Impact of Coexisting Risk Factors on Outcomes in Patients with Acute Coronary Syndrome: A Real-World Analysis Using the Taiwan Chang Gung Research Database

Background

Acute coronary syndrome (ACS) refers to acute myocardial ischemia and/or infarction due to various degrees of coronary blood flow reduction due to plaque rupture/erosion and thrombosis formation or supply and demand mismatch; ACS presents as unstable angina, non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation myocardial infarction (STEMI) [1]. In the current aging society, ACS is still a major health problem, especially in the elderly population [2]. Elderly patients continue to be at high risk of poor prognosis, are less likely to receive evidence-based care, and have high mortality rates regardless of evidence-based care [3–6]. Advanced age, chronic kidney disease (CKD), diabetes mellitus (DM), multiple vessel disease, partial revascularization, and hemodynamic instability were predictive factors for mortality among patients with ACS [3,7–9]. In the Asian population with ACS, TIMI and GRACE risk scores demonstrated good predictive accuracies, but most studies only focused on the patients with STEMI and short-term prognosis [10,11]. In elderly patients with ACS, 2 of the most common comorbidities are DM and CKD, affecting 20% to 30% of this population [12]. However, few large cohort studies have reported the impact of DM, CKD, and advanced age on the prognosis of Asian patients with ACS.

The Chang Gung Research Database (CGRD) is a database derived from the original medical records of Chang Gung Memorial Hospital (CGMH), which comprises 7 medical institutes spanning from the northeast to southern regions of Taiwan. CGMH, with its 10 070 beds, admits over 280 000 patients annually. Moreover, the CGRD is a multi-institutional, original medical record-based research database that offers extensive overall and disease-specific coverage of Taiwan. It is worth noting that the CGRD exhibits significantly higher severity of comorbidities [13,14]. Studies conducted using the CGRD have been recognized for their high quality and positive impact on healthcare in Taiwan. Notably, the CGRD has been utilized for ACS research to explore the effects of conduction delay and the prognosis of real-world lipid control [15,16].

Therefore, this real-world study used data from the Taiwan CGRD to compare outcomes in patients with ACS, DM, CKD, and advanced age.

Material and Methods

ETHICS STATEMENT:

This retrospective study was approved for human research by the Institutional Review Committee of the Kaohsiung Chang Gung Memorial Hospital (number: 202101103B0) and conformed to the guidelines of the 1975 Declaration of Helsinki. Informed consent was waived because of the retrospective nature of the study and the use of anonymous clinical data in the analysis.

PATIENT POPULATION AND GROUPS:

Patients diagnosed with ACS from January 2005 to December 2019 were recruited and their medical history was obtained from the CGRD, which is the largest healthcare system in Taiwan.

The inclusion criteria were age ≥18 years and a diagnosis of ACS (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 410.xx, 411.xx, and 412.xx, or Tenth Revision [ICD-10] codes I20, I21, and I22). Patients were divided into DM, non-DM, CKD, non-CKD, elderly, and non-elderly groups according to comorbidities and age. CKD was defined as a creatinine clearance (Cockcroft-Gault equation) <60 mL/min. Elderly patients were defined as those aged >75 years old.

BASELINE AND OUTCOME VARIABLES:

Data on general demographics, comorbidities, medication use, gastrointestinal (GI) bleeding, recurrent ACS, cardiovascular (CV) mortality, and all-cause mortality of patients were obtained and compared between the groups with or without risk factors.

DEFINITIONS:

GI bleeding was defined as an episode of coffee ground emesis, hematemesis, melena, or red blood per rectum occurring after an ACS episode and documented by the treating physician [17]. ACS was defined as any group of clinical symptoms compatible with acute myocardial ischemia, and included UA, NSTEMI, and STEMI. CV mortality was defined as CV-related death. All-cause mortality was defined as death from any cause of death.

STUDY ENDPOINTS:

Study endpoints were GI bleeding, recurrent ACS, CV mortality, and all-cause mortality.

