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Abstract

Objectives

To examine retrospectively the relationship between acute kidney injury (AKI) and acute myocardial infarction (AMI), and the association between estimated glomerular filtration rate (eGFR) at admission and AKI outcome.

Methods

AKI was defined as an increase in serum creatinine (SCr) by ≥0.3 mg/dl within 48 h or an increase in SCr to ≥1.5 times baseline within the first 7 days of hospitalization. Patients with AMI were divided into subgroups according to their eGFR at admission and the development of AKI.

Results

This study enrolled 396 patients with AMI; 48 (12.1%) developed AKI. In-hospital mortality was 39.6% (19/48) for patients with AKI compared with 7.5% (26/348) in those without AKI (odds ratio [OR] 8.11; 95% confidence interval [CI] 4.02, 16.39). The mortality rate was 35.7% (five of 14) in the eGFR ≥ 60 ml/min/1.73m² with AKI group (OR 6.21, 95% CI 1.50, 25.69) and 41.2% (14/34) in the eGFR < 60 ml/min/1.73m² with AKI group (OR 12.62, 95% CI 5.54, 28.74).

Conclusions

AKI development was common and associated with mortality in AMI patients with either preserved or impaired eGFR levels.

Keywords

Acute kidney injury acute myocardial infarction glomerular filtration rate mortality renal function

Introduction

Acute kidney injury (AKI; previously known as acute renal failure) is a common complication that affects patients with various clinical conditions, such as acute myocardial infarction (AMI),^1–3 congestive heart failure;⁴ and those undergoing cardioangiography (CAG)⁵ and percutaneous coronary intervention (PCI).⁶ Recent studies suggest that AKI is associated with poor outcomes and independently predicts increasing long-term mortality.^1,7–11 However, few studies have investigated the early risk of AKI with AMI.

It is well known that the diagnostic procedure for AKI is not standardized. Rodrigues et al.¹² reported there are over 30 definitions of AKI in the medical literature. This variability causes confusion, making it difficult to compare results across multiple studies. The Risk, Injury, Failure, Loss, End-Stage Renal Disease (RIFLE)¹³ and Acute Kidney Injury Network (AKIN)¹⁴ criteria are most commonly used in the study of AKI syndrome. Unfortunately, the existing criteria, while useful and widely validated, are still limited. Hence, in 2012, the Kidney Disease Improving Global Outcomes (KDIGO)¹⁵ Clinical Practice Guidelines for AKI were designed, to compile information systematically on this topic by experts in the field. Definition and staging of AKI are based on the RIFLE and AKIN criteria. In short, AKI is defined as an increase in serum creatinine (SCr) by ≥0.3 mg/dl within 48 h or an increase in SCr to ≥1.5 times the baseline score within the first 7 days. The effect of pre-existing renal dysfunction on AKI and mortality with AMI remains controversial.^16–20 There is very little information about the role of impaired estimated glomerular filtration rate (eGFR) at the time of hospital admission on the mortality in patients with AMI-associated AKI (as defined by KDIGO).

The present investigation sought to evaluate the prevalence of AKI in association with AMI, and to investigate the association between a decreased admission eGFR and short-term outcome inpatients developing AKI, as defined by the KDIGO criteria, in the AMI setting.

Patients and methods

Study population

This retrospective study enrolled consecutive patients admitted to the Department of Cardiology, The Affiliated Longyan First Hospital of Fujian Medical University, Longyan, Fujian Province, China, between January 2011 and December 2012, whose discharge diagnosis was AMI (ST-elevation myocardial infarction [STEMI] or non-ST segment elevation myocardial infarction [NSTEMI]).²¹ Study exclusion criteria included: lack of at least two SCr measurements at hospitalization; presence of obstructive AKI. The institutional review board of Longyan First Hospital of Fujian Medical University approved the study and all study participants provided written informed consent prior to enrolment.

