JCDR - Register at Journal of Clinical and Diagnostic Research
Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X
Internal Medicine Section DOI : 10.7860/JCDR/2017/27504.10281
Year : 2017 | Month : Jul | Volume : 11 | Issue : 7 Full Version Page : OC34 - OC39

Prevalence of Conventional Risk Factors and Evaluation of Baseline Indices Among Young and Elderly Patients with Coronary Artery Disease

Arsalan Majeed Adam1, Aiman Rehan2, Nageen Waseem3, Unzela Iqbal4, Hira Saleem5, Muhammad Armughan Ali6, Ali Tariq Shaikh7, Ansab Godil8

1 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
2 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
3 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
4 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
5 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
6 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
7 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.
8 Student, Department of Medicine, Dow University of Health Sciences, Karachi, Sindh, Pakistan.


NAME, ADDRESS, E-MAIL ID OF THE CORRESPONDING AUTHOR: Dr. Arsalan Majeed Adam, 149/E, BLOCK 2, PECHS, Karachi-75400, Sindh, Pakistan.
E-mail: arsalan-56@hotmail.com
Abstract

Introduction

Coronary Artery Disease (CAD) is a leading cause of morbidity and mortality worldwide, manifesting in a variety of clinical spectrums such as an asymptomatic disease or acute coronary syndrome. It has become highly prevalent in Southeast Asia, including Pakistan. There has been little work done on the prevalence of traditional risk factors in different age groups and genders and there is a dire need to gauge the importance of baseline indices in CAD patients.

Aim

To determine the prevalence of conventional risk factors and evaluate the variations in lipid profiles, electrolyte levels and haematological indices among patients with CAD in different age groups and gender.

Materials and Methods

This cross-divtional study was carried out in a Tertiary Care Hospital in Karachi, Sindh, Pakistan from January to June 2016, among patients with CAD. We recorded the presence of conventional risk factors and baseline indices within the first 24 hours of admission. Continuous variables were compared using Independent t-test or Mann-Whitney test and categorical variables were compared using chi-square or Fisher’s exact test.

Results

The most frequent risk factor was dyslipidemia (91.2%), followed by hypertension (70.4%), diabetes (51.2%), family history of CAD (40.0%) and smoking (29.2%). Total of 98.4% of patients had at least one risk factor. Diabetes and hypertension were found to be common in females; whereas, smoking was predominantly present in males. Diabetes and dyslipidemia were mostly encountered in elderly patients. The most frequent lipid alteration was low levels of High Density Lipoprotein (HDL). Cholesterol and HDL levels were found to be higher in females than males. Elderly patients had lower levels of HDL and higher levels of Cholesterol. The levels of haematological indices were found to be higher in males and younger patients. The median levels of serum sodium and potassium were found to be higher in elderly patients.

Conclusion

Our study findings corroborate with the findings from previous studies regarding the significance of risk factors in causing cardiovascular pathology. Medical interventions and dietary control to improve body’s lipid status would be indispensable in the prevention of CAD. Deranged electrolyte levels necessitate correction of body electrolyte parameters as an adjunct in prevention strategies.

Keywords

Introduction

CAD is a common multifactorial atherosclerotic pathology characterised by an insufficient supply of oxygen rich blood to the myocardium due to narrowing or blocking of a coronary artery [1]. It comprises a spectrum of clinical manifestations ranging from asymptomatic atherosclerotic disease to Acute Coronary Syndrome (ACS), which includes ST-Elevation Myocardial Infarction (STEMI), Non-ST-Elevation Myocardial Infarction (NSTEMI) and Unstable Angina (UA). By 2020, CAD is likely to be the major cause of global morbidity and mortality. Pakistan, being a part of Southern Asia has high rates of CAD, manifesting at quite an earlier age [2]. This calls for effective preventive strategies.

The study conducted in Pakistan reported that 91% of individuals had at least one of four conventional risk factors [3]. However, these risk factors differ according to age group as well as gender [4]. There is hardly any data which examined age and gender differences in the prevalence of conventional risk factors. Therefore, our study will contribute to a better understanding of gender and age differences that exist in our patients with CAD.

Dyslipidemia is a well known risk factor for the development of CAD. Variations in lipid profiles are prevalent in ACS patients, with differing levels of cholesterol, [Low Density Lipoprotein (LDL), HDL] and triglycerides after an episode of acute cardiac injury [5]. However, there is a paucity of data on studies evaluating the variations of lipid profiles in Pakistani patients with CAD. Initiation of lipid-lowering therapy can only be strictly followed once we have accurate data regarding the variations in lipid profile. This knowledge would also help us to stress on the importance of lipid lowering therapy and hence, indirectly aid in increasing patient compliance and adherence [6].

In addition, imbalances in electrolyte levels may occur within the first few hours of ACS, giving rise to life threatening arrhythmias [7]. Therefore, a thorough comparison of standard electrolyte levels like sodium (Na), potassium (K) and magnesium (Mg) among our patients may help prevent such fatalities.

