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