Objective Heart failure (HF) imposes a substantial burden and the prevalence of HF is high in patients with chronic kidney disease (CKD). HF results in multiple hospital admissions, but whether HF subtypes worsen long-term outcomes and renal function in patients with CKD remains inconclusive.
Methods The study comprised 10 904 patients with CKD aged ≥20 years who underwent echocardiography between 1 January 2011 and 31 December 2018. The patients were stratiﬁed into four groups: non-HF, HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and HF with preserved ejection fraction (HFpEF). The primary end points were all-cause mortality, major adverse cardiovascular events (MACEs) and adverse renal outcomes.
Results In inverse probability of treatment weighting-adjusted method, the risk of all-cause mortality and MACEs relative to the non-HF group was greatest in the HFrEF group (HR 3.18 (95% CI 2.57 to 3.93) and HR 3.83 (95% CI 3.20 to 4.59)), followed by the HFmrEF (HR 2.75 (95% CI 2.22 to 3.42) and HR 3.08 (95% CI 2.57 to 3.69)) and HFpEF (HR 1.85 (95% CI 1.59 to 2.15) and HR 2.43 (95% CI 2.16 to 2.73) groups. In addition, the HFrEF group had the greatest risks of end-stage renal disease (HR 2.58 (95% CI 1.94 to 3.44)) compared with other groups.
Conclusions HF is associated with subsequent worse clinical outcomes, which may be more pronounced in patients with HFrEF, followed by those with HFmrEF and those with HFpEF relative to non-HF group.
- heart failure, systolic
- heart failure, diastolic
Data availability statement
Data are available on reasonable request.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
What is already known on this topic?
Heart failure (HF) is highly prevalent in patients with chronic kidney disease (CKD), and it is strongly associated with adverse outcomes.
Although differences exist among different HF subtypes in cardiac remodelling and associated outcomes, the relationship between HF subtypes, diastolic dysfunction and the risks of long-term outcomes has never been explored.
What this study adds?
Our study included 10 904 patients with CKD who had undergone transthoracic echocardiography.
The risks of all-cause mortality, major adverse cardiovascular events (MACEs) and end-stage renal disease (ESRD) were 3.18-fold, 3.83-fold and 2.58-fold higher in HF with reduced ejection fraction group compared with non-HF group.
Furthermore, risks of all-cause mortality, MACEs and ESRD were 3.33-fold, 3.21-fold and 2.76-fold higher in grade 3 diastolic dysfunction compared with non-HF group.
How this study might affect research, practice or policy?
Based on the results from our study, implementation of HF screening coupled with early diagnosis are crucial for these patients.
Chronic kidney disease (CKD) is recognised as a worldwide health burden, causing an estimated 850 000 deaths per year and affecting an estimated 17% of the adult population in the USA.1 Left ventricular (LV) structural and functional abnormalities are common in patients with CKD, and 30%–60% of patients with CKD experience heart failure (HF) with preserved or reduced ejection fractions.2 The associations between CKD and HF are often complicated by bidirectional causal relationships.
