Prognostic Value of Chronic Kidney Disease Measures in Patients With Cardiac Disease

Abstract

Chronic kidney disease (CKD) is considered a global public health issue. The latest international clinical guideline emphasizes characterization of CKD with both glomerular filtration rate (GFR) and albuminuria. CKD is closely related to cardiac disease and increases the risk of adverse outcomes among patients with cardiovascular disease (CVD). Indeed, numerous studies have investigated the association of CKD measures with prognosis among patients with CVD, but most of them have focused on kidney function, with limited data on albuminuria. Consequently, although there are several risk prediction tools for patients with CVD incorporating kidney function, to our knowledge, none of them include albuminuria. Moreover, the selection of the kidney function measure (e.g., serum creatinine, creatinine-based estimated GFR, or blood urea nitrogen) in these tools is heterogeneous. In this review, we will summarize these aspects, as well as the burden of CKD in patients with CVD, in the current literature. We will also discuss potential mechanisms linking CKD to secondary events and consider future research directions. Given their clinical and public health importance, for CVD we will focus on 2 representative cardiac diseases: myocardial infarction and heart failure.

Chronic kidney disease (CKD) is defined as reduced glomerular filtration rate (GFR) and/or elevated albuminuria¹ and affects 10–20% of adults worldwide.^2,3 CKD is an independent risk factor for cardiovascular disease (CVD),^3–7 and up to half of individuals with CKD die from CVD.⁸ Consequently, the 2016 European Guidelines on Cardiovascular Disease Prevention incorporated CKD to classify CVD risk in primary prevention.⁹ Specifically, they classified individuals with GFR <30 mL/min/1.73 m² and diabetic patients with proteinuria as ‘very high risk’ (equivalent to 10-year predicted risk of CVD mortality ≥10%) and those with GFR 30–59 mL/min/1.73 m² as ‘high risk’ (equivalent to 10-year predicted risk of CVD mortality 5% to <10%).

In addition to predicting incident CVD, a number of studies have shown CKD as a predictor of poor outcomes in patients with existing CVD (namely, in a secondary prevention setting).^10–50 Indeed, several prediction models for patients with CVD include CKD measures. However, they incorporate different measures of kidney function, such as serum creatinine,^10–28 creatinine-based estimated GFR (eGFR),^28–38 and blood urea nitrogen (BUN),^{25–28,39–41} making it difficult for clinicians to actually utilize information on kidney function for classifying the prognosis of patients with CVD. Moreover, to our knowledge, none of those tools incorporate albuminuria, despite the current recommendation of characterizing CKD with both eGFR and albuminuria¹ and a body of evidence indicating its prognostic value in this clinical population.

In this review, we will mainly summarize the burden of CKD and its prognostic value specifically in patients with CVD. Also, we will discuss potential mechanisms linking CKD to secondary events after CVD and consider future research directions. Given their clinical and public health importance, for CVD we will focus on 2 representative cardiac diseases: myocardial infarction (MI) and heart failure (HF).⁵¹

Burden of CKD in Patients With CVD

As shown in Table 1, previous studies have been substantially heterogeneous in terms of kidney measures of interest, definition of CKD, and study population, making it difficult to estimate the prevalence of CKD among patients with MI or HF. More importantly, only a limited number of studies simultaneously reported both GFR and albuminuria, particularly in MI patients.

Table 1. Prevalence of CKD in Representative Studies of Patients With Cardiovascular Disease