The White Blood Cell (WBC) count has been proved to be a strong independent predictor of mortality in ACS patients and is linked to the presence of conventional risk factors [8]. Moreover, Platelet Distribution Width (PDW) and Red Cell Distribution Width (RDW) have also recently been found to influence outcomes in ACS patients [9]. A better understanding of more parameters like Hemoglobin (Hb), Red Blood Cell (RBC) count, Haematocrit (Hct) and platelet count may help establish a better prognosis and approach towards treatment.

The aim of this study was to determine the prevalence of conventional risk factors and to evaluate the variations in lipid profiles, electrolyte levels and haematological indices among patients with CAD in different age groups and gender.

Materials and Methods

This cross-sectional study was conducted at a Tertiary Care Hospital in Karachi, Sindh, Pakistan. The study duration was six months from January to June 2016. The study was approved by the local Ethical Committee and patients’ informed consent was taken. All the patients visiting Cardiology Emergency Ward were evaluated, selected via convenience sampling and only those with confirmed diagnosis of ACS and CAD were included in the study. A total of 300 patients were selected; however, 50 patients refused to become part of the study. This yields a final sample size of 250.

ACS patients were diagnosed and categorised using the criteria defined by American Heart Association [10]. CAD was diagnosed after a patient underwent coronary angiography. Only those patients with > 50% stenosis of any of the coronary arteries were included.

Patients were excluded if they had received anticoagulant therapy or immunosuppressants, received statins or any other lipid decreasing agents, had conditions which put them at high risk of serious bleeding, were diagnosed with cancer, active infectious diseases or inflammatory diseases or severe liver disease.

The detailed history of patients was taken at the time of admission and all baseline laboratory tests [Complete Blood Count (CBC), electrolyte levels and lipid profile] were carried out. The blood sample was drawn within 30 minutes of admission. All the conventional risk factors were recorded after confirmation from previous medical history. Dyslipidemia was defined as high levels of serum cholesterol >200 mg/dl, high levels of serum triglycerides >150 mg/dl, high levels of serum LDL >130 mg/dl and low serum levels of HDL <40 mg/dl.

An automated haematology analyzer, SYSMEX XN-1000 was used to measure haematological indices. Electrolyte levels were measured by Roche Cobas c501 chemistry analyzer (Roche Diagnostics). Fasting lipid panels were measured by standard enzymatic methods.

Statistical Analysis

The data was tested for normality by Shapiro-Wilk test. Patients were stratified by gender and age for analysis. Continuous variables were presented as mean ± Standard Deviation (SD) and median Interquartile Range (IQR). Categorical variables were expressed as frequency (percentages). The difference between the groups was compared using Student’s t-test or Mann Whitney test and, chi-square test or Fisher’s exact test for continuous and categorical variables, respectively. A two tailed p-value of less than 0.05 was considered statistically significant. All analyses were performed with SPSS Statistics, version 17.0 (IBM SPSS Inc., Chicago, IL).

Results

Baseline characteristics and clinical presentation of patients is shown in [Table/Fig-1]. In total, 65.2% (n=163) of the patients were males and 34.8% (n=87) were females. Patients were divided into two groups according to their age, those within the age bracket of 18-45 years were considered younger patients while those >45 years were considered elderly patients. Mean age of patients enrolled in this study was 41.3 ± 5.0 years for younger groups and 64.1 ± 7.0 years for elderly patients. Males on average were nearly five years younger than females (p=0.006). The mean levels of Systolic Blood Pressure (SBP) (p=0.027) and Left Ventricular Ejection Fraction (LVEF) (p<0.001) were higher in females. At the time of admission, prior Myocardial Infarction (MI) (p<0.001) and history of Chronic Kidney Disease (CKD) (p=0.010) was more frequent in elderly patients than in young ones. Moreover, a greater percentage of females had a history of prior MI than males (p=0.032). The levels of Creatine Kinase (CK) (p<0.001) and CK-MB (p<0.001) were found to be higher in males than in females. Similarly, there was a greater frequency of male patients with Troponin T positive as compared to female patients (p<0.001).

Baseline characteristics and clinical presentation of patients.

