Article, Cardiology

Acute kidney injury risk in patients with ST-segment elevation myocardial infarction at presentation to the ED

Unlabelled imageAmerican Journal of Emergency Medicine (2012) 30, 1921-1927

Original Contribution

Acute kidney injury risk in patients with ST-segment elevation myocardial infarction at presentation to the ED

Rafaela Elizabeth Bayas Queiroz a, Leilane Siqueira Nobre de Oliveira b,

Claudio Alves de Albuquerque b, Caroline de Alencar Santana b, Patricia Maia Brasil b,

Luzia Layla Rodrigues Carneiro b, Alexandre Braga Liborioc,?

aFellowship of Emergency Medicine from Escolade Saude Publica do Ceara, Brazil

bMedical CourseUNIFOR, Fortaleza, Ceara, Brazil

cPost-Graduate Program in Public HealthUNIFOR, Fortaleza, Ceara, Brazil

Received 16 February 2012; revised 5 April 2012; accepted 5 April 2012


Introduction: Acute kidney injury is common in acute myocardial infarction (AMI) patients and has serious prognostic implications. The early identification of patients at risk of developing AKI at the emergency department (ED) can reduce its incidence.

Methods: Patients with ST-segment elevation myocardial infarction at the ED were included. Associated factors playing a role at ED presentation and during hospitalization were collected, and independent risk factors of developing AKI were assessed.

Results: Mean age among patients (n = 406, 69.7% male) was 62.5 +- 12.5 years. At ED admission, the mean glomerular filtration rate (GFR) was 70.5 +- 28.1 mL/min per 1.73 m2, and 140 (34.5%) patients had a GFR b 60 mL/min per 1.73 m2. Eighty-three patients (20.4%) developed AKI: 47 (11.6%) with stage 1, 26 (6.4%) with stage 2 and 10 (2.5%) with stage 3. Mortality was 11.8% and was higher in patients with AKI (34.9% vs 5.9%, P b .0001). Univariate analysis disclosed age, reduced GFR at presentation, severe Killip class, heart rate and longer door-to-needle time as risk factors to develop AKI. Moreover, these patients received less ?-blocker and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker in the ED. Multivariate analysis revealed that age, Killip class, heart rate, door-to-needle time, and ?-blocker non-use were independent factors associated with AKI. These factors provided the ED physician with good accuracy in identifying patients at high risk of developing AKI. Conclusion: Factors associated with AKI in STEMI patients allowed physicians to identify patients at high risk in the ED. Moreover, reduced door-to-needle time and ?-blocker use were associated with Renal protection in AMI patients.

(C) 2012


* Corresponding author. Tel.: +55 85 99987995; fax: + 55 85 99987995.

E-mail address: [email protected] (A.B. Liborio).

Acute kidney injury (AKI; previously known as acute renal failure) is a complication that affects hospitalized patients with various clinical conditions, with an estimated incidence of 5% [1]. In this setting, AKI is associated with

0735-6757/$ – see front matter (C) 2012

health-care costs, evolution to chronic kidney disease and long-term mortality at up to 10 years of follow-up [2].

In patients presenting acute myocardial infarction (AMI), the incidence of AKI ranges from 10% to 30% during the hospital stay [3-6]. When AMI is complicated by cardiogenic shock, AKI can affect more than 50% of the patients [7]. Recently, AKI in the setting of AMI has been associated with Short-term outcomes [5]. Moreover, AKI has long-term implications in AMI patients, being associated with chronic kidney Disease progression, recurrent AMI, heart failure progression, and long-term mortality [2,8].

Hospitalized patients with AMI are subjected to several procedures and complications related to AKI (Coronary artery bypass grafting [CABG], catheterization, heart failure, and drug nephrotoxicity) [7,9-11]. In each of these situations, AKI-associated risk factors have already been explored. Previous chronic kidney disease, diabetes mellitus, Volume depletion, hemodynamic instability, and low cardiac output are risk factors that are constantly present in such studies [12-14]. In an attempt evaluate risk factors in patients presenting AKI after AMI, a large retrospective study was performed [5]. However, owing to the retrospective nature of this study, emergency department (ED) data are scarce. Previous studies have also neglected clinical presentation, laboratory profile and procedures performed in the ED when evaluating the risk of developing AKI.

Owing to the poor prognosis of an AKI episode occurring during the setting of AMI, the early identification of patients at high risk by the ED physician is important for better management and care. This study intends to evaluate the AKI-associated risk factors, focusing on those assessed in the ED to develop a specific prognostic score for AKI following STEMI to be used by ED physicians.



