Insurance program was established by the National Health Insurance Administration Ministry of Health and Welfare and maintained by the National Health Research Institute (NHRI). The patient identifications in the National Health Insurance Research Database have been scrambled and de-identified by the Taiwan government, and the database is commonly used for different types of research such as in medical, and public health fields. Thus, informed consent was waived by the Research Ethics Committee of the China Medical University, and the study protocol was approved by the research ethics committee of China Medical University and Hospital (IRB number: CMUH106-REC3-153) and was conducted in accordance with the principles of the Declaration of Helsinki.

Data sources

This retrospective cohort study analyzed data from the National Health Insurance Research Database of the “Applied Health Research Data Integration Service from National Health Insurance Administration”. The data included outpatient prescriptions and treatments, outpatient prescriptions and medical orders, inpatient medical expense lists, inpatient medical expense and medical order lists, insurance details of persons, major injury and illness, medical institution master files, diagnosis, and P4P education records.

Definitions of variables

Hepatitis B: Those with ICD-9 070.2, 070.20, 070.21, 070.22, 070.23, 070.3070.31, 070.32, or 070.33 or ICD-10 B16, B17.0, B18.0, B18.1, or B19.1 as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment.

Hepatitis C: Those with ICD-9 070.41, 070.44, 070.51, or V02.62 or ICD-10 B17.10, B17.11, B18.2, B19.20, B19.21, or Z22.52 as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment.

NAFLD: Those with ICD-9 571.8, 571.9, or ICD-10 K74.4, K74.5, K74.60, K74.69, K76.0, K76.9, etc. as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment, and without the occurrence of a hepatitis B or C code, for whom the first hospital visit within 365 days was defined as the date of diagnosis. Patients with concurrent viral hepatitis and NAFLD were classified as having viral hepatitis.

Age-based categorization included 20–39, 40–54, 55–64, 65–74, and ≥ 75 years age groups. Monthly salary was divided into five grades, namely ≤ NTD 17,280, NTD 17,281–22,800, NTD 22,801–36,300, NTD 36,301–45,800, and ≥ NTD 45,801. Charlson comorbidity index was divided into 0, 1, 2, and ≥ 3 after excluding scores correlated with independent or dependent variables40.

The diabetes complications severity index (DCSI) was scored as 0, 1, and ≥ 2 points. The DCSI was calculated based on the classification and scoring method proposed by Young et al. If the patient had no complication, the score would be 0; for each complication, 1 point would be added; if the complication was serious, 2 points would be added. Based on this calculation method, the maximum score was 13 points41.

Cardiovascular disease: Those with ICD-9 398.91, 402.xx, 404.xx, 410.xx–414.xx, 422.xx, 425.xx or 428.xx, or ICD-10 I09.81, I11, I13, I20–I22, I24, I25, I40–I43, I50, R09.89, etc. as the primary and secondary diagnosis during two outpatient visits or one hospitalization within 365 days of study enrollment42.

Calculation of the coefficient of variation (CV% = standard deviation/mean) of HbA1c and fasting blood glucose: All measurements in the first year were used, and if the measurements were taken less than four times in the first year, measurements taken up to the second year were included. If measurements were taken less than four times in the 2 years, the patient would be excluded.

Adjusted CV = CV/√ (n/n − 1): When the examination data were limited, the examination times would affect the result of the CV. In this case, a relatively correct result of the CV with a reduced effect of the examination times could be obtained by correcting the examination times.

Analytical methods

Descriptive and inferential statistics were carried out according to the research objectives and framework. All research tests were based on a significance level of α = 0.05, and all statistical analyses were conducted using SAS software for Windows, version 9.4 (SAS Institute Inc., Cary, NC, USA). Descriptive statistics such as frequency, percentage, average, and standard deviation were used to describe the dependent and independent variables to be investigated in this study. This study adopted descriptive statistics to present the demographic characteristics, status of comorbidities, blood biochemical indicators, health status, economic factors, and medical care provider characteristics of patients with diabetes. The incidence of cardiovascular disease in patients with T2DM with chronic hepatitis per 1000 person-years was tested using univariate Poisson regression. The relative risks of cardiovascular disease in the four groups were calculated using a Cox proportional hazards model.