Data collection

Data collection was performed using a standardized paper case-report form. Collected data included: patient characteristics, past medical history, final discharge diagnosis, electrocardiogram findings, laboratory investigations, echocardiography changes, medical therapies, use of cardiac procedures and interventions, in-hospital outcomes and overall mortality.

After an overnight fast, venous blood samples (10 ml) were collected into haemogram tubes containing di-potassium ethylenediaminetetra-acetic acid (1.5–2.2 mg/ml) and biochemistry tubes. Samples were maintained at room temperature and tested within 1 h of collection. White blood cell (WBC) counts and haemoglobin levels were determined using an automated blood cell counter (XE-5000™; Sysmex, Kobe, Japan), according to the manufacturer’s instructions. Creatine phosphokinase myocardial bundle (CKMB) and SCr were quantiﬁed using a biochemical analyser (AU2700; Olympus, Tokyo, Japan). Systolic and diastolic blood pressures were measured by trained personnel using a mercury sphygmomanometer. Ejection fraction (EF) was measured and calculated using ultrasound equipment (HD7 Ultrasound System; Philips, Eindhoven, The Netherlands).

Diagnostic criteria for AKI

The SCr at hospital admission and daily during the coronary care unit stay was available for all analysed patients. eGFR was calculated using the abbreviated Modification of Diet in Renal Disease study equation.²² Chronic kidney disease (CKD) was defined as an eGFR < 60 ml/min/1.73 m² for >3 months. AKI was defined as increase in SCr by ≥0.3 mg/dl within 48 h or an increase in SCr to ≥1.5 times baseline within the first 7 days of hospitalization (based on the KDIGO criteria). AKI stage was defined as follows, using SCr: stage 1, 1.5–1.9 times baseline or ≥0.3 mg/dl increase; stage 2, 2.0–2.9 times baseline; stage 3, 3.0 times baseline or an increase to ≥4.0 mg/dl or initiation of renal replacement therapy. Non-AKI was defined as a change in creatinine level of <0.3 mg/dl. Patients were divided into four admission eGFR subgroups: eGFR ≥ 60 ml/min/1.73 m² without AKI; eGFR < 60 ml/min/1.73 m² without AKI; eGFR ≥ 60 ml/min/1.73 m² with AKI; eGFR < 60 ml/min/1.73 m² with AKI.

Outcomes

The primary study endpoint was in-hospital death from all causes. The secondary study endpoints were the occurrence of in-hospital complications including cardiogenic shock, major bleeding, stroke and malignant ventricular arrhythmia.

Statistical analyses

All statistical analyses were performed using the SPSS® statistical package, version 15.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Continuous variables are presented as mean ± SD or median (with interquartile ranges) and categorical variables as n (%) of patients. Baseline characteristics of the groups were compared using analysis of variance for continuous variables and χ²-test for categorical variables. Univariate and multivariate logistic regression were used to identify the risk factors influencing AKI, and the association between mortality and admission eGFR and AKI development. The strength of the association between risk factors and AKI was expressed as an odds ratio (OR) with a 95% confidence interval (CI). The following baseline clinical and biochemical characteristics were considered in the multivariate procedure: age, sex, history of hypertension, diabetes mellitus, stroke, prior MI, smoking status, systolic blood pressure, heart rate, anterior MI (or not), heart failure on admission, revascularization status and complications. In addition, the following baseline laboratory tests were taken into account: haemoglobin, WBC counts, baseline SCr and eGFR in successive models. Only variables with P < 0.1 in the univariate logistic regression analyses were used in the multiple logistic regression analyses. Differences were considered statistically significant by a two tailed P-value of < 0.05.

