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ORIGINAL ARTICLE

Acta Medica Indonesiana - The Indonesian Journal of Internal Medicine

Cardiometabolic Risk Factors and Acute Kidney Injury Based on Urinary Neutrophil Gelatinase Associated Lipocalin (NGALu) in Acute Coronary Syndrome Patients

Lazuardhi Dwipa, Rachmat Soelaeman, Rully M.A. Roesli, Erwan Martanto, IGN. AdhiartaDepartment of Internal Medicine, Padjadjaran University - Hasan Sadikin Hospital. Jl. Pasteur 38 Bandung 40161, Indonesia. Correspondence mail: riabandi81@yahoo.co.uk, lazuardhi.d@gmail.com

ABSTRAKTujuan: untuk menganalisis hubungan antara faktor-faktor kardiometabolik dengan gangguan ginjal akut

(GgGA) berdasarkan neutrophil gelatinase associated lipocalin urin (NGALu) pada penderita dengan sindroma koroner akut (SKA). Metode: studi potong lintang dilakukan pada pasien dengan SKA yang datang ke Unit Gawat Darurat Rumah Sakit Hasan Sadikin. Sampel urin diperoleh pada saat kedatangan untuk menentukan GgGA secara dini dengan metode ELISA menggunakan NGAL dan dianggap suatu GgGA apabila ≥150 ng/ml. Faktor-faktor kardiometabolik sesuai dengan kriteria MetS oleh IDF tahun 2006. Hasil: terdapat total 60 subjek terdiri dari 39 laki-laki (65%) dan 21 perempuan (35%) usia rata-rata 58,47 (SD 9,9) tahun. Tiga puluh subjek (50%) termasuk GgGA berdasarkan pemeriksaan NGAL urin. Terdapat dua faktor risiko yang berhubungan bermakna dengan GgGA, yaitu tekanan darah (hipertensi) dan HDL (p ≤0,05). HDL merupakan faktor kardiometabolik paling signifikan (p=0,037; OR 5,137 (95% CI 1,102-23,95)). Jumlah faktor yang terdapat pada seseorang juga berhubungan dengan kejadian GgGA, semakin banyak faktor risiko terdapat pada seseorang semakin besar kemungkinan kejadian GgGA (p=0,03). Kesimpulan: faktor tekanan darah dan HDL berhubungan dengan kejadian GgGA pada penderita SKA. Semakin banyak faktor kardiometabolik terdapat pada seorang dengan SKA maka semakin besar kemungkinan kejadian GgGA.

Kata kunci: faktor kardiometabolik, sindroma metabolik, sindroma koroner akut, gangguan ginjal akut, NGAL.

ABSTRACTAim: to analyze the association between cardiometabolic risk factors and acute kidney injury (AKI) based

on urinary neutrophil gelatinase associated lipocalin (NGALu) in patients with acute coronary syndrome (ACS). Methods: a cross-sectional study was conducted on the ACS patients who were admitted to the Emergency Room in Hasan Sadikin Hospital. Urinary samples were obtained at the time of the arrival and considered AKI if the urinary NGAL level ≥150 ng/ml. The cardiometabolic risk factors were in accord with the IDF criteria for MetS. Results: there were 60 subjects that consisted of 39 men (65%) and 21 women (35%) and the average of was 58.47 (SD 9.9) years. There were 30 subjects (50%) considered AKI based on NGAL level. There were two significant CMR risk factors associated with AKI; blood pressure (hypertension) and HDL (p ≤0.05). HDL being the most significant cardiometabolic factor (p=0.037; OR 5.137 (95% CI 1.102-23.95)). The number of factors was also associated with the incidence of AKI; the more factors existed in a person the greater the incidence of AKI (p=0.03). Conclusion: blood pressure and HDL were cardiometabolic risk factors associated with AKI in ACS patients. The more cardiometabolic factors existed in a person the greater the incidence of AKI.

Key words: cardiometabolic risk factors, metabolic syndrome, acute coronary syndrome, acute kidney injury, NGAL.