This study was performed in a reference Hospital in Fortaleza, Brazil. This is a cardiopulmonary specialized hospital that serves an estimated population of 3 million people. Patients were selected from the ED from January 2010 to December 2011. All patients presenting a diagnosis of ST-segment-elevation myocardial infarction (STEMI) at presentation to the ED were included. Patients with chronic kidney disease undergoing maintenance dialysis therapy or who had had previous renal transplan- tation were excluded. Medical records were examined daily, including laboratory data and urine output. Data were collected by medical students who had undergone standardized training with 2 authors (REBQ and ABL). During the collection period, these authors reviewed data independently at least once weekly. Glomerular filtration

rate was calculated according to the MDRD equation with four variables [15]. Retrospective analysis was performed using this data set.

Dependent variable

We evaluated AKI throughout hospital stay. AKI was defined according to the Acute Kidney Injury Network (AKIN Group) [16]. Briefty, AKI was defined as an absolute difference of at least 0.3 mg/dL or a minimum increment of 50%, taking into consideration the peak and admission serum creatinine values during hospitalization. Moreover, AKI was classified into 3 stages based on an increase of 50% to 100% in terms of admission serum creatinine (stage 1); 100% to 200% (stage 2); or greater than 300% or an increment of 0.5 mg/dL, if admission serum creatinine was higher than 4 mg/ dL (Stage 3). Serum creatinine was measured using a Jaffe alkaline picrate assay (Abbott Aeroset analyzer). The Jaffe assay was calibrated to isotope diluted mass spectrometry- traceable creatinine values using the Roche enzymatic creatinine assay.

Independent variables

We included variables collected at the ED and during hospitalization. The following parameters were collected in the ED: age, sex, symptom time, Door-to-balloon time, previous history of diabetes mellitus, Arterial hypertension, dyslipidemia, previous drug usage, blood cell counts, biochemical profile, including venous blood gas, and drug administration. Furthermore, GRACE and TIMI risk scores were calculated in the ED. During the hospital stay, patients were evaluated daily, and the Laboratory features were collected. Data about revascularization procedures (CABG vs percutaneous coronary interven- tion), coronary artery occlusion and reperfusion efficacy were evaluated. The Institutional Ethical Committee approved this study.

Statistical analysis

Descriptive statistics are expressed as the mean +- SD or percentages. The primary analysis compared AKI with non-AKI patients. All variables were tested for normal distribution using the Kolmogorov-Smirnov test. Student t test was applied to compare the means of continuous variables and normal-distribution data. Categorical data were tested using the ?2 test. A multiple logistic regression model was built, and the association measures were calculated (adjusted odds ratio), with a confidence interval of 95%. For development of the logistic regression model, continuous variables were categorized according to the inftection point on the receiver operating characteristic curve. For the investigation of independent risk factors for AKI upon presentation to the ED, a

CT characteristics“>stepwise backward elimination multivariate analysis was performed. It included the factors that presented a significance level below 20% in the univariate analysis (Mann-Whitney and ?2 tests). We added factors related to non-ED hospitalization that were associated with AKI to the model to confirm the independent association. For heart rate, there was a J-shaped relationship with AKI; therefore, it was analyzed as a continuous variable by allowing for 2 slopes. This was achieved by fitting a linear spline with a knot at 50 bpm; values were then categorized as under 50 or above 80 vs 51 to 79 bpm. Variables determined by logistic regression underwent probit regression to calculate the weight of each variable in the prognostic score based on the probit coefficient of each variable. The Hosmer-Lemeshow goodness-of-Fit test was used to evaluate the agreement between the observed and expected number of survivors and non-survivors according to the model. A high P value (N.05) would indicate a good fit for the model. Otherwise, P b .05 were considered as statistically significant. Model comparisons were performed using nonparametric methods [17]. The statistical analysis was performed using SPSS 19.0 for Windows. The data are presented as the mean +- SD.


Subject characteristics

During the study period, a total of 431 individuals were diagnosed with STEMI diagnosis upon presentation to the ED. Thirty-one patients were excluded due to missing data (n = 16), maintenance dialysis therapy (n = 8), or previous renal transplantation (n = 1). A total of 406 patients (69.7% male) were included in the final analysis. The mean age of subjects was 62.5 +- 12.5 years. Past medical history included arterial hypertension (62.8%), diabetes mellitus (32.3%), and dyslipidemia (23.3%). At admission, 21 (5.2%) patients had hemodynamic instability, defined as the mean blood pressure under 60 mmHg. Killip classification I through IV was used for 69.9%, 17%, 7.4%, and 5.7% of patients, respectively. Regarding baseline renal function, the mean GFR was 70.5 +- 28.1 mL/min per 1.73 m2. One hundred and forty patients (34.5%) had a GFR below 60 mL/min per 1.73 m2, and 27 (6.7%) presented to the ED with a GFR less than 30 mL/ min per 1.73 m2. Complete data for each patient at the time of ED admission are shown in Table 1.