Results

This study included 441 consecutive patients, 45 of whom met the exclusion criteria and were excluded from the study. The study was undertaken with 396 patients with AMI (127 [32.1%] with STEMI and 269 [67.9%] with NSTEMI). Baseline clinical and demographic characteristics of the patients, grouped according to whether or not they had AKI, are presented in Table 1. Patients who developed AKI were significantly more likely to be older, have hypertension, and have diabetes mellitus than the non-AKI patients (P < 0.05 for all comparisons). SCr, peripheral WBC counts and peak CKMB were significantly higher in the AKI group than in the non-AKI group (P < 0.05 for all comparisons). eGFR was significantly lower in the AKI group than in the non-AKI group (P < 0.001). Patients with AKI were significantly more likely than non-AKI patients to have a faster heart rate and a higher Killip class (>I) at presentation (P < 0.001 for both comparisons). Patients with AKI were significantly less likely to receive β-blockers and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers than non-AKI patients (P < 0.001 for both comparisons) (Table 2). Patients with AKI were significantly less likely to undergo CAG or PCI during their hospitalization than non-AKI patients (P < 0.001 for both comparisons). Patients who developed AKI had a significantly higher rate of cardiogenic shock than those in the non-AKI group (P < 0.001).

Table 1.

Demographic and clinical characteristics of patients (n = 396) with a discharge diagnosis of acute myocardial infarction (MI), stratified according to presence or absence of acute kidney injury (AKI).

Characteristics	Total cohort n = 396	Non-AKI group n = 348	AKI group n = 48	Statistical significance^a
Age, years	65.4 ± 11.9	64.9 ± 11.7	69.3 ± 12.8	P = 0.018
Male	325 (82.1)	286 (82.2)	39 (81.3)	NS
Disease history
Hypertension	169 (42.7)	141 (40.5)	28 (58.3)	P = 0.028
Diabetes mellitus	65 (16.4)	52 (14.9)	13 (27.1)	P = 0.039
Stroke	40 (10.1)	35 (10.1)	5 (10.4)	NS
Currently smoking	229 (57.8)	202 (58.0)	27 (56.3)	NS
Prior MI	20 (5.1)	17 (4.9)	3 (6.3)	NS
SBP at admission, mmHg	127.9 ± 30.6	128.2 ± 28.1	125.8 ± 45.2	NS
HR at admission, bpm	80.3 ± 19.6	79.0 ± 18.6	89.9 ± 23.3	P < 0.001
Baseline SCr, mg/dl	1.2 ± 0.9	1.0 ± 0.4	2.2 ± 1.9	P < 0.001
eGFR, ml/min/1.73 m²	77.0 ± 29.0	81.9 ± 25.8	40.2 ± 25.6	P < 0.001
Peak CKMB, IU/l	102.5 (33.0–238.5)	94.0 (29.0–221.8)	145.0 (48.0–369.3)	P = 0.02
Haemoglobin, g/l	131.7 ± 18.7	132.6 ± 18.4	125.2 ± 19.9	NS
WBC count, ×10⁹/l	10.9 ± 4.9	10.5 ± 4.3	14.0 ± 7.4	P < 0.001
EF, %	59.0 ± 11.9	59.0 ± 11.0	59.0 ± 15.0	NS
Killip class > I	207 (52.3)	163 (46.8)	44 (91.7)	P < 0.001
Anterior MI	125 (31.6)	116 (33.3)	9 (18.8)	P = 0.047

Data presented as mean ± SD, median (interquartile range) or n (%) of patients.

Baseline characteristics of the two groups were compared using analysis of variance for continuous variables and χ²-test for categorical variables.

SBP, systolic blood pressure; HR, heart rate; bpm, beats per min; SCr, serum creatinine; eGFR, estimated glomerular filtration rate; CKMB, creatine phosphokinase myocardial bundle; WBC, white blood cell; EF, ejection fraction; NS, not statistically significant (P ≥ 0.05).

Table 2.

Comparison of in-hospital procedures, medication use and adverse outcomes for patients (n = 396) with a discharge of diagnosis acute myocardial infarction, stratified according to presence or absence of acute kidney injury (AKI).

