Abstract
Background/Objectives: Acute coronary syndrome (ACS) in old people is a growing global health problem, with high incidence and mortality. The aim of this study was to assess the cardiovascular risk factors in older patients with ACS, with particular emphasis on sex differences. Methods: We retrospectively analyzed 1482 patients with ACS (1184 old patients; men ≥ 55 years and women ≥ 65 years) and 298 young ACS patients (men ≤ 55 years and women ≤ 65 years) from University Clinical Centre of Kosovo. Data on cardiovascular risk factors, echocardiographic, electrocardiographic, angiographic indices and medications were collected from medical records. Results: Old ACS patients had higher prevalence of diabetes (50.1 vs. 34.6%; p < 0.001), hypertension (79.8 vs. 42.8; p < 0.001), multivessel coronary artery disease (88.6 vs. 22.1%; p < 0.001) but less prevalent hypercholesterolemia (31.5 vs. 48.2; p < 0.001), smoking, family history of coronary artery disease and other noncardiac risk factors compared with young ACS patients (p < 0.05, for all). Older women smoked less (26.3 vs. 41.1; p < 0.001) and drank less alcohol (0.8 vs. 6.8%; p < 0.001) but had higher prevalence of uncontrolled diabetes, arterial hypertension and hypercholesterolemia (p < 0.05 for all) compared with older males. Family history for coronary artery disease (CAD) was not significant between groups. Multivariate analysis revealed uncontrolled diabetes (OR = 2.26; 95% CI: 1.104–3.989; p < 0.001) and having three or more cardiac risk factors (OR = 3.141; 95% CI: 2.166–4.406; p < 0.001) as the strongest independent predictors of ACS in old patients. These associations remained significant when stratified by gender, with even stronger impact in female (uncontrolled diabetes OR = 2.942, 95% CI: 1.644–4.890; p < 0.001; ≥3 risk factors OR = 2.821; 95% CI: 1.782–4.436; p < 0.001) and in males who smoked (OR: 2.381, 95% CI: 1.109–2.981; p < 0.001). Conclusions: Uncontrolled diabetes and multiple cardiovascular risk factors are key contributors to ACS in older adults. Early identification and management of these risk factors are essential in reducing the burden of CAD older patients.
1. Introduction
Coronary artery disease (CAD) is the most common type of cardiovascular disease worldwide and remains a leading cause of cardiovascular morbidity, mortality, and reduced quality of life []. The incidence of CAD is projected to rise further, driven not only by the ongoing trend of population aging but also by cardiovascular risk factors, particularly obesity, diabetes, and metabolic syndrome []. Over the past two decades, global population aging has markedly accelerated []. The prevalence of CAD varies substantially across demographic and socioeconomic groups, with older adults, men, and certain ethnic populations exhibiting higher risk. Socioeconomic disadvantage, including unemployment, has also been associated with increased CAD burden, although its contribution remains secondary to traditional cardiovascular risk factors such as hypertension, diabetes, and dyslipidemia. Despite a relatively stable prevalence rate, the absolute number of IHD cases continues to rise, primarily driven by global population aging [,]. CAD remains a public health concern among older people, emphasizing the need for targeted preventive strategies, effective management of modifiable risk factors, and strengthened health system capacity to address the demands of aging populations [].
It is well established that lifestyle and social factors significantly influence not only the prevalence but also the clinical course and outcomes of IHD in older adults, playing a central role in shaping gender disparities []. Men are more likely to adopt high-risk behaviors such as smoking, excessive alcohol consumption, as well as poor dietary habits and physical inactivity, all of which contribute to accelerated atherosclerosis, adverse CV events, and ultimately increased mortality risk [,].
Conversely, women often present with different behavioral and psychosocial risk profiles, including higher levels of stress and depression, which may also negatively impact prognosis [,]. Furthermore, socioeconomic factors amplify these disparities, as unequal access to healthcare, education, and resources between men and women impacts disease diagnosis, treatment, and clinical outcomes. Such inequities not only reinforce existing gender gaps but also contribute to worse morbidity and mortality rates in vulnerable populations [].
Therefore, our study aimed to assess cardiovascular risk factors and sex-related differences in older patients with ACS to enhance understanding of disease characteristics across sexes.
2. Methods
2.1. Study Design and Patients
This retrospective study analyzed 1482 patients with typical ACS treated across tertiary care hospitals. Patients were stratified by age into two groups: old ACS (men ≥ 55 years and women ≥ 65 years; n = 1184) and young ACS (men ≤ 55 years and women ≤ 65 years; n = 298) [,], recruited from the Clinic of Cardiology, University Clinical Centre of Kosovo, between January 2024 and October 2024. Patients who met the inclusion criteria for ACS including typical or atypical chest pain, electrocardiographic changes suggestive of ischemia, and elevated cardiac biomarkers, were retrospectively analyzed. Significant CAD was defined as ≥70% diameter stenosis in a major epicardial vessel (or ≥50% in the left main). Exclusion criteria included normal coronary angiograms, recent major trauma, acute kidney injury, hepatic failure, or hemorrhagic shock.