Myocardial hypertrophy caused by hypertension and underlying comorbidities in patients with CKD leads to a mismatch between the myocardial oxygen supply and demand, resulting in myocardial ischaemia.3 Myocardial ischaemia has a detrimental effect on myocardial cell survival, promoting the accumulation of extracellular matrix and collagen and myocardial fibrosis, which, in turn, increases the LV filling pressure, impairs diastolic filling and causes heart dysfunction in patients with CKD.4 HF reduces the renal blood flow and causes renal hypoperfusion, leading to an ineffective circulating volume and the activation of the renin-angiotensin system, which, in turn, increases sodium retention and decreases the effects of endogenous vasodilators, mainly nitric oxide and natriuretic peptides.5 In addition, coexisting comorbidities and renal dysfunction may share traditional cardiovascular risk factors, such as diabetes mellitus, hypertension and smoking, and multiple comorbidities may cause major adverse cardiovascular events (MACEs) and adverse renal outcomes in patients with CKD and HF.6 Cross-sectional studies have shown that patients with HF have impaired renal function, but long-term follow-up data are still limited.7
According to 2021 Universal Definition and Classification of Heart Failure,8 HF is reclassified into three subgroups: HF with reduced EF (HFrEF; left ventricular ejection fraction (LVEF) <40%), HF with mildly reduced ejection fraction EF (HFmrEF; LVEF 41%–49%) and HF with preserved EF (HFpEF; LVEF >50%). The HFmrEF subtype was described as an intermediate group between patients with HFrEF and patients with HFpEF. The clinical presentations of HFmrEF are more like those of HFrEF, but HFmrEF may have a better clinical prognosis than those with HFrEF. HFmrEF and HFpEF are also heterogeneous in their presentation and pathophysiology, which influence their prognosis and treatment.9 However, long-term clinical outcomes in patients with CKD based on the HF subtypes according to the echocardiographic findings remain unknown.
To fill this gap in knowledge, we explored the risks of all-cause mortality, MACEs, renal adverse outcomes and kidney function decline by using a large-scale CKD cohort study. This study used the echocardiography data to discuss the potential different prognoses between HFrEF, HFmrEF, HFpEF and non-HF in patients with CKD.
This comprehensive patient data were extracted from the Big Data Center of Taipei Veterans General Hospital, which includes medical records, prescription order, pharmacy use, laboratory tests and examination echocardiogram parameters from all inpatient, outpatient and emergency services.10 The study cohort consisted of patients who were diagnosed with CKD between 1 January 2011 and 31 December 2018, according to International Classification of Diseases diagnostic codes (ICD codes) 581–583, 585–589, N00–N08, N18–N19 and N25–N27. In our study, CKD stage 1 and 2 were identified by the ICD codes, urine albumin-to-creatinine ratio >30 mg/g and/or urine protein-to-creatinine ratio >150 mg/g. CKD categories 3–5 were identified based on estimated glomerular filtration rate (eGFR) and/or ICD codes.11 We excluded patients aged <20 years, those who had received renal replacement therapy (haemodialysis, peritoneal dialysis or kidney transplantation) prior to enrolment and patients who did not undergo echocardiography.
The demographic characteristics included in the analysis were age and sex. The presence of underlying comorbidities, such as hypertension, diabetes mellitus, coronary artery disease and malignancy, medications prescribed, such as calcium channel blockers, beta-blockers, renin-angiotensin-aldosterone system inhibitors, statins, oral hypoglycaemic agents and insulin, were recorded. Laboratory data extracted from the patients’ medical records were the glycated haemoglobin concentrations, eGFR, the spot urine protein-to-creatinine ratio, spot urine albumin-to-creatinine ratio and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. eGFRs were calculated using the Chronic Kidney Disease Epidemiology Collaboration equation.12
The transthoracic echocardiographic parameters in M-mode, two-dimensional and Doppler images were analysed and read by two sonographers. The LV volumes and LVEF were traced manually at end-diastole and end-systole at four-chamber and two-chamber view using the modified biplane Simpson’s method.13 Other echocardiographic variables included aortic root diameter, left atrial diameter, left atrial volume, end-systolic and end-diastolic LV internal diameter, interventricular septal diameter end-diastolic LV posterior wall thickness, end-systolic and end-diastolic volume, mitral E-wave velocity, mitral A-wave velocity, mitral E/A ratio, medial and lateral E/e′ ratio and average E/e′ ratio (online supplemental table 1).