Variable	Total cohort n = 396	Non-AKI group n = 348	AKI group n = 48	Statistical significance^a
Medication use
Aspirin	371 (93.7)	328 (94.3)	43 (89.6)	NS
Clopidogrel	376 (94.9)	333 (95.7)	43 (89.6)	NS
ACE inhibitor/ARB	310 (78.3)	284 (81.6)	26 (54.2)	P < 0.001
Heparin	354 (89.4)	314 (90.2)	40 (83.3)	NS
β-blocker	261 (65.9)	240 (69.0)	21 (43.8)	P < 0.001
Glycoprotein IIb/IIIa inhibitor	53 (13.4)	47 (13.5)	6 (12.5)	NS
In-hospital procedures
CAG	212 (53.5)	198 (56.9)	14 (29.2)	P < 0.001
PCI	180 (45.5)	167 (48.0)	13 (27.1)	P < 0.001
Thrombolysis	69 (17.4)	61 (17.5)	8 (16.7)	NS
Conservative therapy	205 (51.8)	170 (48.9)	35 (72.9)	P = 0.002
Adverse outcomes
Mortality	45 (11.4)	26 (7.5)	19 (39.6	P < 0.001
Cardiogenic shock	64 (16.2)	43 (12.4)	21 (43.8)	P < 0.001
Bleeding	25 (6.3)	19 (5.5)	6 (12.5)	NS
Stroke	13 (3.3)	9 (2.6)	4 (8.3)	NS
VF/VT	24 (6.1)	20 (5.7)	4 (8.3)	NS

Data presented as n (%) of patients.

Clinical variables of the two groups were compared using χ²-test.

ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker; CAG, cardioangiography; PCI, percutaneous coronary intervention; VF/VT, ventricular fibrillation/ventricular tachycardia; NS, not statistically significant (P ≥ 0.05).

Acute kidney injury occurred in 48 of the 396 (12.1%) patients; with 40 patients (10.1%) in stage 1 and eight patients (2.0%) in stages 2 and 3. The rate of AKI at admission stratified according to baseline eGFR status showed a significant association with eGFR (P < 0.001) (Figure 1). Univariate and multivariate analyses of risk factors associated with AKI in the acute MI setting are presented in Tables 3 and 4, respectively. The eGFR < 60 ml/min/1.73 m² (OR 7.45, 95% CI 2.91, 19.05), baseline SCr (OR 1.10, 95% CI 1.00, 1.14) and Killip class ≥III (OR 3.79, 95% CI 1.68, 8.55) were strongly associated with AKI on multivariate analysis.

Figure 1.

Proportion of patients (%) with acute kidney injury (AKI) in 396 patients with a discharge diagnosis of acute myocardial infarction, stratified according to their baseline estimated glomerular filtration rate (eGFR) at the time of hospital admission.

Table 3.

Univariate risk factors for acute kidney injury (AKI) in patients (n = 396) with a discharge diagnosis acute myocardial infarction (MI).

Parameter	Univariate predictor Odds ratio (95% CI)	Statistical significance
Age, ≥75 years	2.47 (1.32, 4.63)	P = 0.005
Male	1.08 (0.50, 2.35)	NS
History of hypertension	2.06 (1.11, 3.79)	P = 0.021
Diabetes mellitus	2.11 (1.05, 4.26)	P = 0.036
Current smoking	0.93 (0.51, 1.71)	NS
Prior stroke	1.04 (0.39, 2.80)	NS
Prior MI	1.30 (0.37, 4.61)	NS
SBP at admission, <100 mmHg	2.80 (1.34, 5.85)	P = 0.006
HR at admission, >100 bpm	4.08 (2.05, 8.12)	P < 0.001
eGFR, <60 ml/min/1.73 m²	15.94 (7.56, 33.60)	P < 0.001
Baseline SCr, per1 mg/dl increase	3.12 (2.12, 4.58)	P < 0.001
Haemoglobin, <90 g/l	2.48 (0.49, 12.64)	NS
WBC count, >13 × 10⁹/l	3.55 (1.90, 6.65)	P < 0.001
Killip class ≥ III	9.36 (4.58, 19.11)	P < 0.001
Anterior MI	0.46 (0.22, 0.97)	P = 0.042
PCI	0.40 (0.21, 0.79)	P = 0.008
Cardiogenic shock	5.52 (2.87, 10.61)	P < 0.001
Bleeding	2.47 (0.94, 6.54)	NS
Stroke	3.42 (1.01, 11.60)	P = 0.048
VF/VT	1.49 (0.49, 4.56)	NS