CharacteristicsGenderAge Group (years)
Male(n=163)Female(n=87)ap-value18 to <45(n=102)>45(n=148)ap-value
Age [years]53.17+12.6557.85+12.73b0.00641.29+5.0464.11+6.95b<0.001
Male, n (%)---65 (63.7%)98 (66.2%)0.685
Area (Urban), n (%)120 (73.6)63 (72.4)0.83871 (69.6)112 (75.7)0.287
Heart rate [bpm]82.84+15.7084.25+18.10b0.52184.73+15.1682.36+17.44b0.267
Systolic BP [mm Hg]126.53+27.92135.15+31.30b0.027129.00+30.34129.90+28.77b0.813
Diatolic BP [mm Hg]80.99+18.6983.26+19.78b0.36981.80+18.8481.76+19.29b0.986
LVEF [%]44.52+11.7750.93+10.13b<0.00145.92+11.9347.32+11.40b0.351
Medical History, n (%):
Prior MI78 (47.9)54 (62.1)0.03237 (36.3)95 (64.2)<0.001
Prior PCI22 (13.5)14 (16.1)0.57820 (19.6)16 (10.8)0.052
Prior CABG6 (3.7)1 (1.1)d0.4274 (3.9)3 (2.0)d0.448
CKD12 (7.4)9 (10.3)0.4183 (2.9)18 (12.2)0.010
NODV, n (%):0.9580.612
Single-vessel disease69 (42.3)36 (41.4)43 (42.2)62 (41.9)
Two-vessel disease50 (30.7)26 (29.9)28 (27.5)48 (32.4)
Three-vessel disease44 (27.0)25 (28.7)31 (30.4)38 (25.7)
NYHA, n (%):0.3910.171
144 (27.0)15 (17.2)23 (22.5)36 (24.3)
265 (39.9)39 (44.8047 (46.1)57 (38.5)
329 (17.8)18 (20.7)13 (12.7)34 (23.0)
425 (15.3)15 (17.2)19 (18.6)21 (14.2)
Killip Class, n (%):0.5920.238
198 (60.1)59 (67.8)57 (55.9)100 (67.6)
245 (27.6)18 (20.7)31 (30.4)32 (21.6)
38 (4.9)5 (5.7)5 (4.9)8 (5.4)
412 (7.4)5 (5.7)9 (8.8)8 (5.4)
Cardiac Enzymes:
CK [IU/L]281.00 (603.80)99.00 (118.50)c<0.001198.50 (463.60)154.00 (359.50)c0.421
CK-MB [IU/L]53.75 (51.80)34.00 (25.00)c<0.00145.00 (43.80)46.25 (54.70)c0.767
Troponin T +124 (76.1)41 (47.1)<0.00171 (69.6)94 (63.5)0.317

ap value <0.05 were considered statistically significant; bIndependent t-test and cMann Whitney U test was used to compare quantitative data without normal distribution. dFisher’s exact test and x2 test (Pearson’s chi-square test) were used to compare categorical variables. Data presented as mean+standard deviation, median (interquartile range) and frequency (percentages).

BP: blood pressure; LVEF: left ventricular ejection fraction; CK: creatinine kinase; CK-MB: creatine kinase MB isoenzyme; MI: myocardial infarction; NYHA: New York Heart Association; CABG: coronary artery bypass grafting: PCI: percutaneous coronary intervention; CAD: coronary artery disease; UA: unstable angina; NSTEMI; non-ST elevation myocardial infarction; STEMI: ST elevation myocardial infection; NODV: number of diseased vessel


In the studied sample, the most prevalent risk factor was dyslipidemia (91.2%), followed by hypertension (70.4%), diabetes (51.2%), family history of CAD or MI (40.0%) and smoking (29.2%). Diabetes (p<0.001) and dyslipidemia (p=0.001) were more frequent in elderly patients than in young ones while smoking (p=0.431), hypertension (p=0.957) and family history of CAD or MI (p=0.401) were similar between the two groups. Diabetes (p=0.012) and hypertension (p=0.024) were more frequent in females than in males while smoking (p<0.001) was more frequent in males than in females. Frequency of dyslipidemia (p=0.529) and family history of CAD or MI (p=0.255) were similar in both genders. 98.4% of all patients presented with at least one risk factor: 10.4% had one, 25.2% had two, 33.2% had three, 26.4% had four and 3.2% had all five risk factors [Table/Fig-2].

The prevalence of conventional risk factors in different age group and gender.

CharacteristicsGenderAge Group (years)
Male(n=163)Female(n=87)ap-value18 to <45(n=102)>45(n=148)ap-value
Conventional risk factors, n (%):
Smoking65 (39.9)8 (9.2)<0.00127 (26.5)46 (31.1)0.431
Diabetes74 (45.4)54 (62.1)0.01237 (36.3)91 (61.5)<0.001
HTN107 (65.6)69 (79.3)0.02472 (70.6)104 (70.3)0.957
Dyslipidemia150 (92.0)78 (89.7)0.52986 (84.3)142 (95.9)0.001
Family History of CAD or MI61 (37.4)39 (44.8)0.25544 (43.1)56 (37.8)0.401
Number of Risk Factors, n (%):0.1860.207
02 (1.2)2 (2.3)0.5202 (2.0)2 (1.4)0.706
119 (11.7)7 (8.0)0.37315 (14.7)11 (7.4)0.064
244 (27.0)19 (21.8)0.37130 (29.4)33 (22.3)0.203
350 (30.7)33 (37.9)0.24631 (30.4)52 (35.1)0.434
440 (24.5)26 (29.9)0.36122 (21.6)44 (29.7)0.150
58 (4.9)0 (0.0)b0.0532 (2.0)6 (4.1)0.478

ap<0.05 was considered statistically significant

bFisher’s exact test and x2 test (Pearson’s chi-square test) were used to compare categorical variables.

Data presented as frequency (percentages).