STATISTICAL ANALYSES:

Data are presented as mean±standard deviation or numbers (percentages) for descriptive statistics. Clinical characteristics of the 2 groups were compared using the independent sample t test and the chi-square test for categorical variables. Kaplan-Meier curve analysis and hazard ratios (HR) with 95% confidence intervals (CI) were performed using the log-rank test and Cox regression method for GI bleeding, recurrent ACS, CV mortality, and all-cause mortality in the groups during the 3-year follow-up period. Statistical significance was set at P<0.05. All analyses were performed using SAS version 9.4 (SAS Institute. Inc., Cary, NC, USA).

Results

COMPARISON OF BASELINE CHARACTERISTICS BETWEEN PATIENTS WITH AND WITHOUT DM:

This study enrolled 28 163 participants; baseline characteristics and medications are shown in Table 1. Between non-DM (57.9%) and DM (42.1%) populations, older age (non-DM vs DM; 66.02±14.68 years old vs 67.98±12.25 years old; P<0.001), lower prevalence of males (non-DM vs DM; 73.47% vs 62.89%; P<0.001), and higher body mass index (BMI) (non-DM vs DM; 24.67±4.31 kg/m2 vs 25.20±4.42 kg/m2; P<0.001) presented in patients with DM. A significantly higher prevalence of comorbidities, except for chronic obstructive pulmonary disease and smoking, was noted when DM was compared with the non-DM population. A higher prevalence of clopidogrel use and shorter follow-up period were noted in patients with DM.

COMPARISON OF BASELINE CHARACTERISTICS BETWEEN PATIENTS WITH AND WITHOUT CKD:

Between non-CKD (51.8%) and CKD (48.2%) populations, older age (non-CKD vs CKD; 61.69±13.50 years old vs 71.77±12.10 years old; P<0.001), lower prevalence of male sex (non-CKD vs CKD; 76.27% vs 62.18%; P<0.001), and lower BMI (non-CKD vs CKD; 25.38±4.41 kg/m² vs 24.44±4.28 kg/m²; P<0.001) presented in patients with CKD. A significantly higher prevalence of comorbidities, except smoking, was noted when CKD patients were compared with the non-CKD population. A lower prevalence of aspirin, clopidogrel, and ticagrelor use and shorter follow-up period were noted in patients with CKD.

COMPARISON OF BASELINE CHARACTERISTICS BETWEEN NON-ELDERLY AND ELDERLY PATIENTS:

Between non-elderly (66.4%) and elderly (33.6%) populations, older age (non-elderly vs elderly; 59.41±10.17 years old vs 81.86±5.10 years old; P<0.001), lower prevalence of male sex (non-elderly vs elderly; 75.80% vs 55.48%; P<0.001), and lower BMI (non-elderly vs elderly; 25.65±4.27 kg/m² vs 23.26±4.08 kg/m²; P<0.001) presented in elderly patients. A significantly higher prevalence of comorbidities, except DM and smoking, was noted in the elderly than in the non-elderly population. The prevalence of peripheral arterial occlusive disease and liver cirrhosis was similar between the non-elderly and elderly groups. A lower prevalence of aspirin, clopidogrel, and ticagrelor use and a shorter follow-up period were noted in elderly patients.

KAPLAN-MEIER CURVE ANALYSIS AND HRS FOR GI BLEEDING IN PATIENTS WITH DIFFERENT RISK FACTORS DURING THE 3-YEAR FOLLOW-UP PERIOD:

Figure 1A shows the Kaplan-Meier curve analysis for GI bleeding between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).

In patients with 1 risk factor (DM, CKD, or age; Figure 1B), the HRs of GI bleeding were 1.87 (95% CI: 1.48–2.35; P<0.001), 3.39 (95% CI: 2.74–4.18; P<0.001), and 4.33 (95% CI: 3.42–5.50; P<0.001), respectively. In the patients with a combination of 2 risk factors, the HR of GI bleeding was 6.83 (95% CI: 5.26–8.86; P<0.001) for advanced age plus DM, 3.39 (95% CI: 6.58–9.60; P<0.001) for CKD plus advanced age, and 6.21 (95% CI: 5.17–7.45; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of GI bleeding was 11.32 (95% CI: 9.41–13.61; P<0.001) during the 3-year follow-up period.