Lead author (year)	n	Region	Study type	Cardiac disease	Definition of CKD*	Prevalence
MI
Normand (1996)25	14,581	USA	Registry	Acute MI	Serum creatinine ≥2 mg/dL	10%
Al Suwaidi (2002)10	22,103	∼30 countries in Europe, America and Oceania	Clinical trial	ACS with STE and NSTE	Creatinine clearance <70 mL/min	72%
Santopinto (2003)13	11,774	14 countries in Europe, America and Oceania	Registry	UAP, STEMI, NSTEMI	Creatinine clearance ≤60 mL/min	36%
Halkin (2005)14	2,082	USA	Clinical trial	Acute MI undergoing PCI	Creatinine clearance <60 mL/min	18%
Lee (2009)15	9,706	South Korea	Registry	Acute MI	Serum creatinine ≥2 mg/dL	10%
Schiele (2009)43	1,211	France	Registry	Acute MI	eGFR <60 mL/min/1.73 m2 or urine albumin ≥20 μg/min	62%
Fox (2010)52	49,491	USA	Registry	STEMI, NSTEMI	eGFR <60 mL/min/1.73 m2 or dialysis	38%
Kim (2010)19	2,148	South Korea	Registry	NSTEMI	Serum creatinine ≥1.5 mg/dL	14%
Nazer (2013)49	3,280	8 countries in Europe, America and Oceania	Clinical trial	UAP, MI	Urine albumin ≥30 μg/mL	19%
Shiraishi (2014)30	1,447	Japan	Registry	Acute MI receiving PCI	eGFR <60 mL/min/1.73 m2	36%
Lau (2015)57	4,778	Australia	Registry	STEMI, NSTE ACS	eGFR <60 mL/min/1.73 m2	26%
Åkerblom (2016)50	9,473	37 countries in Europe, America, Africa, Asia and Oceania	Clinical trial	NSTE ACS	Dipstick proteinuria ≥30 mg/dL	15%
Bohula (2016)32	8,598	28 countries in Europe, America, Africa, Asia and Oceania	Clinical trial	Recent MI	eGFR <60 mL/min/1.73 m2	12%
HF
Adams (2005)56	105,388	USA	Registry	Acute HF (HFpEF, HFrEF)	Serum creatinine >2 mg/dL	20%
Hillege (2006)34	2,680	USA and Canada	Clinical trial	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2	36%
Heywood (2007)53	118,465	USA	Registry	Acute HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2	64%
Anand (2009)46	5,010	16 countries in Europe, America and Oceania	Clinical trial	Chronic HF (HFrEF)	eGFR <60 mL/min/1.73 m2 or dipstick proteinuria ≥1+	61%
Jackson (2009)47	2,310	USA and Canada	Clinical trial	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2 or ACR ≥22 mg/mmol for men and ≥31 mg/mmol for women	54%
Wedel (2009)21	3,342	20 countries in Europe and Africa	Clinical trial	Chronic HF (HFrEF)	eGFR <60 mL/min/1.73 m2	55%
Masson (2010)48	2,131	Italy and Switzerland	Clinical trial	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2 or ACR ≥30 mg/g	50%
Komajda (2011)29	4,128	25 countries, in Europe, America, Africa and Oceania	Clinical trial	Chronic HF (HFpEF)	eGFR <60 mL/min/1.73 m2	31%
Edelmann (2011)54	4,079	Germany	Clinical trial	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2	32%
Miura (2012)44	2,465	Japan	Registry	Chronic HF (HFpEF)	eGFR<60 mL/min/1.73 m2 or dipstick proteinuria ≥1+	58%
Smith (2013)36	24,331	USA	Registry	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2, dipstick proteinuria ≥1+ or dialysis	66%
Senni (2013)22	6,274	5 countries in Europe	Registry	Chronic HF (HFpEF, HFrEF)	Serum creatinine >2 mg/dL	8%
Inohara (2014)37	4,321	Japan	Registry	Acute HF (HFpEF, HFrEF)	eGFR ≤50 mL/min/1.73 m2	50%
Kajimoto (2014)55	4,393	Japan	Registry	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2	71%
Miura (2014)45	2,039	Japan	Registry	Chronic HF (HFpEF)	eGFR <60 mL/min/1.73 m2 or ACR ≥27.4 mg/g	80%
Uszko-Lencer (2017)38	1,811	Germany	Registry	Chronic HF (HFpEF, HFrEF)	eGFR <60 mL/min/1.73 m2	63%

*eGFR values based on CKD-EPI equation are 24.7–28.4 mL/min/1.73 m² for females and 32.8–37.8 mL/min/1.73 m² for males among those who have 2 mg/dL of serum creatinine and aged 50–70 years. ACR, albumin-to-creatinine ratio; ACS, acute coronary syndrome; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HF, heart failure; HFpEF, HF with preserved ejection fraction; HFrEF, HF with reduced ejection fraction; MI, myocardial infarction; NSTE, non-ST-segment elevation; PCI, percutaneous coronary intervention; STE, ST-segment elevation; UAP, unstable angina pectoris.