The study was conducted in accordance with national and institutional guidelines and the revised Declaration of Helsinki. Ethical approval was obtained from the Institutional Ethics Committee of the University Clinical Centre of Kosovo and the Medical Faculty, University of Prishtina (1489/2025). Patient confidentiality was strictly maintained, and all data were used exclusively for research purposes.
2.2. Cardiovascular Risk Factor Assessment
We collected information on CV risk factors based on patients’ medical history at the tertiary care hospital. The data included age, sex, smoking status (classified as current or former smokers, former smoker was defined as an individual who had quit smoking at least six months prior to hospitalization), arterial hypertension (systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg on at least two occasions, or a previous diagnosis of hypertension by a physician/current use of antihypertensive medication) [], diabetes mellitus (physician-diagnosed diabetes or current use of hypoglycemic agents or insulin) [], hypercholesterolemia (total cholesterol ≥ 200 mg/dL [5.2 mmol/L] or current use of lipid-lowering therapy) [], family history of coronary artery disease (first-degree relative with documented coronary artery disease), and alcohol consumption. Uncontrolled diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L or HbA1c ≥ 7.0% despite treatment [,]. Among non-cardiac risk factors, we evaluated thyroid disorders and anemia, as well as additional systemic conditions. Kidney dysfunction in our study was defined based on elevated serum creatinine and/or urea levels above the upper limit of the normal reference range, since eGFR data were not available for most patients. This approach was used as a practical surrogate to indicate impaired renal function in the absence of direct eGFR measurements []. Peripheral arterial disease (PAD) was defined as a prior clinical diagnosis and/or ankle–brachial index (ABI) < 0.90, or angiographically documented ≥50% stenosis in a major peripheral artery []. Carotid artery disease was defined as documented ≥50% carotid stenosis on duplex ultrasound, CT angiography (CTA), or MR angiography (MRA), or a history of prior carotid revascularization [].
2.3. Laboratory and Imaging Assessment
Routine biochemical test results were collected, including complete blood count, fasting blood glucose, cholesterol, triglycerides, albumin, total protein, and kidney and liver function tests.
Echocardiographic data were obtained using standard transthoracic echocardiography performed by experienced cardiologists at the tertiary care hospital, University Clinical Centre of Kosovo. Key echocardiographic parameters included left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), ejection fraction (EF), and atrial dimensions (right and left atria) []. Electrocardiographic (ECG) recordings were analyzed to assess cardiac rhythm and ischemic changes, including T-wave inversion and ST-segment deviations. Information on medications, including angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), beta-blockers, antiplatelet therapy, and lipid-lowering therapy, was obtained from patients’ clinical records.
2.4. Statistical Analysis
Categorical variables were expressed as counts with corresponding percentages, while continuous variables were presented as mean ± standard deviation (SD) or, when not normally distributed, as median with interquartile range (IQR). Comparisons of continuous data between groups were performed using the independent two-tailed Student t-test, and categorical variables were analyzed with the chi-square test. Associations between categorical and continuous variables were assessed using the chi-square test and point-biserial correlation. Potential predictors of ACS were explored through univariate analyses and subsequently adjusted in multivariate models, both in the overall cohort and stratified by sex. A two-sided p value < 0.05 was considered statistically significant. All analyses were carried out using IBM SPSS Statistics, version 26.0 (IBM Corp., Armonk, NY, USA).
3. Results
3.1. Demographic and Clinical Characteristics of ACS Patients by Age Group
Old patients had more prevalent diabetes (50.1% vs. 34.6%; p < 0.001), hypertension (79.8% vs. 42.8%; p < 0.001) and multivessel disease (88.6% vs. 22.1%; p < 0.001) but less prevalent hypercholesterolemia (31.5% vs. 48.2%; p < 0.001), smoking (33.3% vs. 40.5%; p < 0.001), family history of CAD (5.1% vs. 10.7%; p < 0.001) and other noncardiac risk factors compared with young patients (p < 0.05, for all;). Beyond aspirin, clopidogrel was more commonly used in old patients (56.5% vs. 29.8%; p < 0.001), while young patients more frequently received prasugrel (56.1% vs. 29.6%; p < 0.001). Other medications including ACE/ARBs, diuretics and DOAC/VKA were more frequently used by the older patients (p < 0.05 for all). Lipid-lowering therapy was similarly used (p = 0.661) by the two groups. ST changes on ECG were more commonly seen in young ACS (73.3% vs. 58.1%, p < 0.001), while atrial fibrillation is more frequently reported in older patients (7.4% vs. 2.9%; p < 0.05). Previously cardiaovascular events including myocardial infarction, cardiac revascularization, stroke and peripheral artery disease were significantly more frequent in older patients compared to younger patients (p < 0.05 for all; Table 1).