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INTRODUCTIONCardiometabolic Risk (CMR) factors are

currently recognized as an early identification of cardiovascular disease and metabolic risk factors. These factors tend to cluster together in one individu and some experts identify it as Cardiometabolic Risk (CMR) while for others is metabolic syndrome (MetS). These factors consist of abdominal/central obesity, insulin resistance (elevated fasting blood glucose or diabetes mellitus type 2), atherogenic dyslipidemia (decreased levels of/HDL cholesterol, elevated levels of triglycerides) and an increased blood pressure.1 The incidence range from 26% to 46% in Acute Coronary Syndrome (ACS) patients and associated with increased morbidity and mortality.1-3 Previous studies showed the incidence of Acute Kidney Injury (AKI) ranged from 10% to 25% in Acute Myocardial Infarction (AMI) patients.4-6 AKI was associated with more than two-fold increased risk of death in hospitals, when severe enough in which kidney replacement is needed if the mortality rate might increase up to 60%.7-8 AKI is also known as an independent risk factor in ACS patients for adverse outcome of the disease and all cause mortality rate in both short and long term. This could happen even in mild increase in creatinine serum and the higher the degree of the impairment of kidney function, the higher the incidence of morbidity and mortality.8-18

Previous s tudies showed that each cardiometabolic risk factors are also involved in deterioration of kidney function and are independent risk factors for Chronic Kidney Disease (CKD).19 Lately there are several studies that also studied the association between the cluster of cardiometabolic risk factors based on the criteria of MetS with incidence of AKI in patients with Acute Myocardial Infarction (AMI) which indicated that AKI incidence in MetS patients had higher risk than those without MetS. Other studies showed similar result in patients with three vessel diseases undergoing by-pass surgery.20-22

Nonetheless there has not been any study that examines the association between each individual cardiometabolic risk factors based on the MetS criteria with AKI, especially in patients with ACS. This is in fact an important issue for further investigation since there are still differences of opinions among experts about this

phenomenon of the clustering cardiometabolic risk factors in one individual whether to classify it as a syndrome or not. Unlike the International Diabetes Foundation (IDF), National Heart, Lung, and Blood Institute (NHLBI) and National Cholesterol Education Program (NCEP), which regard it as a syndrome, the American Diabetes Association (ADA) stated that despite the tendency of cardiometabolic risk factors to be clustered in one individual, one cannot classify it as a syndrome since the basic pathogenesis that may explain each cardiometabolic risk factor as one syndrome is still unclear. Another reason is that currently there has been no single therapy that can address all cardiometabolic risk factors simultaneously but instead the approach is still adressing to each risk factor respectively.1,23

Acute Kidney Injury (AKI) on the other hand, which is based on the AKIN or ADQI criteria have several limitations. The criteria are based on the observation of the increase in creatinine serum and the decrease of urinary output, while in fact, the creatinine serum levels cannot be used in certain conditions such as in acute setting because of the late increase in creatinine serum level (it may take up to two or three days) compared with the actual state of injury that has already occurred in the kidney. Moreover, creatinine serum levels are influenced by various factors of renal and non-renal.5,25 While the observation on urinary output often cannot be used in various clinical conditions such as dehydration, urinary tract obstruction, and the use of diuretics. Meanwhile, especially in ACS patients complicated with acute lung edema setting requires diuretics in its management. Thus, according to the ADQI suggestions a biological marker is needed for the diagnosis of AKI capable of early detecting with a fine sensitivity and specificity.24 Neutrophil Gelatinase Associated Lipocalin (NGAL) is considered as one of the most promising AKI novel biomarkers. Previous studies showed that NGAL is a biological marker which is more a sensitive biological marker AKI compared with other markers.5 In addition, there are other things that can influence the events of AKI in ACS patients. Various kinds of interventions and therapies of ACS such as a primary PCI treatment (Contrast-induced Nephropathy) and drugs (ACE-i, NSAIDs, heparin, furosemide, etc.) may also have a role in the development of AKI. These various therapies may confuse clinicians

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whether AKI is caused primarily by ACS or other causes.27-30 NGAL can be a solution to the above mentioned problems because AKI can be detected upon initial arrival in the Emergency Department (ED) before treatment or interventions are given.