CI, confidence interval; SBP, systolic blood pressure; HR, heart rate; bpm, beats per min; eGFR, estimated glomerular filtration rate; SCr, serum creatinine; WBC, white blood cell; PCI, percutaneous coronary intervention; VF/VT, ventricular fibrillation/ventricular tachycardia; NS, not statistically significant (P ≥ 0.05).

Table 4.

Multivariate risk factors for acute kidney injury in patients (n = 396) with a discharge diagnosis acute myocardial infarction.

Parameter	Multivariate predictor Odds ratio (95% CI)	Statistical significance
eGFR, <60 ml/min/1.73 m²	7.45 (2.91, 19.05)	P < 0.001
Baseline SCr, mg/dl	1.10 (1.00, 1.14)	P = 0.014
Killip class ≥ III	3.79 (1.68, 8.55)	P < 0.001

CI, confidence interval; eGFR, estimated glomerular filtration rate; SCr, serum creatinine.

Overall, there were 45 deaths (11.4%) during hospitalization; 26/348 (7.5%) patients in the non-AKI group compared with 19/48 (39.6%) patients in the AKI group (P < 0.001) (Table 2). In the overall sample, the OR of death in patients with AKI was 8.11 (95% CI 4.02, 16.39; P < 0.001) compared with those without AKI.

The influence of baseline eGFR and AKI on mortality was examined. Patients with a diminished eGFR and AKI at admission had the worst outcome, with a mortality OR of 12.62 (95% CI 5.54, 28.74; P < 0.001; Table 5).

Table 5.

Influence of impaired admission estimated glomerular filtration rate (eGFR) on in-hospital mortality rates with and without acute kidney injury (AKI) in patients (n = 396) with a discharge diagnosis acute myocardial infarction.

	Rate of AKI n (%)	Odds ratio (95% CI)	Statistical significance^a
Group 1: eGFR ≥ 60 ml/min/1.73 m² without AKI, n = 281	16 (5.7)	1.00
Group 2: eGFR < 60 ml/min/1.73 m² without AKI, n = 67	10 (14.9)	2.91 (1.25, 6.73)	P = 0.013
Group 3: eGFR ≥ 60 ml/min/1.73 m² with AKI, n = 14	5 (35.7)	6.21 (1.50, 25.69)	P = 0.012
Group 4: eGFR < 60 ml/min/1.73 m² with AKI, n = 34	14 (41.2)	12.62 (5.54, 28.74)	P < 0.001

Compared with group 1; odds ratios were compared using logistic regression analysis.

CI, confidence interval.

Discussion

The main finding of the study was that AKI, defined by the KDIGO criteria, was associated with in-hospital mortality in AMI in patients, with or without impaired eGFR on admission. Overall, the prevalence of AKI in the setting of AMI was 12.1% (48/396 patients). Those with AKI had a substantially higher risk of mortality than those without AKI (P < 0.001).

