Patients characteristics association with survival outcome

The clinical characteristics of the 246 selected patients, divided based on survival status and grouped based on the follow-up duration (31 days, 12 months, and 24 months FU), are reported in Table 1. At baseline, study participants’ median age (IQR) was 86 (83–90) years, and females were 56.9%. As expected, older patients were significantly more represented among deceased patients for all the three follow-up periods considered (p < 0.05 for 31 days, 12 months and 24 months FU, Table 1). Due to the selection strategy, the comorbidity with the highest prevalence was CHF (82.9%), followed by hypertension (HTN), CKD, cardiac arrhythmias, COPD, diabetes/dyslipidemia, CAD/PAD, acute diseases of the digestive system, endocrine/nutritional and metabolic diseases, pneumonia, degenerative diseases of the CNS, acute diseases of the urinary system, chronic diseases of the digestive system, cancer, bone and muscle diseases, unspecified pleural effusion, and, lastly, stroke (2.8%). The impact of these diseases on death risk at the defined time-points is different: a statistically significant difference between survived and deceased patients was found for stroke considering in-hospital mortality (31 days FU), for HTN considering 12 months FU, and for degenerative diseases of the CNS considering 24 months FU (p < 0.05, Table 1). In deceased patients, the rates for stroke and degenerative diseases of the CNS were higher than in survived patients (10.3% vs. 1.8%, 19.1% vs. 10%, and 38.2% vs. 25.5%, respectively, Table 1). Notably, the proportion of HTN was significantly higher in survived patients than in deceased patients (85.4% vs. 71.6% for HTN). These paradoxical results should be contextualized within the therapy regimens and the overall complex clinical evaluation of the patients. Overall, during the 24-month follow-up, 136 (55.3%) deaths occurred with a mean of time to death of 14 months; this is not a surprising result, considering the very old age of this cohort. Interestingly, HFRS was not a determinant for the 31-day risk of death, but it becomes statistically significant for the 12- and 24-month FU. In particular, the “intermediate risk category” appears to have the highest risk of death. About the diagnosis at entrance, CHF has the highest prevalence (21.3%) followed by pneumonia (data not shown). No patients with diabetes/dyslipidemia were hospitalized for these conditions.

Table 1 Clinical characteristics of the 246 selected patients, grouped based on the follow-up times (31 days, 12 months, and 24 months FU)Patients characteristics and circulating biomarker: associations with survival outcome

To estimate the association of miR-17, miR-21-5p, and miR-126-3p with mortality over the different FU periods, we tested miRNAs expression levels both as continuous and dichotomous variables, the upper quartile vs. all the other values. The results of these univariate analyses are reported in Table 1. miR-17 and miR-126-3p resulted significantly associated with mortality. When miR-17 expression levels were analyzed as continuous values, a statistically significant association was observed with mortality at 31 days FU (miR-17 median value of 2.51 for survived patients vs. miR-17 median value of 1.46 for deceased patients, p = 0.009). When miR-17 expression levels were analyzed as dichotomized values, a significant association with mortality at 24 months FU was found (30.9% of survived patients vs 19.9% of deceased with miR-17 ≥ 4.59, p = 0.046). For miR-126-3p, a statistically significant association with mortality at 31 days FU was observed for continuous values (miR-126-3p median value of 4.02 for survived patients vs miR-126-3p median value of 2.08 for deceased patients, p = 0.025). Interestingly, when miR-126-3p expression levels were analyzed as dichotomized values, miR-126-3p levels ≥ 6.66 were statistically more represented among survived patients both at 12- and 24-months FU (p = 0.017 and p = 0.004, respectively), suggesting a protective effect of this miRNA on mortality.

Notably, on the entire sample, a strong correlation between miR-17 and miR-126-3p expression levels was found (Pearson’s correlation 0.916, p < 0.001, data not shown).

On the contrary, no correlation between miR-21-5p and mortality at any FU periods was found (p not significant, Table 1).