Therefore, it is necessary to conduct a study to analyze the association of cardiometabolic risk (CMR) factors with the incidence of Acute Kidney Injury, particularly in ACS patients and utilizing a new method with a new biological marker known as NGAL as an alternative method to help recognize AKI in its early stage.

METHODSThis is a cross sectional study conducted at

the Emergency Department and Cardiac Intensive Care Unit, Department of Internal Medicine, Faculty of Medicine, University of Padjadjaran, Hasan Sadikin Hospital. The accessible population was those with Acute Coronary Syndrome (ACS) admitted to the Emergency Unit of Hasan Sadikin Hospital (RSHS) Bandung and who were willing to participate in the study. Those with sepsis, history of malignancy, anuria, history of chronic heart failure (CHF), history of chronic kidney disease (CKD) or initial creatinine ≥4 mg/dl were excluded from the study. Data collected included characterics such as sex, age, type of ACS, and the clinical presentation based on Killip classification, prior medications, level of urinary NGAL (NGALu) to determine AKI (NGALu ≥150 ng/ml), history of treatment of hypertension, triglyceride, HDL and diabetes mellitus, as well as data based on the cardiometabolic factors from IDF 2006 which consist of waist circumference, level of blood pressure, fasting blood glucose, HDL, and triglyceride. Sampling was based on the consecutive sampling method until the sample size was reached. Data analysis was done by Chi-square test and multivariate analysis was performed by logistic regression technique to control some identified confounding factors. All data were processed and statistical analyses were done with SPSS 13.0 for Windows. Ethical clearance from the ethical committee for Medical Research in the Faculty of Medicine, University of Padjadjaran was obtained prior to the study, and all subjects signed informed consents.

RESULTSOur study recruited a total of 60 subjects

to be analyzed. Most are male 39 (65%) while women were 21 subjects (35%). The average of age 58.47 years-old, with the youngest was 32 and the oldest was 78 years old. Most (35%) are in the range of 50-59 year old. The table showed that the majority was STEMI patients; 37 subjects (61.7%) and followed by NSTEMI and UAP, 17 (28.3%) and 6 (10%), respectively. Most of the subjects admitted with the clinical presentation degree of Killip I; 34 subjects (56.7%), followed by the degree of Killip II, IV, and III; 17 men (28.3%), five subjects (8.3%), and four subjects (6.7%), respectively. Research subjects with AKI were 30 subjects (50%). There were more subjects without MetS which were 43 subjects (71.7%) compared to subjects with MetS according to the criteria of the IDF 2006.

Incidence of AKI increases according to age (p=0.017), the older the subject, the higher the events. AKI was found significantly more in women 17 subjects (81.0%) than in men whereas in women compared with men (3 subjects (33.3%)) p value <0.001. It showed that the higher killip degree, the higher the risk of developing AKI (p=0.019). Prior medication was given at least 48 hours before admission (ACE-i, Furosemide, NSAIDs) were found in 27 subjects (54%) with AKI and 23 subjects without AKI (46 %) based on the statistical analysis, there were no significant differences (p=0.166).

Based on Table 1, blood pressure and low level HDL are significantly associated with the incidence of AKI. Incidence of AKI was more prevalent in subjects with increased blood pressure, 21 men (63.6%) compared with normal blood pressure subjects or haveing no history of hypertension; 9 (33.3%) and was statistically significant (p=0.020). Decreased HDL were also associated with AKI.

Based on the data, variables having value less than p ≤0.25 were female, age, Killip degree, waist circumference, blood pressure and HDL. These variables were subsequently analyzed by multivariate analysis using multiple logistic regression analysis with the results shown in Table 2.