Different HF subtypes based on the parameters of echocardiography
The HF subtype in patients with CKD were divided into four groups based on the LVEF and evidence of increased LV filling pressure: non-HF, HFrEF (LVEF <40%), HFmrEF (LVEF 41%–49%) and HFpEF groups (LVEF >50%). The evidence of increased LV filling pressure included elevated natriuretic peptide (NT-proBNP >125 pg/mL in ambulatory patients and >300 pg/mL in hospitalised/decompensated patients), non-invasive echocardiographic measurements (average E/e′ >14, septal e′ <7, lateral e′ <10, tricuspid regurgitation velocity >2.8 m/s or left atrial volume index >34 mL/m2) and/or invasive haemodynamic parameters (pulmonary capillary wedge pressure or LV end-diastolic pressure >15 mm Hg).14 Diastolic dysfunction was further examined based on the 2016 American Society of Echocardiography (ASE)/European Association of Cardiovascular Imaging (EACVI) guidelines.15 The grade of diastolic dysfunction was further classified into grade 1 (E/A <0.8), grade 2 (E/A 0.8–2) and grade 3 (E/A >2).
Outcomes of interest
The outcomes of interest were all-cause mortality, MACEs (defined as a composite of non-fatal stroke, non-fatal myocardial infarction and hospitalisation for HF), ischaemic stroke, myocardial infarction and hospitalisation for HF. The adverse renal outcomes examined were eGFR decline ≥30% and end-stage renal disease (ESRD, defined as eGFR <15 mL/min/1.73 m2, chronic dialysis or renal transplantation).
Baseline characteristics were presented as medians with IQRs for continuous variables, and percentages for categorical variables. Inverse probability of treatment weighting (IPTW) was used to minimise covariate imbalance among the non-HF, HFpEF, HFmrEF and HFrEF groups.16 17 The detailed description of the missing values handling and IPTW methods are shown in online supplemental methods. We evaluated the balance among non-HF and HF subtypes by comparing standardised mean differences of baseline covariates, and a baseline characteristic was considered balanced if the maximum standardised mean difference was <0.1. All analyses were performed using SAS (V.9.4; SAS Institute, Cary, North Carolina, USA) and R (V.3.5.2 for Windows; R Foundation for Statistical Computing, Vienna, Austria). P values <0.05 were considered statistically significant.
Patient and public involvement
Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Study population and baseline characteristics
We identified 10 904 patients with CKD who had undergone echocardiography during the study period. The median age was 75.1 (IQR 62.6–84.6) years and male predominant. Table 1 shows the baseline characteristics of all patients, non-HF, HFpEF, HFmrEF and HFrEF groups before and after IPTW matching. The detailed NT-proBNP levels, New York Heart Association Functional Classification and parameters of echocardiography among patients with CKD with different HF subtype groups are shown in online supplemental table 1. After IPTW matching, the study groups had more balanced characteristics (online supplemental figure 1).
Risks of all-cause mortality and MACEs among patients with CKD with different HF subtypes
During the study period, there were 633 (16.8%) patients in the HFpEF group, 189 (24.2%) patients in the HFmrEF group and 237 (25.3%) patients in the HFrEF group who died. In IPTW-adjusted methods, compared with the non-HF group, the risk of all-cause mortality was greatest in the HFrEF group (HR 3.18; 95% CI 2.57 to 3.93; p<0.001), followed by the HFmrEF group (HR 2.75; 95% CI 2.22 to 3.42; p<0.001) and the HFpEF group (HR 1.85; 95% CI 1.59 to 2.15; p<0.001; table 2). The risk of MACEs was also highest in the HFrEF group (HR 3.83; 95% CI 3.20 to 4.59; p<0.001), followed by the HFmrEF group (HR 3.08; 95% CI 2.57 to 3.69; p<0.001) and the HFpEF group (HR 2.43; 95% CI 2.16 to 2.73; p<0.001), compared with the non-HF group. The risks of myocardial infarction and hospitalisation for HF were significantly highest in the HFrEF (HR 3.12; 95% CI 2.08 to 4.69; p<0.001 and HR 5.56; 95% CI 4.48 to 6.90; p<0.001) followed by the HFmrEF group (HR 2.09; 95% CI 1.26 to 3.46; p=0.004 and HR 4.31; 95% CI 3.46 to 5.36; p<0.001) and the HFpEF group (HR 1.53; 95% CI 1.10 to 2.13; p=0.013 and HR 3.44; 95% CI 2.94 to 4.01; p<0.001) compared with the non-HF group. However, the risks of ischaemic stroke showed no significant difference between four groups.
