Association of Creatinine Clearance Rate and Coronary Angiographic Severity in Patients with Coronary Artery Disease

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Association of Creatinine Clearance Rate and Coronary Angiographic Severity in Patients with Coronary Artery Disease


Cardiovascular diseases are presently the leading causes of death in industrialized countries. Among these, coronary artery disease (CAD) is the most prevalent manifestation. Atherosclerosis is the main pathology of CAD.

Renal function is a recognised independent predictor of survival in cardiovascular diseases. Cardiovascular disease may develope early in the course of renal dysfuction even when the serum creatinine level is within normal limit. Low muscle mass may be a risk factor for mortality in patient with established CAD. Glomerular filtration rate (GFR) rather than serum creatinine is ideal for determining kidney function. Creatinine clearance rate (CCr) is used as a correlate of GFR. CCr will be estimated by using Cockcroft-Gault formula.

Being a South Asian country Bangladesh has higher prevalence of CAD. In this study we will see the association of CCr and angiographic severity of CAD which will help a great deal in the management and preventive strategy of CAD in Bangladesh.

This will be a cross sectional study. By purposive technique sample will be collected after fullfilling inclusion and exclusion criteria. A formulated study procedure will be followed. CCr will be determined by Cockcroft – Gault formula and extent of angiographic severity of coronary artery will be assessed by vessel score and stenosis score .

A few number of studies have been done out side Bangladesh regarding association of creatinine clearance rate (CCr) and coronary angiographic severity in patients with coronary artery disease; but this type of study has not been done in our population. This study will intend to see the association of creatinine clearance rate and coronary angiographic severity in Bangladeshi coronary artery disease patients.


Cardiovascular diseases are presently the leading causes of death in industrialized countries and expected to become so in emerging countries by 2020.1 Among these, coronary artery disease (CAD) is the most prevalent manifestation and is associated with high mortality and morbidity. Atherosclerotic coronary heart disease (CHD) remains the leading cause of death in the developed world.2 Various studies have pointed out that South Asians have a higher prevalence of CAD as compared with other ethnicities, with a higher rate at younger ages.3,4 Being a south Asian country Bangladesh is not immune from this higher prevalence of CAD. Atherosclerosis is the main pathology behind CAD and non-invasive methods for the prediction of the severity of atherosclerotic lesions have become an important objective for early treatment as well as primary preventive measures.

Renal function, as measured by serum creatinine, blood urea nitrogen, or estimated creatinine clearance, has been shown in epidemiological studies and clinical trials to be an independent predictor of survival.5–9 However, the prognostic significance of mild to moderate renal dysfunction in patients with acute coronary syndromes (ACS) without ST segment elevation is unknown. Mild renal impairment is associated with an increased risk of coronary artery disease and stroke, suggesting that cardiovascular disease may develop early in the course of renal dysfunction.10 Increased serum creatinine concentrations may reflect generalized vascular disease denoting early nephrovasculopathy in association with established atherosclerotic risk factors.9,11,12

Although obesity is a risk factor for incident coronary artery disease (CAD), its significance in individuals with established CAD has recently been questioned. In a meta-analysis that included 40 studies and >250 000 individuals with CAD, there was a reverse J-shaped relationship between body mass index (BMI) and mortality: Individuals with a BMI <20.0 kg/m2 had the greatest mortality risk, whereas obese (BMI, 30.0 to 34.9 kg/m2) or severely obese (BMI >35 kg/m2) individuals were not at greater risk than normal-weight individuals (BMI, 20.0 to 24.9 kg/m2).13 Because BMI does not discriminate between its relative contributions from adiposity or muscle, this finding has lead many to hypothesize that the high death risk associated with low BMI may be due to deficiency in muscle rather than adiposity.14–16 Implicit is the hypothesis that low muscle mass may be a risk factor for mortality in persons with established CAD. Yet, to the best of our knowledge, this association has not been studied in the setting of prevalent CAD .