In the ED, anticoagulant therapy was administered to 84% of patients and ?-blocker therapy to 76.8%. All of the patients except four patients received platelet in- hibitors. Coronary angiography was performed in all except 1 patient, and primary percutaneous coronary intervention was performed in 87% of the patients. The complete data set for coronary obstruction are presented in

No AKI (n = 323)


(n = 86)


Age (y)

61.2 +- 12.5

67.4 +- 10.9


Women, n (%)

98 (30.3)

25 (29.1)


Baseline GFR, mL/min

72.0 +- 26.7

64.8 +- 32.9


per 1.732

Baseline GFR b 60 mL/min

96 (29.7)

43 (51.8)


per 1.732

Mean blood pressure

98.1 +- 24.8

92.7 +- 24.0


at ED (mmHg)

Systolic blood pressure

131.6 +- 31.9

125.8 +- 33.5


at ED (mmHg)

Killip classification


at ED, n (%)

Killip I

240 (74.5)

43 (51.8)

Kilip II

48 (14.9)

21 (25.3)

Killip III

21 (6.5)

9 (10.8)

Killip IV

13 (4)

10 (12)

Heart rate on presentation,

81.7 +- 18.9

89.0 +- 22.5



Hypertension, n (%)

198 (61.3)

57 (68.7)


Diabetes, n (%)

96 (29.7)

35 (42.2)


Sodium, mEq/L

137.6 +- 4.7

136.9 +- 5.9


Potassium, mEq/L

4.2 +- 2.5

4.7 +- 2.5


Hemoglobin, g/dL

13.8 +- 2.07

13.2 +- 2.17


White blood cells,

12.8 +- 3.9

14.5 +- 5.1



GRACE risk

154.5 +- 37.3

182.2 +- 38.6



4.3 +- 2.4

5.3 +- 2.2


Drugs prescribed

at ED, n (%)

Platelet inhibitor

320 (99.1)

82 (98.7)



266 (82.4)

46 (55.4)



272 (84.2)

69 (83.1)



303 (93.8)

80 (96.4)


ACE inibhitor or ARB

300 (92.9)

61 (73.5)


ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.

Table 2. After angioplasty, reperfusion was satisfactory (TIMI 2 or 3) in 90.1% of patients. Overall, Inhospital mortality was 11.8%.

AKI during hospital stay

Table 1 Presenting characteristics at ED by AKI status

During their hospital stay, 83 (20.4%) patients developed AKI: 47 (11.6%) with stage 1, 26 (6.4%) with stage 2, and 10 (2.5%) with stage 3. AKI according to GFR at admission is shown in Fig. 1. Overall, there was an increase in AKI severity with low GFR at the time of admission. Dialysis therapy was necessary in 11 (2.5%) patients. Mortality was higher in patients that developed AKI (34.9% vs 5.9%, P b .0001). There was a stepwise increase in mortality rate according to AKI severity (21%, 50%, and 60%, res- pectively, for stages 1 through 3, P b .0001).

Risk factors for developing AKI

Table 2 Coronary angiography findings, treatment, and in-hospital evolution by AKI

No AKI (n = 323)


(n = 86)


Door-to-needle time, min

102.7 +- 47.5

155.0 +- 56.4


Coronary artery culprit,

n (%)

Left main artery or

209 (67)

54 (58.4)


Anterior descending


Two or more culprit

113 (36.2)

31 (47.3)



Primary PCI, n (%)

288 (89.1)

75 (87.6)


TIMI ftow after PCI


8 (2.8)

1 (1.3)



21 (7.3)

6 (8.0)


31 (10.8)

8 (10.7)


228 (79.2)

60 (80.0)

CABG, n (%)

32 (9.9)

7 (8.1)


GP IIb/IIIa, n (%)

100 (31.9)

31 (38.8)


Clopidogrel, n (%)

292 (90.4)

76 (91.6)


Diuretic during hospital

80 (24.8)

46 (55.4)


stay, n (%)

Statin, n (%)

303 (93.8)

80 (96.4)


vasopressor therapy,

62 (19.2)

51 (61.4)


n (%)


19 (5.9)

29 (34.9)


PCI, percutaneous coronary intervention; GP, glycoprotein.