For MI patients, the most representative US data from the National Cardiovascular Data Registry, by Fox et al in 2010, reported the prevalence of eGFR <60 mL/min/1.73 m² to be 38% (31% in patients with ST-elevation MI [STEMI] and 43% in non-ST-elevation MI [NSTEMI]).⁵² The higher prevalence of reduced kidney function in NSTEMI than in STEMI is partially related to older age in NSTEMI patients.⁵² In a French registry reported by Schiele et al, the prevalence of CKD was 1.7-fold greater when both eGFR and albuminuria were taken into account compared with only eGFR (62% vs. 37%).⁴³ Overall, data from clinical trials tend to have a lower prevalence of CKD than the data from registries, probably reflecting the selected populations in clinical trials.

For patients with HF, Heywood et al (2007) reported the prevalence of eGFR <60 mL/min/1.73 m² to be 64% in patients with acute decompensated HF in a US registry, the Acute Decompensated Heart Failure National Registry (ADHERE).⁵³ The prevalence of eGFR <60 mL/min/1.73 m² tended to be higher in HF with preserved ejection fraction (HFpEF) than in HF with reduced ejection fraction (HFrEF).^36,54,55 A report by Miura et al (2012) using data from a Japanese registry of chronic HF showed the prevalence of eGFR <60 mL/min/1.73 m² and urine albumin-to-creatinine ratio (ACR) ≥∼30 mg/g to be 80%, whereas the prevalence of eGFR <60 mL/min/1.73 m² alone was 45%.⁴⁴

Contrasting these registries, the prevalence of reduced kidney function (e.g., eGFR <60 mL/min/1.73 m²) tended to be higher in patients with HF,^{21,37,38,53,56} compared with patients with MI.^13,30,57 Because MI is a leading cause of subsequent HF,⁵⁸ in general HF patients would be older and have more comorbidities than MI patients.

Taken together, it seems reasonable to consider that approximately 30–40% of MI patients and 50–70% of HF patients would have eGFR <60 mL/min/1.73 m². Importantly, when albuminuria is additionally accounted for, as recommended in the recent international CKD clinical guidelines,¹ the overall prevalence of CKD may reach 60% in MI patients and 80% in HF patients. However, we need more data on simultaneous assessment of eGFR and ACR in MI patients, particularly from Asia.

Effect of CKD on Prognosis Among Patients With CVD

As summarized in Table 2, numerous studies have reported significant associations of CKD measures with prognosis in patients with MI or HF. These studies represent various countries (although data from Asia are again sparse) and have explored a broad range of clinical outcomes such as death, CVD events, and bleeding. Most of the studies explored serum creatinine itself, creatinine clearance, or creatinine-based eGFR, and several studies also demonstrated prognostic values of BUN in patients with MI or HF. Much fewer studies investigated albuminuria, particularly in patients with MI. Two studies (Anand et al⁴⁶ and Miura et al⁴⁴) explored both eGFR and albuminuria in HF patients, but used a semi-quantitative dipstick measurement for albuminuria.

Table 2. Representative Studies Reporting Significant Associations of CKD Measures With Adverse Outcomes Among >1,000 Patients With Cardiac Disease