Patients who have an AMI are at high risk of developing AKI. For example, in a prospective study of patients with STEMI, Goldberg et al.¹ found that 9.6% of individuals experienced worsening renal injury (defined as a 0.5 mg/dl elevation of the SCr level at any point) during their hospital stay. Worsening renal function was associated with an 11.4-fold increased risk of in-hospital mortality.¹ Another study defined AKI as an absolute change in SCr levels; the resulting injury was classified as mild (0.3–0.4 mg/dl), moderate (0.5–0.9 mg/dl), or severe (1.0 mg/dl).¹¹ Using these criteria, AKI was identified in 19.4% (7.1% mild, 7.1% moderate and 5.2% severe) of patients.¹¹ A large study evaluating the influence of AKI on short-term outcome in patients with AMI observed an AKI rate of 16%.²³ When AMI is complicated by cardiogenic shock, AKI may affect over half of all patients.²⁴ However, these investigations did not strictly use the standardized criteria for diagnosing AKI. Some investigations used their own criteria to diagnose, while others used SCr at any timepoint or at 7 days. For future studies, it is very important that standardized AKI criteria are used, such as the KDIGO criteria,²⁵ to allow comparison of results between different studies.

The RIFLE and AKIN criteria also have limitations. First, despite efforts to standardize the definition and classification of AKI, there are still inconsistencies in their application. Secondly, some AKI cases may be missed. Joannidis et al.²⁶ directly compared the RIFLE and AKIN criteria and found that the original RIFLE criteria failed to detect 9% of cases that were detected by the AKIN criteria. However, the AKIN criteria missed 26.9% of cases detected by RIFLE.²⁶ Thirdly, the stages within the RIFLE criteria, containing three severity grades and two outcome criteria, are ambiguous. In addition, in the KDIGO criteria, stage 3 requires patients to reach SCr > 4.0 mg/dl, rather than an acute increase of ≥0.5 mg/dl (AKIN criteria). This change brings the definition and staging criteria to greater parity, and simplifies the criteria.

In this present study, AKI development was common in patients with AMI and was associated with an increased risk of mortality. Furthermore, AKI development was associated with increased in-hospital mortality in AMI patients. Similarly, a retrospective evaluation of the incidence of AKI, based on the AKIN definition, in patients with acute coronary syndromes (ACS; 53% with STEMI, 41% with NSTEMI, and 6% with unstable angina pectoris) found that 13% developed AKI: 8.3% had stage 1, and 4.7% had stage 2 and 3 AKI.²⁷ In-hospital mortality was greater in patients with AKI than in those without AKI (21% versus 1%; P < 0.001).²⁷ There were some differences between these two studies. First, studies used different criteria (KDIGO versus AKIN) and different patient types (AMI versus ACS). This current study examined a more high-risk population, with 51.8% of patients being treated conservatively, 10.1% of patients having had a prior stroke and 16.2% having AMI complicated by cardiogenic shock. As expected, the in-hospital mortality rate in this cohort was similar as that usually reported for AMI patients, which was about 4.1–13.2%.^23,28

A limited number of studies have assessed the role of admission eGFR on the outcome of AMI-associated AKI, especially in terms of short-term outcomes. For example, a study evaluating AMI patients showed that AKI, defined as a ≥25% decrease in eGFR at any timepoint during hospitalization, was associated with a higher 1-year mortality rate.²⁹ The conclusion was that AKI was a risk factor for 1-year mortality, independent of admission eGFR.²⁹ Bruetto et al.²⁸ reported that an admission eGFR of <60 ml/min/1.73 m² with AKI was significantly associated with a 30-day to 1-year mortality hazard (adjusted hazard ratio 3.05, 95% CI 1.50, 6.19) using RIFLE criteria (AKI was defined as a SCr increase of ≥50% from the time of admission in the first 7 days of hospitalization). Most studies have focused on the long-term mortality but few on the short-term outcomes.^11,23 This current study looked at short-term outcomes and for the first time found that an admission eGFR of <60 ml/min/1.73m² with AKI was significantly associated with in-hospital mortality. This means that patients with either chronic or acute renal dysfunction are at a very high risk for in-hospital mortality, which might reflect the underlying mechanisms that adversely affect both cardiac and renal function.