Risks of eGFR decline >30% and ESRD among patients with CKD with different HF subtypes
Compared with the non-HF group, the risk of eGFR decline >30% was greatest in the HFrEF group (HR 2.56; 95% CI 1.85 to 3.56; p<0.001), followed by the HFmrEF group (HR 2.03; 95% CI 1.38 to 3.00; p<0.001) and the HFpEF group (HR 1.62; 95% CI 1.28 to 2.04; p<0.001) compared with the non-HF group (table 2). The risk of ESRD was also greatest in the HFrEF group (HR 2.58; 95% CI 1.94 to 3.44; p<0.001), followed by HFmrEF group (HR 2.23; 95% CI 1.63 to 3.05; p<0.001) and the HFpEF group (HR 1.86; 95% CI 1.52 to 2.27; p<0.001), compared with the non-HF group. The HFrEF had higher rates of eGFR decline compared with those with HFmrEF and HFpEF. The annual eGFR declines were −5.54 mL/min/1.73 m2/year in HFrEF group, −5.02 mL/min/1.73 m2/year in HFmrEF group, −4.47 mL/min/1.73 m2/year in HFpEF group and −3.83 mL/min/1.73 m2/year in non-HF CKD group.
Kaplan-Meier curves for all-cause mortality, MACEs, hospitalisation for HF and ESRD for the four study groups are provided in figure 1. Subgroup analyses produced results similar to those of the main analyses in HFrEF versus non-HF group (online supplemental figures 2–5), HFmrEF versus non-HF group (online supplemental figures 6–9) and HFpEF versus non-HF group (online supplemental figures 10–13).
Risk factors for all-cause mortality, MACEs and adverse renal outcomes in HFpEF
In HFpEF group, older age, male gender, higher CKD stages and hypertension were associated with higher risks of all-cause mortality, MACEs and ESRD (online supplemental table 2). However, diabetes mellitus, use of RAASi or beta-blockers had no significant effects on long-term clinical outcomes in HFpEF.
Grade of diastolic dysfunction among patients with CKD
Grade 3 diastolic dysfunction group was associated with highest risks of all-cause mortality (HR 3.33; 95% CI 1.92 to 5.77; p<0.001), MACEs (HR 3.21; 95% CI 2.07 to 4.98; p<0.001), hospitalisation for HF (HR 4.74; 95% CI 2.94 to 7.65; p<0.001) and myocardial infarction (HR 3.29; 95% CI 1.37 to 7.91; p=0.008) when compared with grade 1 and 2 diastolic dysfunction groups and non-HF group (table 3). Grade 3 diastolic dysfunction group was still at greatest risks of eGFR decline >30% (HR 3.22; 95% CI 1.57 to 6.63; p=0.001) and ESRD (HR 2.76; 95% CI 1.40 to 5.43; p=0.003) when compared with grade 1 and 2 diastolic dysfunction groups and non-HF groups.
Risk matrices for all-cause mortality, MACEs and ESRD demonstrate HRs in different CKD stage stratified by LVEF and diastolic dysfunction
The risk matrices demonstrated the risks of all-cause mortality, MACEs and ESRD combining CKD stage and LVEF stratification using patients with CKD stages 1 and 2 and LVEFs >50% as the reference groups (figure 2A). In all stages of CKD, patients with LVEFs <40% had the highest risks for all-cause mortality, MACEs and ESRD compared with those with LVEFs between 40% and 50% and LVEFs >50%. Moreover, the risks of all-cause mortality, MACEs and ESRD were highest in patients with grade 3 diastolic dysfunction compared with those with other grades of diastolic dysfunction in all CKD stages (figure 2B). The risks associated with CKD and diastolic dysfunction on long-term outcomes appeared to be higher than those associated with CKD and LVEF stratification.