Lead author (year)	Region	n	Cardiac disease	CKD measures	Outcomes	Follow-up
MI
Normand (1996)25	USA	14,581	Acute MI	BUN, serum creatinine	Mortality	≤1 month
Al Suwaidi (2002)10	∼30 countries in Europe, America and Oceania	22,103	ACS	Creatinine clearance	Mortality	≤1.5 years
Sørensen (2002)11	Denmark	6,252	Acute MI	Creatinine clearance	Mortality	≤6 years
Wright (2002)12	USA	3,106	Acute MI	Creatinine clearance	Mortality	≤5 years
Santopinto (2003)13	14 countries in Europe, America and Oceania	11,774	UAP, STEMI, NSTEMI	Creatinine clearance	Mortality, stroke and major bleeding	In-hospital
Anavekar (2004)31	24 countries in Europe, America, Oceania and Africa	14,527	Acute MI	eGFR	CVD mortality, HF, recurrent MI, cardiac arrest, stroke	Median ∼2 years
Halkin (2005)14	USA	2,082	Acute MI patients undergoing PCI	Creatinine clearance	Mortality	≤1 year
Eikelboom (2006)16	13 countries in Europe, America, Asia and Oceania	34,146	ACS	Serum creatinine	Mortality and major bleeding	≤1 month
Smith (2006)28	USA	44,437	Acute MI	BUN, serum creatinine, eGFR	Mortality	≤1 year
Schiele (2009)43	France	1,211	Acute MI	Urine albumin, serum creatinine	Mortality	≤1 month
Subherwal (2009)18	USA	71,277	NSTEMI	Creatinine clearance	Major bleeding	In-hospital
Kim (2010)19	South Korea	2,148	NSTEMI	Serum creatinine	Mortality	≤1 year
Nazer (2013)49	8 countries in Europe, America and Oceania	3,280	MI and UAP	Urine albumin, eGFR	Mortality, MI, unstable angina, revascularization and stroke	Mean 2 years
Shiraishi (2014)30	Japan	1,447	AMI undergoing PCI	eGFR	Mortality	In-hospital
Åkerblom (2016)50	37 countries in Europe, America, Africa, Asia and Oceania	9,473	NSTE ACS	Dipstick	Mortality, CVD mortality, MI, GUSTO moderate or severe bleeding	≤2 years
Bohula (2016)32	28 countries in Europe, America, Africa, Asia, and Oceania	8,598	Recent MI	eGFR	CVD mortality, recurrent MI, ischemic stroke	≤3 years
HF
Hillege (2000)33	13 countries in Europe	1,702	Chronic HF (HFrEF)	eGFR	Mortality	Median ∼9 months
Lee (2003)26	Canada	2,624	Acute HF (HFpEF, HFrEF)	Serum creatinine	Mortality	≤1 year
Hillege (2006)34	USA and Canada	2,680	Chronic HF (HFpEF, HFrEF)	eGFR	CVD mortality, unplanned admission	Median ∼2 years
Smith (2006)28	USA	56,652	Acute HF	BUN, serum creatinine, eGFR	Mortality	≤1 year
Abraham (2008)20	USA	37,548	Acute HF (HFpEF, HFrEF)	Serum creatinine	Mortality	≤2 months
Anand (2009)46	16 countries in Europe, America and Oceania	5,010	Chronic HF (HFrEF)	Cross-categories of eGFR and dipstick	Mortality, hospitalization for HF, or administration of intravenous inotropic or vasodilator drugs	Mean 2 years
Jackson (2009)47	USA and Canada	2,310	Chronic HF (HFpEF, HFrEF)	ACR, serum creatinine	Mortality, CVD mortality, hospitalization for HF	Median ∼3 years
Wedel (2009)21	20 countries in Europe and Africa	3,342	Chronic HF (HFrEF)	Serum creatinine	CVD mortality, non-fatal MI, non-fatal stroke	Median ∼3 years*
Masson (2010)48	Italy and Switzerland	2,131	Chronic HF (HFpEF, HFrEF)	ACR, serum creatinine	Mortality	Mean 3 years
Komajda (2011)29	25 countries, in Europe, America, Africa and Oceania	4,128	Chronic HF (HFpEF)	eGFR	Mortality, hospitalization for HF, MI, stroke, and ventricular or atrial arrhythmias	≤3 years
Miura (2012)44	Japan	2,465	Chronic HF (HFpEF)	Cross-categories of eGFR and dipstick	Mortality, CVD mortality, non-CVD mortality	Mean 2.5 years
O’Connor (2012)40	USA	2,331	Chronic HF (HFrEF)	BUN	All-cause hospitalization, mortality	Median 2.5 years
Postmus (2012)35	The Netherlands	1,023	Acute HF	eGFR	HF re-hospitalization	Up to 1.5 years
Senni (2013)22	5 countries in Europe	6,274	Chronic HF (HFpEF, HFrEF)	Serum creatinine	Mortality	≤1 year
Smith (2013)36	USA	24,331	Chronic HF (HFpEF, HFrEF)	eGFR and dipstick	Mortality, hospitalization	Median ∼2 years
Inohara (2014)37	Japan	4,321	Acute HF (HFpEF, HFrEF)	eGFR	Mortality	In-hospital
Miura (2014)45	Japan	2,039	Chronic HF (HFpEF)	ACR, eGFR	Mortality, MI, hospitalization for HF, and stroke	Median 3 years
Uszko-Lencer (2017)38	Germany	1,811	Chronic HF (HFpEF, HFrEF)	eGFR	Mortality	≤5 years