Associations between AKI and these short-term risks after AMI have several possible explanations. First, patients who develop AKI have a higher prevalence of comorbidities such as diabetes mellitus, hypertension, and CKD, each of which may increase the risk of kidney failure and death.² Secondly, significant differences were observed in the type of AMI treatment received by the two groups in this study. For example, patients in the AKI group were significantly less likely to receive some pharmacological therapies or to undergo interventional procedures. Thirdly, AKI will directly contribute to distant organ dysfunction through the mechanisms of oxidative stress and inflammation. This means that AKI severity, using the KDIGO criteria, represents not only kidney damage but also an imbalance between the kidney and other organ systems. Therefore, AKI defined by the KDIGO criteria, has a greater effect on mortality.

There are several points to be considered. First, the prevalence of AKI in the AMI setting is high and clinicians need to be aware of this important complication. Secondly, uniform standards for diagnosing and classifying AKI should be adopted, which need validation before using in future studies. Thirdly, AKI is associated with the early in-hospital outcomes of AMI in patients with either nonimpaired or impaired admission eGFR. Thus, it is critical to consider measures to prevent AKI as they may represent a viable method for reducing mortality in the AMI setting.

This present study had a number of limitations. It was a single-centre, observational, retrospective cohort study and it used the KDIGO criteria to define AKI, but information on urinary output was not available in the study sample.

In conclusion, AKI occurred in 12.1% (48/396) of patients hospitalized for AMI. This common complication was strongly associated with mortality. The presence of a low eGFR level on admission in patients with AMI-associated AKI was related to a poor short-term survival prognosis. Patients with an impaired eGFR level upon admission, who develop AKI, require extensive clinical monitoring. These results strongly suggest that recognition of these risks and the adoption of appropriate strategies to avoid AKI may improve outcomes after AMI, especially for patients with CKD.

Footnotes

Declaration of conflicting interest

The authors declare that there are no conflicts of interest.

Funding

This study was supported by a grant from the Affiliated Longyan First Hospital of Fujian Medical University (no. 2012001).

References

Goldberg

Hammerman

Petcherski

. Inhospital and 1-year mortality of patients who develop worsening renal function following acute ST-elevation myocardial infarction. Am Heart J 2005; 150: 330–337.

Hwang

Jeong

Ahmed

. Different clinical outcomes of acute kidney injury according to acute kidney injury network criteria in patients between ST elevation and non-ST elevation myocardial infarction. Int J Cardiol 2011; 150: 99–101.

Lazzeri

Valente

Chiostri

. ST-elevation myocardial infarction with preserved ejection fraction: the impact of worsening renal failure. Int J Cardiol 2012; 155: 170–172.

Shirakabe

Hata

Kobayashi

. Long-term prognostic impact after acute kidney injury in patients with acute heart failure. Int Heart J 2012; 53: 313–319.

James

Ghali

Knudtson

. Associations between acute kidney injury and cardiovascular and renal outcomes after coronary angiography. Circulation 2011; 123: 409–416.

Robert

Brown

Sidhu

. The evaluation of creatinine clearance, estimated glomerular filtration rate and serum creatinine in predicting contrast-induced acute kidney injury among patients undergoing percutaneous coronary intervention. Cardiovasc Revasc Med 2012; 13: 3–10.

Amin

Spertus

Reid

. The prognostic importance of worsening renal function during an acute myocardial infarction on long-term mortality. Am Heart J 2010; 160: 1065–1071.

Coca

Yusuf

Shlipak

. Long-term risk of mortality and other adverse outcomes after acute kidney injury: a systematic review and meta-analysis. Am J Kidney Dis 2009; 53: 961–973.

Hsieh

Chen

. Renal dysfunction on admission, worsening renal function, and severity of acute kidney injury predict 2-year mortality in patients with acute myocardial infarction. Circ J 2013; 77: 217–223.

10.

