Saif Altaie1, Wissam Khalife2. 1. Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX, USA. 2. Transplant and Left Ventricular Assist Device Programs, Department of Cardiology, University of Texas Medical Branch, Galveston, TX, USA.
Abstract
AIMS: Mid-range ejection fraction is a new entity of heart failure (HF) with undetermined prognosis till now. In our systematic review and meta-analysis, we assess the mortality and hospitalization rates in mid-range ejection fraction HF (HFmrEF) and compare them with those of reduced ejection fraction heart failure (HFrEF) and preserved ejection fraction HF (HFpEF). METHODS AND RESULTS: We conducted our search in March 2018 in the following databases for relevant articles: PubMed, CENTRAL, Google Scholar, Web of Science, Scopus, NYAM, SIEGLE, GHL, VHL, and POPLINE. Our primary endpoint was assessing all-cause mortality and all-cause hospital re-admission rates in HFmrEF in comparison with HFrEF and HFpEF. Secondary endpoints were the possible causes of death and hospital re-admission. Twenty-five articles were included in our meta-analysis with a total of 606 762 adult cardiac patients. Our meta-analysis showed that HFmrEF had a lower rate of all-cause death than had HFrEF [relative risk (RR), 0.9; 95% confidence interval (CI), 0.85-0.94]. HFpEF showed a higher rate of cardiac mortality than did HFmrEF (RR, 1.09; 95% CI, 1.02-1.16). Also, HFrEF had a higher rate of non-cardiac mortality than had HFmrEF (RR, 1.31; 95% CI, 1.22-1.41). CONCLUSIONS: We detected a significant difference between HFrEF and HFmrEF regarding all-cause death, and non-cardiac death, while HFpEF differed significantly from HFmrEF regarding cardiac death.
AIMS: Mid-range ejection fraction is a new entity of heart failure (HF) with undetermined prognosis till now. In our systematic review and meta-analysis, we assess the mortality and hospitalization rates in mid-range ejection fraction HF (HFmrEF) and compare them with those of reduced ejection fraction heart failure (HFrEF) and preserved ejection fraction HF (HFpEF). METHODS AND RESULTS: We conducted our search in March 2018 in the following databases for relevant articles: PubMed, CENTRAL, Google Scholar, Web of Science, Scopus, NYAM, SIEGLE, GHL, VHL, and POPLINE. Our primary endpoint was assessing all-cause mortality and all-cause hospital re-admission rates in HFmrEF in comparison with HFrEF and HFpEF. Secondary endpoints were the possible causes of death and hospital re-admission. Twenty-five articles were included in our meta-analysis with a total of 606 762 adult cardiac patients. Our meta-analysis showed that HFmrEF had a lower rate of all-cause death than had HFrEF [relative risk (RR), 0.9; 95% confidence interval (CI), 0.85-0.94]. HFpEF showed a higher rate of cardiac mortality than did HFmrEF (RR, 1.09; 95% CI, 1.02-1.16). Also, HFrEF had a higher rate of non-cardiac mortality than had HFmrEF (RR, 1.31; 95% CI, 1.22-1.41). CONCLUSIONS: We detected a significant difference between HFrEF and HFmrEF regarding all-cause death, and non-cardiac death, while HFpEF differed significantly from HFmrEF regarding cardiac death.