*Follow-up time was derived from another CORONA trial study that has been reported.105 BUN, blood urea nitrogen; CVD, cardiovascular disease; GUSTO, Global Utilization of Streptokinase and Tpa for Occluded arteries. Other abbreviations as in Table 1.

One of the largest study from a US national dataset, by Smith et al (2006), uniquely compared the prognostic value of BUN, serum creatinine, and creatinine-based eGFR in patients with MI and those with HF, separately.²⁸ This study observed that levels of BUN, serum creatinine, and eGFR were similarly associated with death among patients with MI, but BUN was most strongly associated with poor prognosis among patients with HF. Such predictive superiority of BUN to creatinine or creatinine-based eGFR in HF patients has also been reported in other studies.^53,59 This may be related to a unique property of BUN potentially reflecting neurohumoral activation, given its absorption is mediated by arginine vasopressin.⁶⁰

Cystatin C has been shown to provide additional prognostic value beyond creatinine-based kidney function in several settings.^61–63 However, data in patients with MI or HF are limited. Nonetheless, a small study by Koenig et al, including approximately 1,000 patients with CVD (only ∼600 MI patients and thus not included in Table 2), reported that only cystatin C, but not serum creatinine or creatinine clearance, was associated with secondary events.⁶⁴

For albuminuria, most studies have been performed in patients with HF, although 3 studies have investigated MI patients.^36,43–50 In general, these studies observed that high albuminuria was associated with adverse outcomes independent of kidney function.^36,43–50 Among MI patients, the largest study was based on data from a clinical trial by Åkerblom et al⁵⁰ and reported that dipstick proteinuria was associated independently with all-cause death but not necessarily with CVD outcomes. Of note, data on the prognostic value of albuminuria in MI patients in Asia are sparse.

Potential Linkage Between CKD and Poor Outcomes in Patients With CVD

There are several pathophysiological mechanisms linking CKD to poor prognosis in both patients with MI and HF. First, patients with advanced CKD are more likely to have comorbidities such as diabetes and atrial fibrillation, which increase the risk of secondary adverse outcomes.^52,65–68 Second, patients with advanced CKD are also known to have severe types of CVD, such as MI with multivessel disease compared with those without advanced CKD.^52,67,68 Third, established complications of CKD, such as anemia, altered calcium-phosphate homeostasis (including mineral bone disorder), and derangements in the coagulation system can impair cardiac function and increase the risk of atherothrombotic events as well.^69–74 Fourth, volume overload as a consequence of kidney dysfunction can result in elevated left ventricular end-diastolic pressure and lead to the manifestation of HF.^72,73 Fifth, several uremic toxins, such as guandines and p-Cresol/ p-cresyl sulfate, are reported to directly damage cardiac function or induce atherosclerosis.⁷⁵ Sixth, inflammation is involved in the progression of atherosclerosis and may also play a role in increasing the risk of CVD.⁷⁶ Finally, urinary albumin excretion is an indicator of microvascular damage and endothelial dysfunction that is directly involved in atherogenesis.^77,78 Importantly, the involvement of microvascular disease in the pathophysiology of HF has been recently suggested.⁷⁹