HTN: hypertension; CAD: coronary artery disease; MI: myocardial infarction


The blood lipid analysis illustrated that mean levels were 168.13±69.49 mg/dl for triglycerides, 90.90±25.42 mg/dl for LDL, 35.88±5.49 mg/dl for HDL and 169.44±38.75 mg/dl for cholesterol. Cholesterol levels were found to be higher in females than in males (p<0.001) and higher in elderly patients than in younger ones (p=0.002). HDL levels were found to be higher in females than in males (p=0.032) and higher in younger patients than in older ones (p<0.001). At least one abnormal level in lipid profile was found in 91.2% of patients and this finding was more frequent in elderly patients than in young ones (p<0.001). The most frequent lipid alteration was low levels of HDL (78.0%), followed by high levels of triglycerides (57.2%), high levels of cholesterol (24.4%) and high levels of LDL (3.6%) [Table/Fig-3].

Lipid profile status in different age group and gender.

CharacteristicsGenderAge group (years)
Male(n=163)Female(n=87)ap-value18 to <45(n=102)>45(n=148)ap-value
Lipid profile:
Cholesterol [mg/dl]157.73+33.21191.38+39.05b<0.001160.92+29.80175.31+43.00b 0.002
Cholesterol >200 [mg/dl], n (%)22 (13.5)39 (44.8)15 (14.7)46 (31.1)
Cholesterol <200 [mg/dl], n (%)141 (86.5)48 (55.2)<0.00187 (85.3)102 (68.9)0.003
HDL [mg/dl]34.91+6.2936.57+4.81b0.03237.68+4.8233.98+6.05b<0.001
HDL >40[mg/dl], n (%)26 (16.0)29 (33.3)36 (35.3)19 (12.8)
HDL <40[mg/dl], n (%)137 (84.0)58 (66.7)0.00266 (64.7)129 (87.2)<0.001
LDL [mg/dl]88.88+24.9894.69+25.94b0.08591.95+23.5390.17+26.69b0.588
LDL >130 [mg/dl], n (%)5 (3.1)4 (4.6)2 (2.0)7 (4.7)
LDL <130 [mg/dl], n (%)158 (96.9)83 (95.4)0.723100 (98.0)141 (95.3)0.317
Triglycerides [mg/dl]167.78+72.39168.78+64.10b0.914172.78+74.29164.93+66.05b0.381
Triglycerides >150[mg/dl], n (%)90 (55.2)53 (60.9)60 (58.8)83 (56.1)
Triglycerides <150[mg/dl], n (%)73 (44.8)34 (39.1)0.38542 (41.2)65 (43.9)0.667
Dyslipidemia, n (%):150 (92.0)78 (89.7)0.52986 (84.3)142 (95.9)0.001

ap value <0.05 were considered statistically significant; bIndependent t-test was used to compare quantitative data.

Data presented as mean+standard deviation and frequency (percentages). HDL: high density lipoprotein; LDL: low density lipoprotein


The level of Hb, RBC and Hct was found to be higher in males than in females (Hb: p<0.001; RBC: p<0.001; Hct: p<0.001) and higher in younger patients than in older ones (Hb: p=0.001; RBC: p=0.014; Hct: p=0.042). Similarly, the levels of WBC count, neutrophils and lymphocytes were found to be higher in males than females (WBC: p=0.002; neutrophils: p<0.001; lymphocytes: p=0.035) and higher in young patients than in older ones (WBC: p=0.003; neutrophils: p<0.001; lymphocytes: p<0.001). Platelet count was found to be lower in elderly patients than in young ones (p<0.001). The median levels of serum Na (p<0.001) and serum K (p<0.001) were found to be considerably higher in elderly patients than in young ones. In addition, there was a statistically significant decrease in serum K levels in females as compared to males (p<0.001). The levels of other electrolytes were similar in different age groups and gender [Table/Fig-4].

The status of electrolytes and haematological indices in different age group and gender.

CharacteristicsGenderAge Group (years)
Male (n=163)Female (n=87)ap-value18 to <45 (n=102)>45 (n=148)ap-value
Haematological indices:
WBC count [×103/μL]12.39+3.4010.66+5.41b0.00212.76+3.4411.12+4.67b0.003
Neutrophil [×103/μL]7.16+1.236.53+1.0.4b<0.0017.29+1.076.70+1.23b<0.001
Lymphocyte [×103/μL]2.82+1.052.56+0.87b0.0353.21+0.802.40+0.99b<0.001
Hemoglobin [gm/dl]13.02+2.1610.21+2.26b<0.00112.64+2.0611.64+2.80b0.001
RBC count [×106/μL]4.77+0.773.99+0.74b<0.0014.66+0.784.39+0.87b0.014
Haematocrit [%]39.15+6.0533.22+5.81b<0.00138.11+5.8136.39+7.02b0.042
Platelet count [×103/uL]253.18+105.16269.60+95.73b0.227292.53+127.01235.72+72.41b<0.001
MPV [fL]10.40+1.1910.61+1.24b0.18310.57+1.1910.41+1.22b0.305
RDW [%]14.60 (2.30)14.60 (2.60)c0.45514.50 (2.13)14.65 (2.75)c0.367
Electrolytes:
Sodium [mEq/L]136.0 (6.5)136.0 (6.0)c0.667135.00 (6.00)137.00 (8.00)c<0.001
Potassium [mEq/L]4.30 (0.82)4.00 (0.90)c<0.0014.05 (0.80)4.30 (0.98)c<0.001
Chloride [mEq/L]97.43+8.5497.89+7.86b0.67697.61+10.8797.57+5.95b0.971
Magnesium [mg/dl]2.11+0.172.07+0.21b 0.1922.11+0.182.08+0.19b0.287
Calcium [mg/dl]8.93+0.498.95+0.46b 0.7648.92+0.538.94+0.44b 0.636
Phosphate [mg/dl]3.37+0.593.30+0.55b 0.3633.31+0.613.36+0.55b 0.499

ap value <0.05 were considered statistically significant; bIndependent t-test and cMann Whitney U test was used to compare quantitative data without normal distribution.