The differences between patients who did or did not develop AKI are shown in Tables 1 and 2. Overall, patients who developed AKI were older and had reduced GFR at presentation, a severe Killip classification, higher heart rate

Fig. 1 Acute kidney injury stages according to GFR at the time of ED admission.

Fig. 2 Incidence of AKI according to heart rate at the time of ED admission.

and longer door-to-needle time. Moreover, these patients received less ?-blocker and angiotensin-converting enzyme inhibitors/angiotensin receptor blocker medication in the ED. After they left the ED, these patients were more prone to receive diuretic and vasopressor therapy.

Aiming at a better understanding of the association between heart rate and ?-blocker use with AKI, the relationship of AKI and heart rate was analyzed (Fig. 2). There was an increase in AKI when heart rate was lower than 50 bpm. The number of patients with heart rate below 50 bpm was only 16 (3.9%) and of these, only 3 received ?-blockers; one of these patients developed AKI (P = .898). Above 50 bpm, there was a stepwise increase in AKI occurrence, especially when the patient’s heart rate was above 80 bpm. Furthermore, AKI injury severity was higher in those patients who were not receiving ?– blocker treatment.

Multivariate analysis including all factors listed in Table 1 as well as door-to-needle time identified age, Killip class, heart rate at admission, door-to-needle time, and ?-blocker use at admission as independent factors associated with the development of AKI during hospital stay (Table 3). After adjusting for the other 2 variables related to AKI during hospital stay (diuretic and vasopressor use), the association was maintained.

The derived risk score for AKI (Table 4) had a good calibration when tested with the Hosmer-Lemeshow method (?2 = 8.640, P = .374) (Fig. 3) and a discrimination capacity (area under receiving Operator characteristics) of 0.813 (0.741-0.886), which is better than that of GRACE (AUROC 0.679 CI 0.637-0.721) or TIMI risk (AUROC 0.592 CI

0.542-0.640) when used to predict AKI, P = .011 and 0.005, respectively, as shown in Fig. 4.

Reference parameter

Hazard ratio of AKI

95% CI


Model 1: variables collected at ED


b 65 years




Heart rate

Heart rate between 50-80 bpm




Killip class

Class I




?-Blocker use at ED





Door-to-needle time

Less than 120 min




Model 2: Model 2 + diuretic use and vasopressor need during hospital stay


b 65 years




Heart rate

Heart rate between 50-80 bpm




Killip class

Class I




?-Blocker use at ED





Door-to-needle time (N 120 min)

Less than 120 min





Table 3 Hazard ratio of hospital mortality by previous nephrology consultation

The present study demonstrated independent risk factors in the ED associated with AKI occurrence during hospital- ization in patients with STEMI. In summary, increasing age, Killip class, heart rate in the ED, and door-to-needle time were risk factors for AKI, while ?-blocker use was protective. Moreover, the score risk derived from these factors showed good discrimination and calibration, allow- ing the emergency physician to identify patients at risk of developing AKI. Moreover, for the first time, we suggest an association between door-to-needle time and ?-blocker use in the ED and reduced AKI in STEMI patients.

Patients suffering an AMI are at high-risk for developing AKI. The risk factors for developing AKI are related to morbidities (high prevalence of diabetes mellitus and chronic kidney disease [18]), procedures (contrast, CABG) and cardiac complications (hemodynamic instability, heart fail- ure). All these factors are associated with AKI development and risk factors for the development of AKI in each specific situation have already been studied extensively [7,10,11,13,19]. However, AKI-related risk factors in patients presenting AMI have been studied only recently [5], and there has been no study evaluating the risk factors in the ED.

The new interest in AKI after AMI is due to the association between AKI with in-hospital and long-term mortality [5,8]. The association between AKI and mortality

Table 4 AKI Score at ED after STEMI Risk factor

Age (N 65 years)

Heart rate (N 80 or b 50 bpm)

Killip class

?-Blocker use at ED (users are reference) Door-to-needle time (N 120 min)

Score ranges from 0 to 16.

a Add 2 points to each Killip class above I.




2 a



in this setting remains even after 10 years of follow-up [3]. These studies identify a new concern regarding the prevention of AKI after AMI. Recently, a large study evaluating the inftuence of AKI on the short-term outcome of patients with AMI revealed other new and important risk factors for AKI: STEMI vs non-STEMI, heart rate, and an unexplained protective effect of dyslipidemia on AKI occurrence [5]. The abovementioned study is a landmark due to the large number of patients (n = 59.970); however, it was a retrospective study and did not describe all ED- associated factors (Killip class, prescribed medications, door-to-needle time).

