Outcomes
Table 3 shows the results according to the multivariate Cox regression
analysis, and figure 3 (below) shows the Kaplan-Meier curves. Regarding
HF mortality and readmissions, age, comorbidity (CCI), Barthel index,
eGFR and serum sodium were significantly related to the endpoint. In the
analysis of the clusters, the clusters of patients without T2DM had
neither significantly better nor worse outcomes than those of cluster 1
(patients with T2DM). However, significantly worse outcomes were
detected among the patients with T2DM in clusters 2, 3 and 4, the worst
being in number 3 (HR 2.0, 95% CI 1.36-2.93, p=0.001). As for total
mortality and readmissions, again age, comorbidity (CCI), Barthel index,
eGFR, and serum sodium were significantly related to this endpoint.
Furthermore, in terms of clusters, clusters of patients without T2DM
were again not significantly associated with an increase in total
mortality and readmissions. Nevertheless, cluster 3 and 4, showed this
association, and once more cluster 3 was the worst (HR 1.6, 95% CI
1.22-2-16, p=0.001).
DISCUSSION
Our cluster analysis of patients with and without T2DM revealed a
greater number of defined groups among patients with T2DM and, moreover,
a worse prognosis in the majority of these patients compared with the
clusters of patients without T2DM.
Composite connections between comorbidities themselves and between
comorbidities and the cardiovascular system lead to the establishment of
HF, whether HFpEF or HFrEF. Conversely, HF may cause comorbidities,
which, in turn, adversely influence outcomes [15]. It is known that
HFpEF is associated with more comorbidities than HFrEF [16] and
thus, HFpEF emerges as a model with proinflammatory cardiovascular and
non-cardiovascular coexisting comorbidities, resulting in systemic
inflammation and later fibrosis and different clinical HFpEF phenotypes.
DM is a prevalent comorbidity in HF and has a significantly adverse
impact on prognosis. About 45% of patients with HFpEF have DM, and the
prevalence of comorbid DM is growing most markedly in those with
new-onset HFpEF [17]. Although the characteristics and outcomes of
this population are poorly understood, some previous reports suggest
that DM is associated with increased morbidity and long-term mortality
in HFpEF [18,19]. Furthermore, patients with DM and HFpEF have
already been described as a unique phenotype within HFpEF [19]. In
this study, we show how other additional pathologies can form new
sub-clusters resulting in different outcomes within the group of
patients with T2DM, while this influence is not observed in patients
without T2DM.
Compared to the set of patients without T2DM, our patients with T2DM
shared similar characteristics to those previously described in this
phenotype [19]. Patients had higher BMI, more prevalence of both
dyslipidemia and ischemic etiology, and all subgroups were similar in
terms of impaired renal function and hemoglobin below 12 g/dl. We might
hypothesize about the presence of a cardiorenal anemia syndrome in this
population, derived from an interaction between diabetic microvascular
disease affecting the kidneys and myocardium [20], and other factors
such as elevated central venous and intra-abdominal pressure, left
ventricular hypertrophy, left ventricular strain, RAAS activation,
oxidative injury, pulmonary hypertension, and right ventricular
dysfunction [21]. Additionally, it should be noted that AF/flutter
can form a separate cluster (cluster 4), very similar to cluster 1
except for the presence of these arrhythmias and older age. It is known
that AF/flutter interacts with both DM and HFpEF [22,23]. In our
case, the presence of AF/flutter in patients with HFpEF and DM
determines a different profile which adds up to a significantly worse
outcome. However, the worst profile in terms of outcomes corresponds to
cluster 3, the only group of T2DM patients with predominantly men, and
the one that is particularly characterized by the presence of COPD (also
more than half of the patients had AF/flutter). It is known that COPD is
an independent predictor of mortality in patients with HFpEF and in
patients with HFrEF [24]. DM is likewise independently correlated
with reduced lung function, while obesity may further worsen ventilatory
mechanics [25]. Apart from smoking, which is more prevalent in this
group, the comorbidity burden (CCI) is also the highest. All these
factors may incorporate a pro-inflammatory state that determines greater
cardiovascular disease, and this, along with a worse functional class
(the prevalence of NYHA III was the highest in this cluster), could
contribute to higher mortality.
In contrast to patients with T2DM, the clusters of patients without T2DM
had significant differences in hemoglobin and renal function (eGFR).
Renal impairment is not as prevalent as in diabetic patients and
determines one group (cluster 6) in which dyslipidemia and
cerebrovascular disease is also prevalent. This cluster is comparable
with clusters 1 and 4 in patients with T2DM. However, the differences in
hemoglobin and eGFR may lead to a lower prevalence of cardiorenal anemia
syndrome, and along with the absence of T2DM may contribute to the
differences in prognosis among these clusters. Again cluster 5 may have
some similarities with cluster 3. The presence of COPD and smoking are
decisive in both groups, though, here too, disparities in eGFR, BMI and
hemoglobin may play a role in the significant differences in outcomes.
Finally clusters 2 and 7, which were the most numerous, encompass the
oldest female patients with a high prevalence of AF/flutter and
hypertensive myocardiopathy, but with no another differential
characteristics. It could be that patients with genuine HFpEF and no
other relevant pathologies (their CCI was the lowest among the clusters
in their class, with/without T2DM) modify the phenotype, irrespective of
the presence or absence of T2DM, which would contribute to the
difference in the prognosis between both of them in terms of HF. These
clusters should be better defined using other variables that we were
unable to analyze, such as exercise capacity or vascular stiffness.
Our study has several limitations. Firstly, mortality during admission
was not recorded, and this may have led to a significant selection bias
and misleading results. Secondly, the data come from a registry which
started to include patients in 2008, so they may not all conform to the
current definition of HFpEF. Finally, we have not included in the
analysis some discordant comorbidities of T2DM (e.g., depression) that
may have a significant clinical impact [26].
In conclusion, the grouping of our patients with HFpEF and T2DM into
clusters based on their comorbidities revealed prognostic implications
according to the phenotype obtained. All clusters with T2DM presented
similar levels of kidney disease and anemia. In contrast, the clusters
of patients with HFpEF but without T2DM showed significant differences
in renal dysfunction and anemia. However, they did not have a
significantly worse outcome compared to the clusters with T2DM.
Therefore, comorbidities may play a more important role in determining
prognosis in patients with HFpEF and T2DM.
FUNDING
This study received neither grants nor funding.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
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Table 1: Characteristics by clusters based on selected comorbidities