Left ventricular ejection fraction (LVEF) has long been used in the stratification of patients with HF, although it is not an ideal parameter owing to its relative subjectivity. The lack of evidence supporting the use of other parameters such as myocardial deformation imaging made LVEF widely accepted for stratifying HF patients.1Considering LVEF, there are three types of heart failure (HF); the largest is the reduced ejection fraction (HFrEF) (EF < 40%), which is widely distributed, and the smallest is the preserved ejection fraction (HFpEF) (EF > 50%).2 Although HFpEF was considered in the literature only two decades ago, it proved that almost half of HF patients fall in this category with an expected rise in the future.3 Between these two types, there is the mid‐range ejection fraction (HFmrEF) (EF 40–49%), which is considered as a grey zone according to the European Society of Cardiology guidelines.2, 4Although few studies described HFmrEF prevalence in comparison with that of other HF types, HFmrEF proved to have intermediate clinical picture, haemodynamics, laboratory findings, and echocardiographic data between the other two types.1, 5, 6, 7In 2017 and depending on a registry report, the mortality rates of HFmrEF, HFrEF, and HFpEF were reported8; however, a stronger evidence is needed to estimate the rate difference.In our meta‐analysis, we measured all‐cause mortality, cardiac mortality, non‐cardiac mortality, all‐cause hospitalization, and HF‐related hospitalization in HFmrEF in comparison with HFrEF and HFpEF to better understand the differences between the three subgroups and to determine the features of HFmrEF.
Methods
The study is written according to the guidelines and recommendations in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‐Analyses) statement.9 No published protocol for this systematic review and meta‐analysis exists.
Literature search strategy
We conducted a systematic search in PubMed, CENTRAL, Google Scholar, Web of Science, Scopus, NYAM, SIEGLE, GHL, VHL, and POPLINE using the terms mid‐range ejection fraction heart failure, mid‐range ejection fraction heart failure, borderline ejection fraction heart failure, HFmrEF, prognosis, mortality, death, and re‐admission. We conducted this search in December 2017, and it was updated in March 2018.
Study selection
Studies were eligible if (i) they aimed at defining the prognosis of HFmrEF in terms of mortality and hospitalization, (ii) they included patients (adult men or women) aged >18 years old with no restriction to the date of publication, and (iii) the studies defined HF subtypes according to the European Society of Cardiology guidelines (HFrEF as <40%, HFmrEF as 40–49%, and HFpEF as ≥50%).2, 4 We did not include studies not restricting to this guideline for fear of data overlap between the HF subtypes.Reviews, comments, duplicated publications, non‐English articles, articles with unreliable data extraction, and pooling analyses of original studies were excluded. After including the eligible articles, we manually searched the reference lists of these studies for relevant articles.
Data extraction and quality assessment
The following data were extracted: (i) study characteristics like study title, year of publication, study design, country of study, inclusion criteria of the patients, total sample size, number of patients in each category of HF, their ages, and their gender male percentage; and (ii) criteria of the study outcomes like all‐cause mortality, cardiac mortality, non‐cardiac mortality, all‐cause hospitalization, and HF‐related hospitalization.The methodological quality of included studies was appraised using National Institutes of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross‐Sectional Studies.10 The score consists of 14 questions covering the assessment of the study methodology. A study was given one or zero points according to its fulfilment of the conditions. The total score was 14 points, and a study with a score ≥ 10 points was considered of high quality.
Statistical analysis
The study measures included all‐cause mortality, cardiac mortality, non‐cardiac mortality, all‐cause hospitalization, and HF‐related hospitalization.All statistical analyses were performed with the REVMAN software (version 5.3; Cochrane Collaboration, Oxford, UK). The Mantel–Haenszel method was used to calculate estimates, confidence intervals (CIs), and P values. Statistical heterogeneity was tested with the I
2 statistic, with I
2 ≤ 50% indicating no significant heterogeneity.11 In case of significant heterogeneity, a random effect model was used, while a fixed effect model was used in case of no significant heterogeneity. Relative risk (RR) was calculated from raw published study data, and all outcomes were reported with a 95% CI. For the χ
2 test, a P value < 0.05 was considered statistically significant.
Results
Search results
As shown in Figure
, we identified 299 records in the preliminary search. After scanning the titles or abstracts and removing the duplicates, we excluded 238 articles. The remaining 61 publications underwent full‐text screening, of which 42 failed to meet the inclusion criteria and were removed. On data extraction, 23 articles were excluded. On manual searching of the reference lists of the remaining 19 articles, we found another six articles to include. Finally, 25 articles were included in the final data analysis.3, 8, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34
Figure 1
Flow chart showing the number of included papers after literature search, title/abstract screening, full text screening, data extraction, and final data analysis.