Data presented as mean+standard deviation and median (interquartile range)

WBC: white blood cell; RBC: red blood cell; MPV: mean platelet volume; RDW: red cell distribution width; BUN: blood urea nitrogen


A detailed literature review was done and a comparison of the main findings of the present study with all the relevant studies from South East Asia is shown in [Table/Fig-5].

Comparison of the findings of present study with other studies from South East Asia.

AuthorYearType of StudySize of PopulationStudiedFindings of this StudyFindings of Our Study
James C et al., [35] 2013Cross-sectional Study496Irrespective of gender, diabetes and dyslipidemia were found to be the major risk factors owing to CAD.Dyslipidemia and HTN were found to be the top two contributing factors to CAD.
Khan MA et al., [36] 2012Retrospective Study3025The frequency of CAD showed a significant increase in the local population, more so in women. There was increasing trend of CAD in the younger age group over the time span.The majority of the patients enrolled in our study were males and of the older age bracket, however we did not investigate this trend over the years.
Butt Z et al., [3] 2010Cross-sectional Study100Females have a higher prevalence of diabetes and HTN and less prevalence of smoking as compared to males.Consistent with the findings of this study.
Jayachandra S et al [4] 2014Cross-sectional Study190HTN and smoking were the most common risk factors in young patients. Along with HTN, diabetes and CKD were found in elderly patients.Diabetes and dyslipidemia were more frequent risk factors in elderly patients, whereas smoking, HTN and a family history of MI or CAD were similar between the two age groups.
Saleheen D et al., [14] 2004Cross-sectional Study976Majority of the patients admitted were males and older than 45 years of age. Young AMI patients had a positive history of HTN, family history of CAD, high cholesterol, high LDL and high triglycerides as compared to older patients.Majority of the patients enrolled were males and in the older age bracket. HTN and a positive family history of CAD as risk factors were common between the two age groups. High cholesterol levels were more prevalent in the older age bracket.
Goel PK et al [22] 2002Retrospective Study2656In north Indians, CAD occurs at much lower levels of total cholesterol and LDL. Hypertriglyceridemia is widely prevalent in this population. Smoking and family history of CAD were most commonly associated risk factors in younger patients.Dyslipidemia and HTN were most commonly associated risk factors in younger patients
Naqvi SM et al., [23] 2015Prospective Observational Study162Mean Hb levels decreased as the severity of CAD increased, however this association was not statistically significantMean Hb levels and red cell indices were higher in males and those in the young age bracket. We did not see the correlation of Hb with the severity of the disease.

AMI: acute myocardial infarction; CAD:coronary artery disease; CKD: chronic kidney disease; Hb: hemoglobin; HTN: hypertension; LDL: low density lipoprotein; MI: myocardial infarction


Discussion

Worldwide, the incidence of CVD is increasing, especially in the middle-income and low-income countries. The escalation in the number of patients succumbing to CVD is fundamentally due to the rising prevalence of the conventional risk factors which, if tackled could significantly reduce the burden of CVD [11].

A total 98.4% of the patients included in our study presented with at least one conventional risk factor out of five. This figure was even higher than the one reported in the study done in Mexico City, in which 95.7% of the patients had a conventional risk factor present; however, that study did not include past history of CAD/MI as an identifiable risk factor [7]. Greenland P et al., on his analysis of three cohort studies concluded that there was a high occurrence of at least one or more conventional risk factors in patients with varying outcomes of CAD [12]. The number and presence of conventional risk factors being interlinked with hospital mortality in patients who suffer from a first MI was discussed by Canto JG et al., who corroborated that 81% of patients included, had three identifiable risk factors present [13].

Dyslipidemia was found to be the most frequent risk factor (91.2%) in our sample. This is similar to the finding by Saleheen D et al., in which the comparison of risk factor profiles in both young and old patients revealed that dyslipidemias, specifically low HDL levels, were the most commonly encountered risk factor [14]. However, this is in contrast to the findings of the INTERHEART study, which included 29000 individuals from 52 different countries and established that smoking and an unusual relation between apolipoprotein B/apolipoprotein A-1 were the two common risk predictors for an acute MI [11].

Diabetes and dyslipidemias were both shown to be higher in elderly patients as compared to young patients. This lines up with previously published literature that shows that diabetes is more common in the elderly [15]. Hypertension was shown to be a more common finding in females than in males (79.3% vs 65.6%). Mansur AP et al., in his study, says that systemic arterial hypertension was found to be the major risk factor for females to develop CAD both before and after menopause [16]. Smoking, however, was more common in males i.e., 39.9% as female smoking in Pakistan is against conservative beliefs.