It is estimated that >98% of creatinine comes from muscle,17 where it is produced and secreted into serum at a continuous rate.18 Once in serum, creatinine is almost exclusively excreted in the urine in individuals without severe kidney failure.19,20 Because muscle mass does not change rapidly within individuals, elevations in serum creatinine typically reflect decrements in glomerular filtration rate (GFR). When the serum creatinine concentration is in steady state, however, regardless of its serum concentration, creatinine generation must equal creatinine excretion. Thus, the urinary creatinine excretion rate (CER) has been recognized

as a marker of muscle mass for nearly a century.21

Serum creatinine is commonly used to estimate creatinine clearance but is a poor predictor of glomerular filtration rate. Glomerular filtration rate is the ideal for determining kidney function but it is difficult to measure. For practical purposes, estimated creatinine clearance is used as a correlate of glomerular filtration rate and is commonly estimated by using the Cockcroft-Gault formula without the need for 24 hour urine collection.22–24 Other formulas have been developed to estimate creatinine clearance rates in specific populations but these equations are more

Complex and may be limited in their application.25

Estimated creatinine clearance rate (eCCr) using Cockcroft-Gault formula

A commonly used surrogate marker for estimate of creatinine clearance is the Cockcroft-Gault formula, which in turn estimates GFR in mL/min.26 It is named after the scientists who first published the formula, and it employs serum creatinine measurements and a patient’s weight to predict the creatinine clearance.27,28 The formula, as originally published, is:

This formula expects weight to be measured in kilograms and creatinine to be measured in mg/dL, as is standard in the USA. The resulting value is multiplied by a constant of 0.85 if the patient is female. This formula is useful because the calculations are simple and can often be performed without the aid of a calculator.

When serum creatinine is measured in µmol/L:

Where Constant is 1.23 for men and 1.04 for women.

One interesting feature of the Cockcroft and Gault equation is that it shows how dependent the estimation of CCr is based on age. The age term is (140 – age). This means that a 20-year-old person (140-20 = 120) will have twice the creatinine clearance as an 80-year-old (140-80 = 60) for the same level of serum creatinine (120 is twice as great as 60). The C-G equation also shows that a woman will have a 15% lower creatinine clearance than a man at the same level of serum creatinine.

A substantial number of patients get admitted to the cardiology department of Dhaka Medical College Hospital with the diagnosis of CAD and many of them undergo coronary angiogram (CAG). The aim of this study is to evaluate the association between creatinine clearance rate (CCr) and the extent of CAD by coronary angiogram in our setting.


Creatinine clearance rate (CCr) is inversely related with the angiographic severity of coronary artery disease (CAD).



To see the association between creatinine clearance rate (CCr) and coronary angiographic severity in patients with coronary artery disease (CAD).


1) To measure the level of serum creatinine.

2) To calculate the creatinine clearance rate (CCr).

3) To assess the severityof coronary artery disease by angiography.

4) To find out the association between Coronary Angiographic Severity with creatinine clearance rate (CCr).


Most of the prior studies that examined the relationship between renal function and cardiovascular outcomes relied on serum creatinine, an unreliable proxy of renal function.29 Indeed, a significant proportion of patients with serum creatinine levels slightly above the upper limit of the normal range or even within the normal range have impaired renal function, often even significant renal dysfunction.29

More recently, renal function has been assessed using equations estimating the glomerular filtration rate (GFR).29 Several studies have clearly demonstrated that reduced values of glomerular filtration rate that are even within the mildly impaired or normal range are associated with worse cardiovascular outcomes among a wide spectrum of patients with established cardiovascular conditions, including asymptomatic and symptomatic heart failure, 30 acute myocardial

Infarction etc.31

Renal function is mostly estimated by a standard method, using serum creatinine level. However, this is not a sensitive marker, because of its dependency on other parameters like muscle mass, age, gender, race, and metabolism. 32,33

Various studies have pointed out that South Asians have a higher prevalence of CAD as compared with other ethnicities, with a higher rate at younger ages. 34, 35 being a south Asian country Bangladesh is not immune from this higher prevalence of CAD.

In this study we will see the association of CCr and coronary angiographic severity in CAD. A few number of studies have been done out side Bangladesh regarding association of creatinine clearance rate (CCr) and coronary angiographic severity in patients with coronary artery disease; but this type of study has not been done in our population. This study will intend to see the association of creatinine clearance rate and coronary angiographic severity in Bangladeshi coronary artery disease patients. This information will help a great deal in the management and preventive strategy of CAD in Bangladesh.


Study Design

Type of study : Cross sectional study

Place of study : Department of cardiology

Dhaka Medical College Hospital, Dhaka.

Period of study : April, 2011 to March, 2012

Study population : All the patients with CAD admitted in the department of cardiology, Dhaka Medical College Hospital, Dhaka within the study period.

Sampling population : All the patients with CAD, undergoing serum creatinine estimation and coronary angiogram (CAG) in the department of cardiology, Dhaka Medical College Hospital, Dhaka after fulfilling the inclusion and exclusion criteria.

Study population and sampling

Selection criteria:

Inclusion criteria

Allthe patients with CAD, admitted in the Department of Cardiology, DMCHwithin the study period, who will undergo CAG and whose CCr will be estimated.