Flow chart showing the number of included papers after literature search, title/abstract screening, full text screening, data extraction, and final data analysis.
Study characteristics
As shown in Table
1, the set of eligible studies consists of 10 prospective cohort studies and 15 retrospective studies with a total of 606 762 patients. The included studies were published from 2001 to 2018. The period of follow‐up ranged from 1 month to 5 years, and the most common adjusted variables were age and sex. Regarding the quality of the studies, the NIH scores ranged from 9 to 13 with a mean of 11.2, suggesting the presence of high methodological quality.
Table 1
Study characteristics and the patient characteristics in the included studies
Study
Publication year
Patients' country
Design
Total sample size
HFrEF
HFmrEF
HFpEF
Number
Age (years)
% men
Number
Age (years)
% men
Number
Age (years)
% men
Lam et al.
2018
New Zealand and Singapore
Prospective cohort
2039
1209
62.1 ± 13.2
83
256
65.8 ± 12.7
69
574
71.5 ± 11.8
52
Hamatani et al.
2018
Japan
Retrospective cohort
1792
860
—
—
318
—
—
614
—
—
Guisado‐Espartero et al.
2018
Spain
Prospective cohort
2735
808
79 (72–84)
62
281
80 (74–84)
58
1664
81 (76–86)
37
Vedin et al.
2017
Sweden
Retrospective cohort
42 789
23 805
—
70
9225
—
64
9957
—
45
Shah et al.
2017
USA
Retrospective cohort
39 982
18 398
79 (73–85)
59
3285
81 (74–86)
49
18 299
82 (75–87)
33
Rickenbacher et al.
2017
Switzerland
Retrospective cohort
622
402
75.5 ± 7.5
67
108
79 ± 6.8
53
112
80.2 ± 7.1
35
Pascual‐Figal et al.
2017
Spain
Retrospective cohort
3446
2351
64.4 ± 12.3
76.8
460
66.7 ± 12.1
73
635
72.1 ± 12.2
42.8
Margolis et al.
2017
Israel
Prospective cohort
2243
215
67 ± 15
78
858
62 ± 13
79
1013
60 ± 12
81
Choi et al.
2018
Korea
Prospective cohort
5625
3182
—
—
875
—
—
1357
—
—
Koh et al.
2017
Sweden
Retrospective cohort
42 061
23 402
72 ± 12
71
9019
74 ± 12
60
9640
77 ± 11
45
Gomez‐Otero et al.
2017
Spain
Retrospective cohort
1420
583
68.2 ± 12.8
76.7
227
72.5 ± 11.1
67
610
75 ± 10.7
46.7
Farré et al.
2017
Spain
Prospective cohort
3580
2232
66.2 ± 12.5
75.7
504
68.1 ± 12.9
66.9
844
73.5 ± 11.4
44
Delepaul et al.
2017
France
Prospective cohort
482
258
66 ± 12
72
115
69 ± 13
72
109
71 ± 12
55
Chioncel et al.
2017
22 countries
Prospective cohort
9134
5460
64 ± 12.6
78
2212
64.2 ± 14.2
68.5
1462
68.6 ± 13.7
52
Bonsu et al.
2017
Ghana
Prospective cohort
1488
354
58.9 ± 14.2
48.1
265
60.4 ± 12.7
50.2
878
60.8 ± 14.6
43.3
Bhambhani et al.
2017
USA
Prospective cohort
28 820
1084
70 ± 10
64
200
72 ± 8
52
811
71 ± 9
41
Coles et al.
2015
USA
Retrospective cohort
4025
940
71.4
60
364
74.4
45.1
1476
75.7
33
Coles et al.
2014
USA
Retrospective cohort
3604
1479
73.7 ± 12.8
56.5
346
76.1 ± 11.4
45.4
1779
76.5 ± 11.9
33.4
Cheng et al.
2014
USA
Retrospective cohort
40 239
15 716
79 (72–85)
60
5626
81 (74–86)
49.5
18 897
82 (75–87)
32.7
Tsuji et al.