Table 1.
Demographic and clinical data of patients in older compared to young ACS patients.
3.2. Laboratory and Cardiac Imaging Data in Old Versus Young ACS Patients
At admission, older patients had higher fasting blood glucose levels (10.1 ± 6.7 vs. 7.5 ± 4.7 mmol/L; p < 0.001), frequently uncontrolled diabetes (63.1% vs. 43.7%; p < 0.001), and worse renal function (33.9% vs. 12%; p < 0.001) compared to young patients (p < 0.005). In contrast, cholesterol levels different differed between groups, with lower total cholesterol (5.1 ± 3.1 vs. 5.9 ± 1.2 mmol/L; p = 0.061), LDL-C (2.93 ± 1.6 vs. 3.51 ± 1.3 mmol/L; p = 0.041) and HDL-C (1.1 ± 0.9 vs. 1.2 ± 0.7 mmol/L; p = 0.556) in the older group compared to the younger group. Triglycerides were not different between groups (2.1 ± 7.1 vs. 2.1 ± 1.4 mmol/L; p = 0.881) (Table 2). Older patients had significantly more prevalent three-vessel coronary artery disease (88.6 vs. 22.1%, p < 0.001) and less frequently one vessel/two vessel disease and ST segment shift on ECG compared to younger patients (p < 0.001; Table 1). Except left atrial (LA) dilatation, a mild reduction in left ventricular (LV) ejection fraction (EF), and slightly increased LV dimensions in older patients (p < 0.05), no other significant cardiac structure or function differences were found between groups (p > 0.05 for all; Table 1 and Table 2).
Table 2.
Echocardiographic and laboratory indices of patients in older compared young ACS patients.
3.3. Sex Differences in Old ACS Patient Groups
Older male patients had more frequent arterial hypertension (86.1% vs. 74.5%; p < 0.001), smoking (41.1% vs. 26.3%; p < 0.001) and alcohol use (6.8% vs. 0.8%; p < 0.001) while diabetes, uncontrolled diabetes, hypercholesterolemia and number of cardiac risk factors were less prevalent compared to older females (p < 0.05 for all). Among non-cardiac risk factors, thyroid disorders, anemia, and liver diseases were more prevalent in women (p < 0.05 for all; Table 3). ST shift was more prevalent but T inversion and atrial fibrillation less prevalent in older males compared to older females. Prasugrel was frequently used in old males, while clopidogrel and diuretics were more common used in older females. While previous myocardial infarction and revascularization were more frequent in males compared to females, the prevalence of stroke and peripheral artery disease did not differ (Table 3).
Table 3.
Demographic and clinical indices in older compared to young ACS patients by gender.
3.4. Independent Predictors of ACS in Old Patients
Multivariate analysis revealed uncontrolled diabetes (OR = 2.26; 95% CI: 1.104–3.989; p < 0.001) and having three or more cardiac risk factors (OR = 3.141; 95% CI: 2.166–4.406; p < 0.001) as the strongest independent predictors of ACS in old patients, followed by age (OR = 1.261; 95% CI 1.019–2.901; p = 0.011), hypercholesterolemia (OR = 2.001; 95% CI: 1.437–3.971; p = 0.014) and hypertension (OR = 1.121; 95% CI: 1.009–1.741; p = 0.033; Table 4).
Table 4.
Predictors of older ACS.
These associations remained significant when patients were stratified according to sex, with even stronger impact in female (uncontrolled diabetes OR = 2.942; 95% CI: 1.644–4.890; p < 0.001; ≥3 risk factors OR = 2.821; 95% CI: 1.782–4.436; p < 0.001) and in males who smoked (OR: 2.381; 95% CI: 1.109–2.981; p < 0.001; Table 4).
4. Discussion
In our cohort, older patients with ACS exhibited distinct risk factor profiles compared with younger individuals. Diabetes, uncontrolled diabetes, and hypertension were more frequent among older patients, whereas smoking and hypercholesterolemia were less common. Within the older subgroup, men more often presented with arterial hypertension, smoking, and alcohol use, while women showed a higher prevalence of diabetes, hypercholesterolemia, and a greater overall burden of cardiovascular risk factors. Notably, uncontrolled diabetes and the presence of three or more risk factors emerged as the strongest correlates of ACS in older adults, particularly among females.