In addition, we need to keep in mind the potential of suboptimal management of MI and HF in CKD patients. Fox et al reported that MI patients with CKD were less likely to take antiplatelet agents, β-blockers, or statins.⁵² Also, more frequent errors in dosing of medications have been reported in patients with CKD, which would contribute to their poor prognosis.⁵² This treatment disparity may be caused by concerns regarding higher risk of adverse events related to evidence-based therapies (e.g., bleeding risk in the context of antiplatelet or anticoagulation therapy) in patients with CKD than in those without CKD.^52,80–85

To further complicate the issue, some evidence-based therapies may not be as effective in CKD patients as in patients without CKD. SWEDHEART, a Swedish registry, showed that the benefit of invasive therapy in patients with NSTEMI was diminished in patients with severely reduced kidney function.⁸⁶ This may be partially explained by the higher risk of contrast-induced nephropathy in patients with CKD than in those without,^87,88 which can also increase the risk of secondary events. Importantly, patients with CKD are often excluded from clinical trials.⁸⁹ This is true for renin-angiotensin aldosterone inhibitors, which have been effective in MI and HF patients in general,^90–92 but have not been robustly studied in CKD patients. There are concerns of hyperkalemia and acute kidney injury when these drugs are used in CKD patients.^93–95 Thus, future investigations are needed to establish an evidence-base for optimal management of MI and HF in CKD patients.

CKD Measures in Risk Prediction Tools for Patients With MI or HF

Most prediction tools for patients with MI are based on data from North America and Europe and target death as an outcome with a short time frame for risk prediction (≤1 year) (Table 3). Reported risk discrimination (i.e., c-statistic) ranges from 0.63 to 0.83. Regarding predictors, most tools consistly use some combination of demographic factors, clinical comorbidities, and severity of MI. Age is most often included, followed by diabetes and Killip class. Approximately two-thirds of tools have any measures of CKD, and serum creatinine and creatinine clearance are the most commonly used as a measure of kidney function. However, there are no prediction tools for MI patients that include albuminuria. Of note, a small study reported that albuminuria was more predictive than some key predictors such as Killip class and left ventricular ejection fraction (EF).¹⁰⁰

Table 3. Representative Risk Prediction Tools for Patients With MI

Lead author (year)	Region	n	Patient type	Predictors					Outcomes	Prediction time frame	C-statistic
				Demographic	Comorbidities	Severity of MI	Cardiac markers	CKD measures
Normand (1996)25	USA	14,581	Acute MI	Age	Cancer, mobility, BMI, respiratory rate, heart rate, log10 MAP, serum albumin	Shock, S3 gallop rhythm, cardiomegaly, ECG reading, MI on ECG, location of MI, HF, cardiac arrest	–	BUN, serum creatinine	Mortality	1 month	0.81
Jacobs (1999)39	USA	6,134	UAP/Acute MI	Age	MI, stroke, angina, CABG, HTN, Charlson comorbidity index	ECG, shock, HF, cardiac arrest	–	BUN	Mortality	6 years	0.77
Antman (2000)96	10 countries in America and Europe	1,957	UAP/NSTEMI	Age, family history of CAD	HTN, total cholesterol, diabetes, smoking, aspirin	Severe angina symptoms, ST-segment deviation	Creatine kinase MB, troponin	–	Mortality, MI, urgent revascularization	14 days	0.63
Granger (2003)17	13 countries in Europe, America and Oceania	11,389	UAP/STEMI	Age	SBP, heart rate	Killip class, cardiac arrest, ST-segment deviation	Creatine kinase MB, troponin	Serum creatinine	Mortality	In-hospital	0.83
Addala (2004)97	USA	3,252	Acute MI patients undergoing PCI	Age	Heart rate, diabetes	Killip class, location of MI, left bundle branch block	–	–	Mortality	6 months	–
De Luca (2004)98	The Netherlands	1,917	STEMI	Age		Location of MI, Killip class, TIMI flow, ischemic time, multivessel disease, HF	–	–	Mortality	1 month	0.76
Halkin (2005)14	USA	2,082	Acute MI patients undergoing PCI	Age	Anemia	LVEF, Killip class, TIMI flow, multivessel disease	–	Creatinine clearance	Mortality	1 month and 1 year	1 month: 0.81; 1 year: 0.78
Lee (2009)15	South Korea	9,796	Acute MI	Age	BMI, CAD, diabetes, PAD, glucose, total cholesterol	Lethal arrhythmia, Killip class, LVEF, shock, in-hospital resuscitation, mechanical ventilator, intra-aortic balloon pump, drug-eluting stent, multivessel disease, left main CAD	NT-proBNP	Serum creatinine	Mortality, recurrent MI, revascularization	6 months	–
Subherwal (2009)18	USA	71,277	NSTEMI	Sex	Hematocrit, heart rate, PAD/stroke, diabetes, SBP	–	–	Creatinine clearance	In-hospital major bleeding	–	0.72
Kim (2010)19	South Korea	2,148	NSTEMI	–	–	TIMI risk index, Killip class	–	Serum creatinine	Mortality	1 year	0.80
Bohula (2016)32	28 countries in Europe, America, Africa, Asia and Oceania	8,598	MI	Age	HTN, diabetes, stroke, CABG, PAD, smoking	HF	–	eGFR	CVD mortality, recurrent MI, ischemic stroke	3 years	–
Karam (2016)99	France	8,112	STEMI	Age	Diabetes, obesity, respiratory rate	Time from the chest pain onset to the call	–	–	Sudden cardiac arrest	Prehospital	–