2017
Japan
Retrospective cohort
3480
730
66.9 ± 12.7
76.7
596
69.0 ± 11.6
71.8
2154
71.7 ± 10.9
60.8
Steinberg et al.
2012
USA
Retrospective cohort
110 621
55 083
70 (58–80)
64
15 184
76 (65–84)
53
40 453
78 (67–85)
37
Toma et al.
2014
398 centres across the world
Retrospective cohort
5687
4474
64 (54–73)
71.4
674
73 (64–81)
58.9
539
76 (66–82)
41.6
Kapoor et al.
2016
USA
Retrospective cohort
99 825
48 950
69.6 ± 14.2
63.2
12 819
74.4 ± 13.3
51.1
38 056
75.9 ± 13.1
34.9
Löfman et al.
2017
Sweden
Retrospective cohort
40 230
12 607
67 (59–76)
75
2087
71 (62–79)
47.5
3908
75 (65–82)
51
Tsutsui et al.
2001
Japan
Prospective cohort
172
61
67 ± 14
71
38
69 ± 9
61
73
69 ± 16
49
Numbers are expressed as mean ± SD or median (inter‐quartile range).
Study characteristics and the patient characteristics in the included studiesNumbers are expressed as mean ± SD or median (inter‐quartile range).
All‐cause death
As shown in Figure
, HFmrEF had a significantly lower all‐cause death rate than had HFrEF (RR, 0.9; 95% CI, 0.85–0.94; P < 0.001). On the other hand, there was no significant difference between HFpEF and HFmrEF (RR, 0.98; 95% CI, 0.86–1.12; P = 0.82). Both analyses detected high levels of heterogeneity (I
2 = 84% and I
2 = 98%).
Figure 2
Forest plots demonstrating all‐cause death in (A) HFrEF and HFmrEF and (B) HFpEF and HFmrEF. HFmrEF, mid‐range ejection fraction heart failure; HFpEF, preserved ejection fraction heart failure; HFrEF, reduced ejection fraction heart failure.
Forest plots demonstrating all‐cause death in (A) HFrEF and HFmrEF and (B) HFpEF and HFmrEF. HFmrEF, mid‐range ejection fraction heart failure; HFpEF, preserved ejection fraction heart failure; HFrEF, reduced ejection fraction heart failure.
Cardiac and non‐cardiac mortality rates
As shown in Figure
, the pooled analyses of the cardiac mortality results showed no significant difference between HFrEF and HFmrEF (RR, 0.89; 95% CI, 0.69–1.15; P = 0.38), but HFpEF had a significantly higher cardiac mortality rate than had HFmrEF (RR, 1.09; 95% CI, 1.02–1.16; P = 0.001). The two pooled analyses detected low levels of heterogeneity (I
2 = 0% and I
2 = 46%).
Forest plots demonstrating (A, B) cardiac and (C, D) non‐cardiac mortality rates. HFmrEF, mid‐range ejection fraction heart failure; HFpEF, preserved ejection fraction heart failure; HFrEF, reduced ejection fraction heart failure.Regarding the non‐cardiac mortality results, HFrEF had a significantly higher rate than had HFmrEF (RR, 1.31; 95% CI, 1.22–1.41; P < 0.001), while there was no significant difference between HFpEF and HFmrEF (RR, 0.91; 95% CI, 0.75–1.09; P = 0.3). The analyses showed low and high levels of heterogeneity (I
2 = 46% and I
2 = 57%).
All‐cause and HF‐related hospitalization
As shown in Figure
, the pooled analyses of all‐cause hospitalization showed no significant difference between HFrEF and HFmrEF or between HFpEF and HFmrEF (RR, 0.91; 95% CI, 0.18–4.59; P = 0.9; and RR, 0.95; 95% CI, 0.84–1.07; P = 0.38, respectively). Both analyses detected high levels of heterogeneity (I
2 = 100% and I
2 = 62%).