Jose

Skali

Anavekar

. Increase in creatinine and cardiovascular risk in patients with systolic dysfunction after myocardial infarction. J Am Soc Nephrol 2006; 17: 2886–2891.

11.

Parikh

Coca

Wang

. Long-term prognosis of acute kidney injury after acute myocardial infarction. Arch Intern Med 2008; 168: 987–995.

12.

Rodrigues

Bruetto

Torres

. Effect of kidney disease on acute coronary syndrome. Clin J Am Soc Nephrol 2010; 5: 1530–1536.

13.

Bellomo

Ronco

Kellum

. Acute renal failure – definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004; 8: R204–R212.

14.

Mehta

Kellum

Shah

. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care 2007; 11: R31–R31.

15.

Kellum

Lameire

. the KDIGO AKI Guideline Work Group. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care 2013; 17: 204–204.

16.

Ishani

Xue

Himmelfarb

. Acute kidney injury increases risk of ESRD among elderly. J Am Soc Nephrol 2009; 20: 223–228.

17.

Khosla

Soroko

Chertow

. Preexisting chronic kidney disease: a potential for improved outcomes from acute kidney injury. Clin J Am Soc Nephrol 2009; 4: 1914–1919.

18.

Kolli

Rajagopalam

Patel

. Mild acute kidney injury is associated with increased mortality after cardiac surgery in patients with eGFR <60 mL/min/1.73 m(2). Ren Fail 2010; 32: 1066–1072.

19.

Skott

Nørregaard

Sorensen

. Pre-existing renal failure worsens the outcome after intestinal ischaemia and reperfusion in rats. Nephrol Dial Transplant 2010; 25: 3509–3517.

20.

Huang

Lai

. Acute-on-chronic kidney injury at hospital discharge is associated with long-term dialysis and mortality. Kidney Int 2011; 80: 1222–1230.

21.

Thygesen

Alpert

White

. Universal definition of myocardial infarction. J Am Coll Cardiol 2007; 50: 2173–2195.

22.

Stevens

Coresh

Greene

. Assessing kidney function – measured and estimated glomerular filtration rate. N Engl J Med 2006; 354: 2473–2483.

23.

Fox

Muntner

Chen

. Short-term outcomes of acute myocardial infarction in patients with acute kidney injury: a report from the national cardiovascular data registry. Circulation 2012; 125: 497–504.

24.

Marenzi

Assanelli

Campodonico

. Acute kidney injury in ST-segment elevation acute myocardial infarction complicated by cardiogenic shock at admission. Crit Care Med 2010; 38: 438–444.

25.

Rodrigues

Bruetto

Torres

. Incidence and mortality of acute kidney injury after myocardial infarction: a comparison between KDIGO and RIFLE criteria. PLoS One 2013; 8: e69998–e69998.

26.

Joannidis

Metnitz

Bauer

. Acute kidney injury in critically ill patients classified by AKIN versus RIFLE using the SAPS 3 database. Intensive Care Med 2009; 35: 1692–1702.

27.

Marenzi

Cabiati

Bertoli

. Incidence and relevance of acute kidney injury in patients hospitalized with acute coronary syndromes. Am J Cardiol 2013; 111: 816–822.

28.

Bruetto

Rodrigues

Torres

. Renal function at hospital admission and mortality due to acute kidney injury after myocardial infarction. PLoS One 2012; 7: e35496–e35496.

29.

Lazaros

Tsiachris

Tousoulis

. In-hospital worsening renal function is an independent predictor of one-year mortality in patients with acute myocardial infarction. Int J Cardiol 2012; 155: 97–101.

Renal function,acute kidney injury and hospital mortality in patients with acute myocardial infarction

Abstract

Objectives

Methods

Results

Conclusions

Keywords

Introduction

Patients and methods

Study population

Data collection

Diagnostic criteria for AKI

Outcomes

Statistical analyses

Results

Discussion

Footnotes

Declaration of conflicting interest

Funding

References