Fresco C et al., evaluated the changes in lipid levels in patients who had a MI or an event of UA [17]. Total cholesterol and LDL-C levels underwent a change of 7% and 10% respectively in those who had experienced MI and 5% and 6% in those with UA taken from the time of admission to the next morning. Owing to the marked changes that occur in lipid profiles following ACS, current guidelines emphasize on the measurement of serum lipids after admission for ACS patients. Testing of lipid levels and their comparison with baseline values play a role in helping to determine whether a patient has ‘dyslipidemia’ and also aid in the selection and quantization of lipid lowering therapy.

In addition to the importance of elevated total cholesterol and LDL-C levels in cardiovascular events, low HDL-C levels have also been shown to be independent risk predictors for CAD [18] hence, were included in our study. The most frequent lipid alteration was low levels of HDL i.e., 78%. This is in accordance with previous studies done on ACS patients [19]. Low levels of HDL can be credited to the rising prevalence of diabetes, obesity and metabolic syndrome [20]. Elevated cholesterol was also noted in 24.4% of the patients in our study. Previous literature describes that South Asians ‘total cholesterol and LDL-C levels are comparable to those of whites and Afro-Caribbean, but they have higher triglyceride and low HDL-C levels [21]. Goel PK et al., discussed how the South Asian population has a lower set value of hypercholesterolemia for the development of CAD [22].

A previous study conducted showed that haemoglobin levels in ACS patients were higher in men than in women [23]. This lines up with the findings of our study in which males were found to have higher levels of Hb, Hct and RBC count, however it also showed that anaemia was more prevalent in females. The RBC indices were also lower in elderly patients. Mahlknecht U and Kaiser S conducted a study on 1724 hospitalized patients to see if age affected their peripheral blood indices and the results showed that erythropoiesis related indices were, indeed, affected by progressing age [24]. This can be attributed to reduced number of haematopoietic stem cells, finite cell divisions and ineffective progenitor cells [25,26]. It is important to take notice of these varying Hb levels, as baseline Hb acts as prognostic indicators after an ACS episode [27].

The levels of WBC count, neutrophils and lymphocytes were found to be higher in males and in young patients, which is consistent with previous studies [28,29]. It is well established that smoking increases the leukocyte count and this has been documented in multiple studies [30,31]. Since smoking, in Pakistan, is a more common culture in young males, it can justify the elevated leukocyte count. In a study of patients presenting with chest pain, smokers as compared with nonsmokers had an increased WBC count and epicardial coronary endothelial dysfunction [32]. Our study demonstrated a lower WBC count in the elderly as compared to young patients. Bone marrow depression and a decreased turnover is commonly present in the aged which decreases the WBC count, in general, as well as in ACS patients.

There is a lack of literature on how baseline electrolyte levels vary during CAD; however, it is well established that electrolyte abnormalities like hypokalemia can lead to fatal arrhythmias and hence, there is a need to implement proper supplementation [7]. Our study revealed that the median levels of Na and K were significantly higher in elderly patients (p<0.001). Peng Y et al ., aimed to showcase the association between K levels and long term mortality after ACS and his study also corroborated with the finding that K levels increased with age [33]. The Centre of Disease Control revealed that hypokalemia owing to renal dysfunction was more prevalent in females, which supported our finding of statistically significant decreased serum K levels in females (4.0 vs. 4.3). Hence, anomalies in electrolyte levels not only lead to severe ventricular arrhythmias, but may also help in predicting renal dysfunction, which, even when mild, is associated with an increased chance of mortality after ACS [34].

Limitation

This study had certain limitations. Being a single center cross-sectional study, the sample size was small and geographically limited. Therefore, it is necessary to do a large population based study in order to adequately identify the conventional risk factor associations, as well as the changes that occur in baseline indices of CAD patients. Identification of risk factor was based on the information given by patients or their family members and, hence, may be erroneous. The lipid profile, haematological indices and electrolyte levels were from blood samples taken only once within the first 24 hours of admission.

Conclusion

Our study documented a strikingly high prevalence of conventional risk factors among the Pakistani population with CAD. The most commonly reported risk factor was dyslipidemia, followed by hypertension and diabetes. Therefore, appropriate and timely efforts are needed to reverse dyslipidemia and also, decrease the burden of metabolic abnormalities. We also evaluated significant variations in baseline indices. Early assessment of these indices may help to implement proper supplementation and reduce the severity and possible implications of CAD.A large multicentre research focusing on novel biochemical markers like hs-CRP, homocysteine, fibrinogen and apo-B is required to design a proper preventive strategy specifically for the Pakistani population, who are at a higher risk for developing CAD.