BMI, body mass index; CABG, coronary artery bypass graft; CAD, coronary artery disease; ECG, electrocardiogram; HTN, hypertension; MAP, mean arterial pressure; PAD, peripheral artery disease. Other abbreviations as in Tables 1,2.

As with the tools for MI patients, most of the prediction tools for HF patients are derived from North American and European data and also target death as an outcome with a short time frame for risk prediction (≤1 year) (Table 4). Reported risk discrimination (i.e., c-statistic) ranges from 0.70 to 0.87. Regarding predictors, most tools consistly implement some combination of demographic factors, clinical comorbidities, and severity of HF. More specifically, age is most often included, followed by EF, systolic blood pressure, and the New York Heart Association HF functional class. Most tools include CKD measures, and serum creatinine is the most commonly used measure of kidney function, followed by BUN. However, despite a body of evidence for albuminuria predicting adverse outcomes in HF patients (Table 2), to the best of our knowledge, there are no prediction tools for HF patients that include albuminuria.

Table 4. Representative Risk Prediction Tools for Patients With HF

Lead author (year)	Region	n	Patient type	Predictors					Outcomes	Prediction time frame	C-statistic
				Demographic	Comorbidities	Severity of HF	Natriuretic peptide	CKD measures
Lee (2003)26	Canada	2,624	Acute HF (HFpEF, HFrEF)	Age	Respiratory rate, SBP, sodium, stroke, dementia, COPD, hepatic cirrhosis, cancer, hemoglobin	–	–	BUN	Mortality	1 month, 1 year	–
Fonarow (2005)27	USA	33,046	Acute HF (HFpEF, HFrEF)	–	SBP	–	–	BUN, creatinine	Mortality	In-hospital	0.76
Levy (2006)101	USA and Canada	1,125	Chronic HF (HFrEF)	Age, sex	SBP, anti-hypertensive medication, statin, sodium, total cholesterol, hemoglobin, lymphocytes, uric acid	LVEF, NYHA class, ischemic etiology, biventricular pacemaker, implantable cardioverter-defibrillator	–	–	Mortality	1–3 years	0.73
Pocock (2006)102	UK	7,599	Chronic HF (HFpEF, HFrEF)	Age, sex	Diabetes, BMI, DBP	LVEF, NYHA class, cardiomegaly, HF	–	–	Mortality	2 years	0.75
Abraham (2008)20	USA	37,548	Acute HF (HFpEF, HFrEF)	Age	Heart rate, SBP, primary cause of hospitalization	LVEF	–	Serum creatinine	Mortality	2 months	0.75
Wedel (2009)21	20 countries in Europe, Africa	3,342	Chronic HF (HFrEF)	Age, sex	Diabetes, BMI, CABG, AF, ApoA-1, intermittent claudication, heart rate, MI	LVEF, NYHA class	NT-proBNP	Serum creatinine	Mortality, hospitalization for HF	–	0.70
Peterson (2010)41	USA	39,783	Acute HF (HFpEF, HFrEF)	Age, race	SBP, sodium, heart rate, COPD	–	–	BUN	Mortality	In-hospital	–
Komajda (2011)29	25 countries, in Europe, America, Africa and Oceania	4,128	Chronic HF (HFpEF)	Age	Diabetes, neutrophils, COPD, QOL, MI, heart rate	Hospitalization for HF, EF, ischemic etiology	NT-proBNP	eGFR	Mortality, hospitalization for HF, MI, stroke, and ventricular or atrial arrhythmias	3 years	–