Exclusion criteria

1. Patients having previous history of PCI or CABG

2. Patients unfit for CAG

3. Patient with serious co-morbid condition such as ESRD, hepatic dysfunction, malignancy, systemic infection etc.

4. Unwilling to give consent.

Sampling technique:

Purposive sampling

Sample size:

As the sampling population is confined within patients with CAD admitted for CAG in the Department of Cardiology, DMCH, the sample size calculation will be that for sample size calculation in case of cross sectional study.

i. e. n = NpqZ2 / d2 (n—1) + Z2 pq

Where, N = Number of patients with IHD, underwent CAG in the Department of Cardiology, DMCH from April, 201o to March, 2011= 170

P = 0.5, as no previous study at DMCH found to show the correlation. So p is assumed to be 50%

q = 1—p = 1— 0.5 = 0.5

d = 10% 0f p = 0.05

Z = 1.96,standard deviation with 95% CI

So, n = N (0.5 × 0.5) (1.96)2 / (0.05)2 (N—1) + (1.96)2 (0.5×0.5)

=170×0.25×3.84 / 0.0025× 169 + 0.96

=163.26 / 1.3825 = 118

Sample size = 118.

Study procedure:

· Patients with CAD admitted in the Department of Cardiology, DMCH will be selected.

  • By inclusion and exclusion criteria, patients undergoing CAG will be selected for the study.
  • Informed consent will be taken from each patient or from legal guardian.
  • Patient’s name and particulars will be recorded in the case record file.
  • Initial evaluation of the patients by history and clinical examination will be performed and recorded in the preformed data collection sheet.
  • Demographic profile and Pulse, BP, height, weight, BMI will be measured.
  • Risk factors of CAD like hypertension, diabetes mellitus, smoking, dyslipidaemia, obesity and family history of premature CAD will be noted. Drug history will be taken regarding anti hypertensive, anti diabetic and lipid lowering drugs.
  • Baseline laboratory investigation e.g. serum electrolytes, blood sugar, lipid profile,ECG, Echocardiography will be done for each patient.
  • Serum creatinine will be done before CAG.
  • By Cockcroft-Gault formula, CCr will be estimated and categorized as normal or mild renal dysfunction (CCr>60 ml/min.), moderate renal dysfunction (30-60 ml/min.) and severe renal dysfunction (<30 ml/min.)

· Coronary angiogram will be done in all patients who will fulfill the criteria.

  • Interpretations of coronary angiogram will be reviewed by at least two cardiologists.

· Angiographic severity of coronary artery disease will be assessed by:

1. Vessel score: This is the number of vessels with a significant stenosis. For left main coronary artery 50% or greater and for others 70% or greater reduction in luminal diameter 36. Score ranges from 0 to 3, depending on the number of vessel involve. Left main artery will be scored as single vessel disease 37.

2. Stenosis score: For stenosis score a modified Gensini score will be used. The reduction in the lumen diameter and the roentgenographic appearance of concentric lesions and eccentric plaques were evaluated (reductions of 25%, 50%, 75%, 90%, 99%, and complete occlusion are given Gensini scores of 1, 2, 4, 8, 16, and 32, respectively). Each principal vascular segment was assigned a multiplier in accordance with the functional significance of the myocardial area supplied by that segment: the left main coronary artery, ×5; the proximal segment of left anterior descending coronary artery (LAD), ×2.5; the proximal segment of the circumflex artery, ×2.5; the mid-segment of the LAD, ×1.5; the right coronary artery, the distal segment of the LAD, the posterolateral artery and the obtuse marginal artery, ×1; and others, ×0.5. This score therefore, places emphasis on the severity of stenosis, while including some of the extent of CAD38.

  • All the information will be properly noted in the preformed data sheet.

Data analysis:

Data will be analyzed by using SPSS(Statistical Package for the Social Science) version 11.5.Test statistics to be used to analyze the data are descriptive statistics, Chi square and unpaired t- Test. Level of significance will be set at 0.05.

Ethical implication:

Prior to commencement of this study the respective authority will approve the research protocol. All the patients included in this study will be informed about the nature, risk and benefit about the study. Proper permission will be taken from the department and institution concerned for this study.

Observation and results: Result of this study will be presented by different tables, graphs, charts, diagrams etc.


Discussion will be made after the result obtained in the study.