ap value <0.05 were considered statistically significant; bIndependent t-test and cMann Whitney U test was used to compare quantitative data without normal distribution. dFisher’s exact test and x2 test (Pearson’s chi-square test) were used to compare categorical variables. Data presented as mean+standard deviation, median (interquartile range) and frequency (percentages).BP: blood pressure; LVEF: left ventricular ejection fraction; CK: creatinine kinase; CK-MB: creatine kinase MB isoenzyme; MI: myocardial infarction; NYHA: New York Heart Association; CABG: coronary artery bypass grafting: PCI: percutaneous coronary intervention; CAD: coronary artery disease; UA: unstable angina; NSTEMI; non-ST elevation myocardial infarction; STEMI: ST elevation myocardial infection; NODV: number of diseased vesselap<0.05 was considered statistically significantbFisher’s exact test and x2 test (Pearson’s chi-square test) were used to compare categorical variables.Data presented as frequency (percentages).HTN: hypertension; CAD: coronary artery disease; MI: myocardial infarctionap value <0.05 were considered statistically significant; bIndependent t-test was used to compare quantitative data.Data presented as mean+standard deviation and frequency (percentages). HDL: high density lipoprotein; LDL: low density lipoproteinap value <0.05 were considered statistically significant; bIndependent t-test and cMann Whitney U test was used to compare quantitative data without normal distribution.Data presented as mean+standard deviation and median (interquartile range)WBC: white blood cell; RBC: red blood cell; MPV: mean platelet volume; RDW: red cell distribution width; BUN: blood urea nitrogenAMI: acute myocardial infarction; CAD:coronary artery disease; CKD: chronic kidney disease; Hb: hemoglobin; HTN: hypertension; LDL: low density lipoprotein; MI: myocardial infarction

References

[1]Coronary heart disease | pathology [Internet]. Encyclopedia Britannica. 2017 [cited 20 January 2017]. Available from: https://www.britannica.com/science/coronary-heart-disease  [Google Scholar]

[2]Nishtar S, Wierzbicki AS, Lumb PJ, Lambert-Hammill M, Turner CN, Crook MA, Waist-hip ratio and low HDL predict the risk of coronary artery disease in Pakistanis Curr Med Res Opin 2004 20(1):55-62.  [Google Scholar]

[3]Butt Z, Shahbaz U, Hashmi AT, Naseem T, Khan MM, Bukhari MH, Frequency of conventional risk factors in patients with acute coronary syndrome in males and females Annals of King Edward Medical University 2010 16(1):56  [Google Scholar]

[4]Jayachandra S, Agnihotram G, Rao RP, Murthy CV, Risk factor profile for coronary artery disease among young and elderly patients in Andhra Pradesh Heart India 2014 2(1):11  [Google Scholar]

[5]Rosenson RS, Myocardial injury: The acute phase response and lipoprotein metabolism JACC 1993 22(3):933-40.  [Google Scholar]

[6]Vargas-Barrón J, Vallejo M, Piña-Reyna Y, Martínez-sánchez C, Prevalence of conventional risk factors and lipid profiles in patients with acute coronary syndrome and significant coronary disease Therapeutics and Clinical Risk Management 2014 10:815-23.  [Google Scholar]

[7]Maciejewski P, Bednarz B, Chamiec T, Górecki A, Łukaszewicz R, Ceremuzyński L, Acute coronary syndrome: Potassium, magnesium and cardiac arrhythmia Kardiologia Polska 2003 59(11):402-07.  [Google Scholar]

[8]Munir TA, Afzal MN, Baseline leukocyte count and acute coronary syndrome: Predictor of adverse cardiac events, long and short term mortality and association with traditional risk factors, cardiac biomarkers and C-reactive protein Journal of Ayub Medical College, Abbottabad: JAMC 2008 21(3):46-50.  [Google Scholar]

[9]Timóteo AT, Papoila AL, Lousinha A, Alves M, Miranda F, Ferreira ML, Predictive impact on medium term mortality of haematological parameters in acute coronary syndromes: Added value on top of GRACE risk score Eur Heart J Acute Cardiovasc Care 2015 4(2):172-79.  [Google Scholar]

[10]Acute Coronary Syndrome [Internet]. Heart.org. 2017 [cited 11 February 2017]. Available from: http://www.heart.org/HEARTORG/Conditions/HeartAttack/AboutHeartAttacks/Acute-Coronary-Syndrome_UCM_428752_Article.jsp#.WJ-IYzt97IU  [Google Scholar]

[11]Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study The Lancet 2004 364(9438):937-52.  [Google Scholar]

[12]Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, Major risk factors as antecedents of fatal and nonfatal coronary heart disease events JAMA 2003 290(7):891-97.  [Google Scholar]

[13]Canto JG, Kiefe CI, Rogers WJ, Peterson ED, Frederick PD, French WJ, Number of coronary heart disease risk factors and mortality in patients with first myocardial infarction Jama 2011 306(19):2120-27.  [Google Scholar]

[14]Saleheen D, Frossard P, CAD risk factors and acute myocardial infarction in Pakistan Acta Cardiol 2004 59(4):417-24.  [Google Scholar]

[15]Pyörälä K, Laakso M, Uusitupa M, Diabetes and atherosclerosis: An epidemiologic view. Diabetes/metabolism reviews Diabetes Metab Rev 1987 3(2):463-524.  [Google Scholar]

[16]Mansur AP, Ramires JA, Gonçalves EP, Avakian SD, Caramelli B, Martins JR, Risk factors, angiographic findings, and menopausal status in women with chronic stable coronary heart disease Cardiovascular Risk Factors 1996 6(5):284-88.  [Google Scholar]