Forest plots demonstrating (A, B) all‐cause hospitalization and (C, D) HF‐related hospitalization. HFmrEF, mid‐range ejection fraction heart failure; HFpEF, preserved ejection fraction heart failure; HFrEF, reduced ejection fraction heart failure.Regarding HF‐related hospitalization, the pooled analyses showed also no significant differences between HFrEF and HFmrEF or between HFpEF and HFmrEF (RR, 0.92; 95% CI, 0.84–1.01; P = 0.08; and RR, 1.05; 95% CI, 0.83–1.33; P = 0.69, respectively). Both analyses had high levels of heterogeneity (I
2 = 85% and I
2 = 98%).
Discussion
For a decade now, it has been uncertain as to whether HFmrEF should be considered as a separate clinical entity of HF and subsequently having different prognosis and treatment from HFpEF and HFrEF or not; so, in our study, we measured the mortality rates and hospital re‐admission rates in the different types as a measure of this difference.Moher et al.9 and Gomez‐Otero et al.12 considered HFmrEF as part of HFrEF owing to its high prevalence of ischaemic heart disease and its response to N terminal pro‐brain natriuretic peptide‐guided therapy. On the other hand, Margolis et al.13 and Coles et al.14 considered HFmrEF as a separate clinical entity with intermediate features between HFrEF and HFpEF.13, 14Some studies suggested that HFmrEF represents a transitional status or an overlap zone between HFpEF and HFrEF, rather than an independent entity of HF, and another study showed that HFmrEF constitutes intermediate features between both HFpEF and HFrEF, with more similarities towards HFpEF than to HFrEF.35Morbidity and mortality rates proved to be similar in HFpEF and HFrEF36; however, there are not enough studies to measure them in HFmrEF. On the other hand, there are many studies discussing all‐cause mortality, HF‐related mortality, all‐cause hospital re‐admission, and HF‐related hospital re‐admission, so we pooled these outcomes to better understand this new entity of HF.2Our meta‐analysis is the largest study meta‐analysing the results of HFmrEF prognosis in the elderly population. Our study further supports the European Society of Cardiology guidelines by showing a significant difference between HFmrEF and HFrEF or HFpEF. This further supports the guidelines considering HFmrEF as a separate entity. Our meta‐analysis detected a significant difference between HFrEF and HFmrEF regarding all‐cause death and non‐cardiac death, but there was no difference between the two arms regarding cardiac mortality, all‐cause hospitalization, or HF‐related hospitalization. On the other hand, we detected a significant difference between HFpEF and HFmrEF regarding cardiac mortality, but there was no significant difference between the two arms regarding all‐cause death, non‐cardiac mortality, all‐cause hospitalization, or HF‐related hospitalization.These findings further support the statistical evidence making it a separate entity, but the clinical significance of HFmrEF separation must be reconsidered as only few of the outcomes significantly differed between the HF subtypes, and the measures of those outcomes did not show a high clinical significance.Accordingly, we recommend developing other studies evaluating the cut‐off points separating the HF subtypes. Future studies should consider the transition or the change of HF status over time as this may affect the outcomes. This could help prevent data overlap between the HF subtypes. Also, they should consider other factors affecting the outcomes such as distinguishing between acute and chronic HF and the data distribution inside each arm of HF.Our study was limited by the marked level of heterogeneity across the studies, the different distribution of precipitating factors of HF possibly playing as confounders, the probably misleading values of RRs (which do not consider the different periods of follow‐up), the type of HF (either acute or chronic), and the similarity in the outcome between the three HF subtypes, but this may be explained as the eligible patients in some of the included studies belonged to the same medical centre and were of the same race, which raises the suspicion that their similar lifestyle and co‐morbidities are the reason why they have similar mortality rates rather than being influenced by the subtype of HF they have. Also, 20 studies were eligible. Not all of them discussed the four outcomes as primary endpoints, so the small number of the data points made the outcome analysis less informative.
Conclusions
In conclusion, significant differences of hospitalization and mortality were detected between HFmrEF and the other subtypes of HF, which supports classifying HFmrEF as a special subtype.
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