ACS is more common among older individuals, in whom the cumulative effects of cardiovascular risk factors, diabetes, and hypertension lead to a more advanced and often multivessel form of the disease compared with younger patients [,]. In older ACS patients, diabetes, especially when poorly controlled and together with hypertension, smoking, and alcohol consumption, was more frequently observed. Such age-related clustering of risk factors highlights that their influence on CAD is not uniform, but rather evolves across different stages of the lifespan. [,]. Many researchers have documented the strong genetic contribution to ACS [,]. In our study, a positive family history of cardiovascular disease was less frequent among older patients. This observation likely reflects the higher contribution of inherited and shared early-life factors to premature forms of coronary artery disease. However, given the complexity of genetic and environmental interactions, this interpretation should be viewed as descriptive rather than mechanistic. A first-degree relative with CHD increases the risk 1.5–3-fold, and more than tenfold if the event occurs before age 45. Since atherosclerosis develops silently from early adulthood, familial clustering can accelerate progression even without other risk factors, which explains its greater impact in younger patients [,]. While observational studies have long established the link between smoking and atherosclerotic cardiovascular disease [,,,], recently, Levin et al. analyzed data from over 1.5 million participants across multiple datasets to identify genetic loci related to smoking in large Genome-Wide Association Studies (GWASs) of coronary artery disease, stroke, and peripheral artery disease. Their findings suggest that smoking exerts a direct atherogenic effect, with variable impact across different vascular beds []. Our findings emphasize the importance of gender-related differences in cardiac risk factors []. Although men and women share most traditional risk factors, their relative contribution differs. In younger women, hypercholesterolemia confers a lower risk compared with men. With menopause, however, lipid patterns shift: total cholesterol rises by about 10%, LDL cholesterol by 14%, and lipoprotein(a) by 4–8%, while HDL levels remain stable []. Beyond 65 years of age, women have higher mean LDL cholesterol than men []. Importantly, evidence from a large Japanese cohort showed that statin therapy provides clear primary prevention benefits for women over 55 with moderately elevated cholesterol levels [].
Finally, multivariate analysis showed that uncontrolled diabetes and the presence of three or more cardiac risk factors were the strongest independent predictors of ACS in older patients, followed by increasing age and hypercholesterolemia. These associations remained significant after stratification by gender, with diabetes and clustered risk factors exerting a particularly strong influence in women, while smoking emerged as the most important contributor among men.
Uncontrolled diabetes and multiple cardiovascular risk factors are major contributors to ACS in older adults. Diabetes accelerates atherosclerosis, worsens endothelial dysfunction, and heightens vascular inflammation, thereby amplifying ischemic risk. When these processes act in concert with other risk factors, their impact becomes synergistic, leading to higher incidence and severity of coronary artery disease. Early detection and timely management through strict glycemic control, blood pressure and lipid regulation, lifestyle changes, and appropriate pharmacotherapy are essential for reducing future coronary events, with their known impact on cardiac performance and its consequences [,].
Study limitations: Our study has certain limitations that merit consideration. Firstly, laboratory data were incomplete, particularly lipoprotein(a) which is an established cardiovascular risk factor that might have provided additional insights. Secondly, the echocardiographic evaluation was not comprehensive. Advanced imaging parameters, including strain, strain rate, and wall motion score index, which offer valuable information on left ventricular intrinsic myocardial function, were not systematically assessed, because of the acute scenario. Another limitation of our study is that patients were not analyzed according to their clinical presentation or the specific type of acute coronary syndrome (STEMI, NSTEMI, or unstable angina). Finally, the retrospective nature of the study is associated with inherent constraints, such as missing data, unmeasured confounders, and the inability to establish causal inferences.
Conclusion: Uncontrolled diabetes and multiple cardiovascular risk factors are key contributors to acute coronary syndrome in older adults. Early identification and management of these risk factors are essential in reducing the burden of coronary artery disease in old patients.
Author Contributions
I.B. and S.T.: Conceptualization, study design, methodology and project administration; I.B., V.H., E.D. (Endrit Dragusha), E.D. (Enera Dragusha) and S.M.: data analysis and writing the first draft of manuscript. I.B., M.Y.H., S.T.: Review manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Ethical approval was obtained from the Institutional Ethics Committee of the Doctors Chamber of Kosovo and the Medical Faculty, University of Prishtina (1489/21 February 2025).
Informed Consent Statement
Patient consent was waived due to the retrospective and anonymized nature of the data analysis, as approved by the Ethics Committee.
Data Availability Statement
Data may be made available by the corresponding author upon reasonable request and with approval from the institutional ethics committee.
Conflicts of Interest
The authors declare no conflicts of interest.
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