The detailed study design and key findings are summarised in figure 3. In our study, HFrEF group has the highest risk of MACE when compared with non-HF group (HR 3.83), followed by HFmrEF (HR 3.08) and then HFpEF (HR 2.43). In addition, the HFrEF group has the highest risk of decline in eGFR >30% and ESRD compared with the non-HF group (HR 2.56 and 2.58), followed by HFmrEF (HR 2.03 and 2.23) and then HFpEF (HR 1.62 and 1.86). Furthermore, diastolic dysfunction, which occurs during the diastolic phase, increased these risks of MACEs and ESRD, but to a greatest extent in diastolic dysfunction grade 3 (HR 3.21 and 2.76) compared with those without HF.
In the Framingham Heart Study,18 the mortality rate ranged from 20% to 60% after diagnosis of HF in the US population, and the Rotterdam study19 reported that the mortality rate ranged from 11% to 40% in the European population. The Third National Health and Nutrition Examination Study including the US general population aged 18–64 years found that 27.58% of participants with renal dysfunction had HF,20 and other study suggested that about 30%–60% of patients with CKD have HF.2 21 Consistent with previous studies, our study found about 50.3% of patients with CKD had HF, and the mortality rate among patients with CKD with HF ranged from 16.8% in HFpEF group to 25.3% in HFrEF group.
Clinical-epidemiological studies have shown that patients with HFmrEF had different clinical characteristics and may be intermediate between the those with HFrEF or HFpEF.22 In the meta-analysis of 12 observational studies with 109 257 patients, all-cause mortality and hospitalisation for HF were lower in patients with HFmrEF than in those with HFrEF and HFpEF.23 However, the study population was heterogeneous, and only five studies provided outcomes of cardiovascular death or hospitalisation for HF. Therefore, the results may be inconclusive and should be interpreted cautiously. In contrast, a cohort study of 42 987 patients with ischaemic heart disease from the Swedish Heart Failure Registry found that ischaemic heart disease was associated with an increased risk of all other outcomes except non-significant changes in all-cause mortality in HFpEF.24 Our study focusing on the long-term clinical outcomes in CKD populations, who are well known cardiovascular risk populations, found that the risks of all-cause mortality and MACEs still increased as LVEF decreased. The risk of all-cause mortality was 3.18 times higher in the HFrEF group, followed by 2.75 times greater risks in HFmrEF and 1.85 times greater risks in the HFpEF group compared with non-HF group.
Animal models of renal congestion found HF with reduced ejection fraction leads to volume overload and increased intra-abdominal pressure may cause venous congestion and subsequent tubular injury.25 In addition, excessive reactive oxygen species production and endothelial dysfunction in HF promote profibrotic pathways, interstitial fibrosis and renal function decline.26 Previous clinical studies found that CKD is common in patients with HF, and a large meta-analysis from 57 studies including 1 076 104 patients found that about 32% of patients with HF suffered from CKD.27 However, most previous studies were limited by cross-sectional design, preventing the thorough investigation of clinically important long-term renal outcomes. In the present study, HFrEF, HFmrEF and HFpEF groups were associated with eGFR decline >30% and ESRD, but HFrEF group carried the greatest risk.