[17]Fresco C, Maggioni AP, Signorini S, Merlini PA, Mocarelli P, Fabbri G, Variations in lipoprotein levels after myocardial infarction and unstable angina: The LATIN trial Italian heart journal: official journal of the Italian Federation of Cardiology 2002 3(10):587-92.  [Google Scholar]

[18]Assmann G, Schulte H, von Eckardstein A, Huang Y, High-density lipoprotein cholesterol as a predictor of coronary heart disease risk. The PROCAM experience and pathophysiological implications for reverse cholesterol transport Atherosclerosis 1996 124:S11-20.  [Google Scholar]

[19]Pintó X, Millán J, Muñoz A, Corbella E, Hernández-Mijares A, Zuñiga M, A very high prevalence of low HDL cholesterol in Spanish patients with acute coronary syndromes Clin Cardiol 2010 33(7):418-23.  [Google Scholar]

[20]Gregg EW, Cheng YJ, Cadwell BL, Imperatore G, Williams DE, Flegal KM, Secular trends in cardiovascular disease risk factors according to body mass index in US adults JAMA 2005 293(15):1868-74.  [Google Scholar]

[21]Pais P, Pogue J, Gerstein H, Zachariah E, Savitha D, Jayprakash S, Risk factors for acute myocardial infarction in Indians: A case-control study The Lancet 1996 348(9024):358-63.  [Google Scholar]

[22]Goel PK, Bharti BB, Pandey CM, Singh U, Tewari S, Kapoor A, A tertiary care hospital based study of conventional risk factors including lipid profile in proven coronary artery disease Indian Heart J 2002 55(3):234-40.  [Google Scholar]

[23]Naqvil SM, Rao TR, Chandra SJ, Haemoglobin levels in acute coronary syndrome patients admitted in cardiology intensive care units in a tertiary care hospital The Journal of the Association of Physicians of India 2015 63(6):26-29.  [Google Scholar]

[24]Mahlknecht U, Kaiser S, Age-related changes in peripheral blood counts in humans Experimental and Therapeutic Medicine 2010 1(6):1019-25.  [Google Scholar]

[25]Hayflick L, The limited in vitro lifetime of human diploid cell strains Exp Cell Res 1965 37(3):614-36.  [Google Scholar]

[26]Lipschitz DA, Udupa KB, Milton KY, Thompson CO, Effect of age on hematopoiesis in man Blood 1984 63(3):502-09.  [Google Scholar]

[27]Ferreira M, António N, Gonçalves F, Monteiro P, Gonçalves L, Freitas M, Hemoglobin: Simply a laboratory value or a powerful predictor of risk in patients with acute coronary syndrome? Rev Port Cardiol (English Edition) 2012 31(2):121-31.  [Google Scholar]

[28]Sulaiman K, Al-Zakwani I, Panduranga P, Al-Suwaidi J, Alsheikh-Ali AA, Mahmeed WA, Relationship between white blood cell count and in-hospital outcomes in acute coronary syndrome patients from the Middle East Angiology 2012 63(1):24-29.  [Google Scholar]

[29]Huang G, Zhong XN, Zhong B, Chen YQ, Liu ZZ, Su L, Significance of white blood cell count and its subtypes in patients with acute coronary syndrome Eur J Clin Invest 2009 39(5):348-58.  [Google Scholar]

[30]Barron HV, Cannon CP, Murphy SA, Braunwald E, Gibson CM, Association between white blood cell count, epicardial blood flow, myocardial perfusion, and clinical outcomes in the setting of acute myocardial infarction Circulation 2000 102(19):2329-34.  [Google Scholar]

[31]Grzybowski M, Welch RD, Parsons L, Ndumele CE, Chen E, Zalenski R, The association between white blood cell count and acute myocardial infarction in hospital mortality: Findings from the national registry of myocardial infarction Acad Emerg Med 2004 11(10):1049-60.  [Google Scholar]

[32]Lavi S, Prasad A, Yang EH, Mathew V, Simari RD, Rihal CS, Smoking is associated with epicardial coronary endothelial dysfunction and elevated white blood cell count in patients with chest pain and early coronary artery disease Circulation 2007 115(20):2621-27.  [Google Scholar]

[33]Peng Y, Huang FY, Liu W, Zhang C, Zhao ZG, Huang BT, Relation between admission serum potassium levels and long term mortality in acute coronary syndrome Internal and Emergency Medicine 2015 10(8):927-35.  [Google Scholar]

[34]Nabais , Rocha , Costa JO, Marques JO, Torres , Magalhães , Prognostic impact of moderate renal dysfunction in acute coronary syndromes Rev Port Cardiol 2008 Mar 27(3):303-12.discussion 315-7  [Google Scholar]

[35]James C, Risk factors for coronary artery diseases: A study among patients with ischemic heart disease in Kerala Heart India 2013 Jan 1 1(1):7  [Google Scholar]

[36]Khan MA, Hassan MU, Hafizullah M, Coronary Artery Disease, is it more frequently effecting younger age group and women? Pakistan Heart Journal 2012 Sep 5 39(1-2)  [Google Scholar]