In our data, some risk factors are also classically associated with AKI in other clinical scenarios, such as age and heart dysfunction (in this study, heart dysfunction was evaluated using Killip class). Heart rate was also recently described to exhibit a J-shaped correlation with AKI [5]. Interestingly, even within the normal heart rate range, there was an increase in AKI occurrence, and bradycardia was associated with AKI only at less than 50 bpm (Fig. 2). We were able to identify 2 modifiable factors in the ED that could potentially reduce AKI in patients with STEMI: door- to-needle time and ?-blocker use.

Fig. 3 AKI score calibration.

Fig. 4 Discrimination of risk scores for the development of AKI after STEMI. “Score at the ED” includes age, Killip class, heart rate at admission, door-to-needle time, and ?-blocker use. The weight of each variable was based on multivariate analysis coefficients.

?-Blockers are routinely prescribed to patients with AMI unless there is any contraindication, mainly a low heart rate, decompensated heart failure, or bronchoconstriction. In the setting of AMI, low heart rate and heart failure are potential complications and are also associated with AKI [7]. However, even after adjusting for heart rate at presentation and Killip class, ?-blocker use was still associated with low AKI frequency and reduced severity.

Possible mechanisms through which ?-blockers can protect against AKI include a direct effect on renal function, activating endothelial nitric oxide synthase and improving endothelial dysfunction secondary to renal ischemia [20]. In addition, ?-blockers can ameliorate renal function by reducing sympathetic activation: there is a large amount of data on the effects of Sympathetic activity on Renal damage [21]. The last hypothesis is more clearly supported by our data. AMI is associated with Sympathetic hyperactivity, and our data demonstrated that, in addition to ?-blocker use, elevated heart rate, even within the normal range, was also associated with AKI. Because propranolol (40 mg PO thrice daily) is the standardized ?-blocker administered in the ED of the study institution, it is not possible to determine if this effect is agent- or class-specific.

Although we have adjusted for heart rate, Killip class, need for vasopressor drugs and mean blood pressure, it is difficult to include all potential confounding factors in the association between ?-blocker use and AKI. A more careful interpretation of our data implies, at least, that STEMI patients not receiving ?-blockers in the ED must be observed by emergency physicians as a high-risk with respect to the development of AKI. The association between an increasing

reperfusion time and AKI is clearer. When early reperfusion is performed, there is less myocardial damage, heart failure, and hemodynamic instability.

We have compared our score with 2 composite risk scores regarding their ability to predict AKI (GRACE and TIMI risk scores). Although these scores were designed to predict mortality, they are the most used by ED physicians, and although patients with AKI had higher GRACE and TIMI scores, neither had good discriminatory capacity to predict AKI. This finding highlights the importance of a specific score. While model 1 (Table 3) included only variables at ED presentation, the second model also analyzes the effects of diuretic use and vasopressor use during the hospital stay. These were the only ED-related factors associated with AKI occurrence. The first model was preferred for risk score development because it is more reliable for clinical practice.

The risk score for developing AKI after AMI can help emergency physicians to expediently identify early patients at high risk. Avoiding exposure to nephrotoxic drugs, excessive contrast volume, and hemodynamic instability can reduce renal injury and improve patient outcomes.

Our study has several limitations: the relatively low number of patients is counterbalanced by the quality of the data collected data. Second, all patients presented with STEMI, and the results cannot be extrapolated to other acute coronary syndromes. The reported score is simply one of derivation and before any clinical use, prospective validation on a separate cohort followed by prospective application in a multicenter study is needed. Lastly, we reinforce the difficulty in detangling a direct effect of ?– blockers on renal function, even after adjusting for many variables. Only a randomized study can answer this question adequately, but it is not feasible owing to the known beneficial effect of ?-blockers on mortality. Therefore, in this observational study, one can safely state that patients who are not receiving ?-blockers are at a high risk for developing AKI after STEMI.

In conclusion, we determined that admission to the ED

increases the patient’s exposure to risk factors that can contribute to AKI in patients with STEMI. Information about age, heart rate, ?-blocker use in the ED, Killip class, and door-to-needle time were independently associated with AKI after STEMI. A simple score was developed to be used by ED physicians to access AKI risk. Moreover, ?-blocker use must be assessed adequately to evaluate its potential renal protection in patients suffering from AMI.


We are very grateful to the team of physicians, residents, medical students and nurses from Hospital de Messejana for the assistance provided to the patients and for the technical support provided for the development of this research.


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