Diastolic dysfunction is characterised by reduced ventricular compliance and elevated filling pressure of the left ventricle during diastole, and the risk of diastolic dysfunction increases with the presence of comorbid conditions such as hypertension and diabetes.28 29 Since the diseases associated with diastolic dysfunction are risk factors for CKD, and therefore diastolic dysfunction are still common in patients with CKD.30 In spite of a better prognosis than systolic dysfunction, diastolic dysfunction has an annual mortality rate of about 10%.30 Limited data exist on diastolic dysfunction and long-term renal dysfunction. In the present study, we found that diastolic dysfunction was also associated with future risks of MACEs and renal function decline in patients with CKD, and these risks are greatest in patients with CKD with grade 3 diastolic dysfunction relative to other groups. Our findings suggest the existence of detrimental the interplay between worsening HF and worsening renal function in patients with either HF subtypes or diastolic dysfunction.
The primary strength of this study is the evaluation of cardiac function and associated longitudinal risks of a large cohort of patients with CKD who underwent echocardiography. However, this study has some limitations. First, we cannot rule out the possibility of variable imbalance among study groups. To minimise such bias, we performed IPTW-based analyses to balance the distribution of clinical variables. Second, patients who did not undergo echocardiography were excluded from this study, meaning that our findings may be generalisable only to patients with CKD for whom measures of cardiac function are available. In addition, the study only included patients with CKD who underwent echocardiography, and therefore, selection bias may have been present. Finally, although we analysed consecutive eGFR measurements, these measurements were not performed at the same intervals in all patients. However, this situation may be representative of real-world practice.
In conclusion, our data suggest that patients with CKD with HFrEF have worse outcomes than do those with other systolic dysfunction, but outcomes in those with HFmrEF and HFpEF remain worse than those with non-HF. In addition, the diastolic dysfunction in patients with CKD may still have worse prognostic value for patients with CKD.
Data availability statement
Data are available on reasonable request.
Patient consent for publication
The study was approved by the institutional review board of Taipei Veterans General Hospital (2017-09-002BC). Informed consent was waived due to the de-identified data that were analysed.
Twitter @email@example.com, @ChienYiHsu
C-YH and D-CT contributed equally.
Contributors Conception and study design: S-MO, C-JC, M-TT, C-YH and D-CT. Data acquisition: S-MO, M-TT, K-HL, W-CT and D-CT. Data analysis and interpretation: S-MO, C-JC, M-TT, K-HL, W-CT, P-JB, Y-PL, C-YH and D-CT. Statistical analysis: S-MO, P-JB, C-YH and D-CT. Drafting of the manuscript: S-MO, C-JC, C-YH and D-CT. Guarantors: S-MO, C-YH and D-CT.
Funding This work was supported in part by the Ministry of Science and Technology, Taiwan (MOST 106-2314-B-010-039-MY3, MOST 107-2314-B-075-052, MOST 108-2314-B-075-008, MOST 109-2314-B-075-067-MY3, MOST 109-2320-B-075-006, MOST 109-2314-B-075-097-MY3, MOST 110-2312-B-075-002, MOST 110-2634-F-A49-005, MOST 110-2320-B-075-004-MY3, MOST 110-2314-B-038-131); Taiwan Society of Cardiology (TSOC 107-0505); Taipei Medical University and Taipei Medical University Hospital (109TMU-TMUH-16, 110TMU-TMUH-14, 111TMUH-MOST-21); Taipei Veterans General Hospital (V107B-027, V108B-023, V108C-103, V108D42-004-MY3-2, V109B-022, V109C-114, V109D50-001-MY3-1, V109D50-001-MY3-2, V109D50-001-MY3-3, V109D50-002-MY3-3, V109E-008-5(110), V110C-152, V110E-003-2, V111E-002-3, V111C-171, V111C-151, V111D60-004-MY3-1); Taipei Veterans General Hospital-National Yang-Ming University Excellent Physician Scientists Cultivation Programme (No. 104-V-B-044), Taipei, Taichung, Kaohsiung Veterans General Hospital, Tri-Service General Hospital, Academia Sinica Joint Research Programme (VTA110-V1-3-1) and Foundation for Poison Control (FPC-109-002).
Disclaimer The funders did not play any role in the study design, data collection or analysis, decision to publish or preparation of the manuscript.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.