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After going through multiple logistic regression analysis, significant factors were HDL and hypertension. Subjects with low HDL have five times higher risk of developing AKI compared with subjects with normal HDL. Subjects with hypertension were three times having more risky of developing AKI than those without. Female gender has 16.7 times risk of developing AKI compared with male. Older subjects were also having more risk of developing AKI. There was a significant association between the number of cardiometabolic risk factors existed in a person with the incidence of AKI with the value of Mann Whitney Z = 1.872 and p = 0.032, the more cardiometabolic risk factors existed in a person, the greater the incidence of AKI.

DISCUSSION Metabolic Syndrome (MetS) was found in 17

subjects (28.3%) and these result were similar to previous studies performed by Zeller et al., Pandey

et al and Takeno et al., where the incidence were ranging from 26 to 46%.33-35 MetS are statistically more significant in female compared with male (p≤0.001). Something similar was found in the study by Miftahurrachman (2008) conducted in Bandung, where MetS were found more in women than in men 46% vs. 39%, respectively, although this difference was statistically less significant.36 Based on previous studies on ethnic, such as Hispanic and African race, MetS were more prevalent in the female 4% vs. 25.1% in male.35 It is also similar to the study by Termizy et al. in Malaysia (2009), where female were more prevalent than male; 43.7% vs. 32.23% respectively.37

The incidence of AKI were found in 30 subjects (50%), it was much higher than the previous studies reported by Roesli et al and Parikh et al (2008) that ranged from 10% to 25%.7-8 This might be due to the higher sensitivity of NGALu to detect AKI in its early development

Table 1. Relationship between cardiometabolic risk factors with incidence of AKI

VariablesAKI

P value Odds ratio (95% CI)yes no

Waist Circumference

- Obesity 15 (62,5%) 41,7%) 0,114 1,67 (0,87-3,20)

- Normal 9 (37,5%) 21 (58,3%) 1,0

Blood Pressure

- Increase 21 (63,6%) 12 (36,4%) 0,020 1,91 (1,06-3,45)

- Normal 9 (33,3%) 18 (66,7%) 1,0

FBG

- Increase 24 (57,1%) 18 (42,9%) 0,091 1,71 (0,85-3,47)

- Normal 6 (33,3%) 12 (66,7%) 1,0

Triglyceride

- Increase 12 (60%) 8 (40%) 0,273 1,33 (0,81-2,19)

- Normal 18 (45%) 22 (55%) 1,0

HDL

- Decrease 25 (61,0%) 16 (39%) 0,012 2,32 (1,05-5,11)

- Normal 5 (26,3%) 14 (73,7%) 1,0

FBG= Fasting Blood Glucose, HDL=High Density Lipoprotein

Table 2. Multivariate analysis on the relationship between cardiometabolic risk factors with the incidence of AKI

Variables Coefficient B SE P value (two-tailed test) Odds ratio (95% CI)

Sex 2,821 0,888 0,001 16,7 (2,946-95,745)

Age 0,785 0,395 0,047 2,19 (1,011-4,757)

HDL 1,637 0,785 0,037 5,137 (1,102-23,95)

Hypertension 1,287 0,698 0,065 3,62 (0,921-14,222)

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since it was not influenced by a variety of renal nor non-renal factors. Other factors that could cause this marked increase of incidence might be the fact that this study had a broader coverage of patients while in previous studies were limited only subjects with STEMI (ST-elevation Myocardial Infarction) but not ACS as a whole with its varieties. Subjects with MetS have the risk as high as 3.3 times than those without MetS for AKI. These results were similar to the previous study conducted by Clavijo et al. Thus it is confirmed that the people with MetS are in increased risk of developing AKI.4

The results also showed that the greater the degree of Killip classification, the greater the incidence of AKI. This is in accordance with the basic pathophysiology of AKI where this occurs mainly through hemodynamic disturbances due to cardiac contractility dysfunction in ACS patients.11,14,30,38-40