KAPLAN-MEIER CURVE ANALYSIS AND HRS FOR RECURRENT ACS IN PATIENTS WITH DIFFERENT RISK FACTORS DURING THE 3-YEAR FOLLOW-UP PERIOD:

Figure 2A shows the Kaplan-Meier curve analysis for recurrent ACS between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).

In patients with 1 risk factor (DM, CKD, or age; Figure 2B), the HRs of recurrent ACS were 1.13 (95% CI: 0.99–1.29; P=0.070), 1.63 (95% CI: 1.44–1.85; P<0.001), and 1.62 (95% CI: 1.38–1.91; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of recurrent ACS was 2.20 (95% CI: 1.81–2.67; P<0.001) for advanced age plus DM, 2.35 (95% CI: 2.08–2.66; P<0.001) for CKD plus advanced age, 2.72 (95% CI: 2.45–3.03; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of recurrent ACS was 2.99 (95% CI: 2.65–3.37; P<0.001) during the 3-year follow-up period.

KAPLAN-MEIER CURVE ANALYSIS AND HR FOR CV MORTALITY IN PATIENTS WITH DIFFERENT RISK FACTORS DURING THE 3-YEAR FOLLOW-UP PERIOD:

Figure 3A shows the Kaplan-Meier curve analysis for CV mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).

In patients with 1 risk factor (DM, CKD, or age; Figure 3B), the HRs of CV mortality were 1.19 (95% CI: 1.00–1.42; P=0.057), 4.43 (95% CI: 3.88–5.05; P<0.001), and 4.47 (95% CI: 3.84–5.21; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of CV mortality was 4.53 (95% CI: 3.74–5.49; P<0.001) for advanced age plus DM, 8.76 (95% CI: 7.76–9.89; P<0.001) for CKD plus advanced age, and 4.17 (95% CI: 3.66–4.74; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of CV mortality was 7.29 (95% CI: 6.42–8.29; P<0.001) during the 3-year follow-up period.

KAPLAN-MEIER CURVE ANALYSIS AND HR FOR ALL-CAUSE MORTALITY IN THE PATIENTS WITH DIFFERENT RISK FACTORS DURING THE 3-YEAR FOLLOW-UP PERIOD:

Figure 4A shows the Kaplan-Meier curve analysis for all-cause mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).

In patients with 1 risk factor (DM, CKD, or age; Figure 4B), the HR of all-cause mortality was 1.37 (95% CI: 1.23–1.52; P<0.001), 3.92 (95% CI: 3.60–4.27; P<0.001), and 5.05 (95% CI: 4.60–5.55; P<0.001), respectively. In patients with combination of 2 risk factors, the HR of all-cause mortality was 5.30 (95% CI: 4.72–5.95; P<0.001) for advanced age plus DM, 8.27 (95% CI: 7.66–8.94; P<0.001) for CKD plus advanced age, and 4.75 (95% CI: 4.39–5.15; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of CV mortality was 8.59 (95% CI: 7.94–9.30; P<0.001) during the 3-year follow-up period.

Discussion

STUDY LIMITATIONS:

This study had the limitations of having a retrospective study design and obtaining patient information from medical records. The study focused on the risk factors of DM, CKD, and advanced age and did not explore the effect of coronary artery disease and left ventricular performance severity. We also did not explore the effect of different medical treatments. Nevertheless, our results provide valuable information regarding important factors, including DM, CKD, and advanced age, and the associated clinical outcomes in patients with ACS.

Conclusions

In patients with 3 risk factors (DM, CKD, and advanced age), there was an 11.32-fold increased risk of GI bleeding, 7.29-fold increased risk of CV mortality, and 8.59-fold increased risk of all-cause mortality compared to the population without DM, CKD, and advanced age. Additionally, patients with 2 or more risk factors had a 2- to 3-fold increased risk of recurrent ACS than the population without DM, CKD, and advanced age.