Summary and Conclusion:

At the end of the study summary and conclusion of the whole study will be presented.


n Demographic variables

· Age

· Sex

n Other variables

· Smoking

· Hypertension

· Diabetes mellitus

· Family history of premature CAD

· Dyslipidemia

· . Weight

· Height

· Serum creatinine

· Creatinine clearance rate (CCr)

· Serum lipid profile (Fasting)

· Random blood sugar


· Echocardiography

· Coronary angiogram

· Coronary angiographic severity score

Coronary angiographic profile

a. Vessel Score

b. Stenosis Score

Study Flow Chart

Working definitions:

Spectrum of CAD –

Acute myocardial infarction39: Either of the following criteria satisfies the diagnosis for acute, evolving or recent myocardial infarction:

1. Typical rise and / or fall of biochemical markers of myocardial necrosis with at least one of the following:

a) Ischemic symptoms

b) Development of pathological Q wave in the ECG

c) ECG changes indicative of ischemia (ST segment elevation or depression)

d) Imaging evidence of new loss of viable myocardium or new regional wall motion abnormality.

2. Pathological findings of an acute myocardial infarction.

Unstable Angina 40

Unstable angina is defined as angina pectoris (or equivalent type of ischemic discomfort) with at least one of three features:

1. Occurring at rest (or minimal exertion) and usually lasting >20 minutes (if not interrupted by nitroglycerin administration)

2. Being severe and described as frank pain, and of new onset (i.e., within 1 month) and

3. Occurring with a crescendo pattern (i.e., more severe, prolonged, or frequent than previously)

NSTEMI: It is defined as an acute coronary event in which there is cardiac marker evidence of myocardial necrosis (e.g. positive CK-MB or Troponin) without new ST segment elevation.

STEMI: It is defined as an acute coronary event in which there is cardiac marker evidence of myocardial necrosis and new (or presumably new if no prior ECG is available) ST segment elevation on the admission ECG.

Stable Angina:

Angina without a change in frequency or pattern over preceding 60 days. Angina is controlled by rest and / or sublingual / oral / transcutaneous medication.

n Acute Coronary Syndrome41

Acute coronary syndrome (ACS) is an emergency situation requiring immediate diagnosis and treatment. Unstable angina (UA), non-ST segment elevation myocardial infarction (NSTEMI) and ST segment elevation myocardial infarction (STEMI) collectively constitute the diagnosis of ACS.

n Dyslipidemia42

Total cholesterol ³ 200mg/dl

TG ³ 150mg/dl

LDL-C ³ 100 mg/dl

HDL-C < 40 mg/dl for male and < 50 mg/dl for female

n Diabetes Mellitus43

a. Symptoms of diabetes plus causal plasma glucose concentration ? 200 mg/dl (11.1 mmol/L) or

b. FPG ? 126 mg/dl (7.0 mmol/L) or

c. 2 hour post load glucose ? 200 mg/dl (11.1 mmol/L) during OGTT or

d. Patient under treatment for diabetes.

n Hypertension44

BP ³ 140/90 mmHg or patient on antihypertensive drug treatment.

n Overweight and obesity45

The National Institute of Health; National Heart, Lung, and Blood Institute report entitled “ clinical guideline on the identification, evaluation, and treatment of overweight and obesity” provides clear, scientifically based definition of overweight and obesity.

Classification of overweight and obesity

Class BMI (Kg/m2)

Healthy weight 18.5 – 24.9

Overweight 25 – 29.9


· Class I 30 – 34.9

· Class II 35 – 39.9

· Class III (Extreme obesity) ? 40

n Family History of CAD42

CAD in male first degree relative < 55 years; CAD in female first degree relative < 65 years.

n Smoking46

According to NCEP: ATP-III, the designation “smoker” means any cigarette smoking or chewing tobacco any amount in the past month.

List of abbreviation:

ACS Acute coronary syndrome

AMI Acute myocardial infarction

ATP IIIAdult Treatment Panel III

BMI Body mass index

CABG Coronary artery bypass graft

CAD Coronary artery disease

CAG Coronary Angiogram

CCr Creatinine clearance rate

CCU Coronary care unit

CER Creatinine excreation rate

C-G Cockcroft-Gault

CI Confidence interval

DM Diabetes mellitus

DMCH Dhaka medical college hospital

ECG Electrocardiogram

ESRD End stage renal disease

FPG Fasting plasma glucose

GFR Glumerular filtration rate

HDL High density lipoprotein

IHD Ischemic Heart Disease

LDL Low Density Lipoprotein

NSTEMI Non ST elevation myocardial infarction

NCEP National Cholesterol Education Programme

RBS Random blood sugar

STEMI ST elevation myocardial infarction

TG Triglyceride

UA Unstable angina

WHO World Health Organization

PCI Percutaneous coronary intervention


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