Bivariate analysis showed the association between each factor and the the incidence of AKI. Each risk factor brings a greater incidence of AKI, but factors which were statistically significant were blood pressure (hypertension) and HDL. Although only blood pressure and HDL that were statistically significant, it is interesting to note further that the total number of cardiometabolic risk factors existing in one person might have a significant role in AKI development in ACS patients. The more cardiometabolic risk factors existed in one person, the higher the risk of AKI. Although the exact mechanism was unknown to us why these factors could predispose to AKI, this study showed that the incidence of AKI especially in patients with ACS was more than merely due to the occurrence of cardiac contractility dysfunction resulting in hemodynamic disturbance alone but

perhaps there are other factors that could explain this result. One thing in common that all of these CMR factors share is that these factors are causing endothelial dysfunction which occurred at the cellular level effecting both heart and kidney. Endothelial dysfunction increases pro-inflammatory mediators and oxidative stress which in turn makes the dysfunction even worse and this could effect renal function by worsening renal hemodynamic through multiple mechanism including sodium retention, activation of sympathetic nervous system, decreased Na-K ATP-ase activity, and elevation of glomerular filtration fraction. Further injury to the kidney occurred as a result of hemodynamic disturbance from cardiac dysfunction and consequently causing the activation of Renin-Angiotensin-Aldosterone System (RAAS), the increase of inflammatory cells and inflammatory mediators. This complex interplay leads to a vicious cycle which is called ‘acute cardiorenal syndrome’ and further worsening of function of both at cellular and organic levels in heart and kidney. It is also possible that the more CMR factors involved in this complex process, the more profound the effect on both organs.11,20-23,30

Nonetheless, there were other CMR factors in this study that were not associated with the incidence of AKI. On the other hand, the study also showed that the more factors existed in a person, the greater the risk of developing AKI. The issue whether MetS is a syndrome/disease entity is real or merely a collection of risk factors for cardiovascular disease and diabetes is still a matter of debate primarily due to the absence of an apparent linking factor that could explain it as a syndrome. So far, insulin resistance is thought to be the linking factor but the basic pathological

Table 3. Correlation between number of risk factors with the incidence of AKI

Total of cardiometabolic risk

factors

AKIZ (mw); p value Odds ratio (95%CI)

yes (n=30) no (n=30)

0 1 (20%) 4 (80%) 1

1 3 (33,3%) 6 (66,7%) 1,67 (0,23-12,09)

2 7 (50%) 7 (50%) 1,872 ; p=0,032 2,50 (0,4-15,58)

3 9 (56,3%) 7 (43,8%) 2,81 (0,46-17,11)

4 6 (60%) 4 (40%) 3,0 (0,48-18,60)

5 4 (66,7%) 2 (33,3%) 3,33 (0,53-21,03)

AKI = Acute Kidney Injury

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theory is still unclear and there are still dilemmatic problems that can not be answered only by insulin resistance. In fact, this study showed that fasting blood glucose as an early sign of insulin resistance did not show a significant association with AKI. This result could further emphasize that insulin resistance may not be a primary factor in this subset of patients and there might be other possible pathomechanisms that have an important role and further research is required to investigate this issue. Nonetheless, this study also show us that each factors might have various degree effect on the kidney that each factor has a cumulative effect on AKI and we should pay attention to each factor more closely, especially if they are clustered together, whether it is classified a metabolic syndrome or not.40

CONCLUSIONHypertension and HDL were significantly

associated with the incidence of AKI in ACS patients. Other factors such as fasting blood glucose, triglyceride, and waist circumference were not significantly asscoiated, but this does not necessarily eliminate the effect on each these factors. This is showed by the total number of cardiometabolic factors existing in a person, significantly associated with the incidence of AKI, the more the cardiometabolic factors exist, the higher the risk of AKI occurence in ACS patients. This means that although individually the CMR factors were not significantly associated with AKI, they have cumulative effect on the incidence of AKI whether it is classified as a syndrome or not.

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