O’Connor (2012)40	USA	2,331	Chronic HF (HFrEF)	Sex	–	Cardiopulmonary exercise test, symptom stability	–	BUN	Hospitalization and mortality	1 year	0.73
Postmus (2012)35	The Netherlands	1,023	Acute HF	Age	Stroke, PAD	LVEF	–	eGFR	HF hospitalization	1.5 years	0.73
Senni (2013)22	5 countries in Europe	6,274	Chronic HF (HFpEF, HFrEF)	Age	Diabetes with micro- or macro-angiopathy, anemia, HTN, s-blocker, severe valve heart disease, AF	LVEF, NYHA class	–	Serum creatinine	Mortality	1 year	0.87
Pocock (2013)23	30 countries in Europe, America, Asia, Oceania and Africa	39,372	Chronic HF (HFpEF, HFrEF)	Age, sex	BMI, smoking, SBP, diabetes, COPD, anti-hypertensive medication	LVEF, NYHA class HF duration	–	Serum creatinine	Mortality	3 years	–
Uszko-Lencer (2017)38	Germany	1,811	Chronic HF (HFpEF, HFrEF)	Age	BMI, SBP, heart rate, 6-min walk	NYHA class	NT-proBNP	eGFR	Mortality	5 years	–

AF, atrial fibrillation; COPD, chronic obstructive pulmonary disease; EF, ejection fraction; LV, left ventricular; NYHA class, New York Heart Association heart failure functional class; QOL, quality of life; SBP, systolic blood pressure. Other abbreviations as in Tables 1–3.

Future Directions

Future studies from regions other than North America and Europe are warranted to either validate any existing models or develop region-specific ones incorporating kidney function. It is important that kidney function measures (e.g., serum creatinine) are routinely assessed worldwide during hospitalization and such a study could be planned efficiently. Although a number of studies have explored kidney dysfunction and albuminuria as predictors of adverse outcomes among patients with MI or HF, we definitely need more studies investigating ACR in patients with MI. It would be ideal to simultaneously assess both kidney function and albuminuria in these clinical populations and be reasonable to try to develop prediction models with both CKD measures. Also, efforts may be needed to increase awareness of the clinical importance of albuminuria among healthcare providers managing patients with MI or HF. Importantly, the assessment of albuminuria is already recommended in several clinical populations such as diabetes and hypertension,^103,104 and thus data on albuminuria may be readily available in many patients with MI or HF.

Summary

Reduced kidney function is highly prevalent in patients with MI or HF and is a potent predictor of poor prognosis in these clinical populations. Despite the international recommendation for characterizing CKD by measuring both GFR and albuminuria,¹ data on albuminuria are still limited, warranting future investigations of the burden and prognostic effect of albuminuria in patients with cardiac disease (particularly MI). Healthcare providers should pay clinical attention to not only reduced kidney function but also albuminuria (particularly when information on albuminuria is already available) in patients with MI or HF.

Disclosures

K.M. reports a grant from Kyowa Hakko Kirin outside the submitted work.

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