Among routine blood parameters, a significant association with 31-day mortality was observed for the following biomarkers: WBC, neutrophils %, lymphocytes %, monocytes %, neutrophil–lymphocyte ratio (NLR), BUN, creatinine, and eGFR. These parameters resulted significantly higher in deceased patients compared to survived patients, except for lymphocytes, monocytes, and eGFR. Biochemical parameters significantly associated with 12-month mortality were WBC, RBC, HGB, HCT, neutrophils %, lymphocytes %, monocytes %, eosinophils %, NLR, BUN, creatinine, and eGFR. Finally, parameters associated with 24-month mortality were the same as observed for 12 months mortality except for WBC and RBC that, in this case, did not reach the statistical significance. Among the hematological parameters, neither platelets nor basophils were associated with mortality at any FU time-point. Similarly, among the biochemical parameters, no association was observed for sodium and potassium.

Univariate and multivariate Cox proportional hazards regression analysis of overall survival at different FU

To estimate the association between miR-17 and miR-126-3p and the survival rate, we analyzed miRNAs expression levels in terms of quartiles and of dichotomous variable (highest quartile of miRNAs expression levels vs. all other quartiles), over the three time-points. Kaplan–Meier curves for miRNAs quartiles and for the highest quartile of miRNAs vs. the others are reported in Figs. 1 and 2, respectively. The quartiles-based analysis in Fig. 1 showed that patients with the lowest levels of miR-17 had a significantly higher risk mortality at 31 days (p = 0.016); conversely, the higher risk of mortality at 24-month FU was observed for patients with the lowest levels of miR-126-3p (p = 0.028). When we considered the highest quartile of miR-17 and miR-126-3p, the log-rank test showed that patients with the highest levels of miR-17 (higher than 4.59) and miR-126-3p (higher than 6.66) had a better prognosis at 24 months FU (p = 0.029 and p = 0.003, respectively). Moreover, the highest levels of miR-126-3p were positively associated with a good prognosis also at 12 months FU.

Fig. 1

Kaplan–Meier curves for miRNAs quartiles. Kaplan–Meier survival function for patients according to (A) miR-17 quartiles plasma levels and (B) miR-126 quartiles plasma levels in respect to the three times FU (31 days, 1 year, and 2 years). MiRNAs are reported as relative expression

Fig. 2

Kaplan–Meier curves for highest quartile of miRNA. Kaplan–Meier survival function for patients according to (A) miR-17 (upper quartile vs lowest quartile) and (B) miR-126 (upper quartile vs lowest quartile) plasma levels in respect to the three times FU (31 days, 1 year, and 2 years). MiRNAs are reported as relative expression

To evaluate the prognostic accuracy of all the variables resulted statistically significant in Table 1, the crude hazard ratio and CI 95% were evaluated through a logistic regression (see Table 2). Neither miR-17 nor miR-126-3p was found predictive of death rate, at any of the time-point. Concerning comorbidities, only HTN and stroke have been confirmed to be predictors of death. In particular, stroke reached statistical significance with a HR of 4.73 (1.43–15.64) for 31-day mortality. Surprisingly, patients with HTN would appear to be protected from the risk of death over all the FU considered (HR of 0.45 for 31-day FU, HR of 0.54 for 12-month FU, HR of 0.61 for 24-month FU). These results could be explained, at least partly, by the ongoing pharmacological treatments. Crude hazard ratio for HFRS confirmed the results reported in Table 1; patients belonging to the intermediate risk category have a higher risk of 12- and 24-month FU mortality (HR 1.88 (1.13–3.13) for 12-month FU and 2.06 (1.30–3.27) for 24-month FU, Table 2). Regarding biochemical parameters, crude HR confirmed the results already reported in Table 1. In particular, RBC, HGB, lymphocytes%, monocytes%, eosinophils%, and eGFR showed significantly crude HR < 1, suggesting that patients with low values of these biomarkers were at higher risk of death at the different time-points considered (Table 2). Conversely, WBC, HCT, neutrophils%, BUN, creatinine, and NLR showed significantly crude HR > 1, suggesting that patients with high values of these parameters were at higher risk of death at the different time-points considered (Table 2).

Table 2 Univariate Cox proportional hazards regression analysis of overall survival at different FU

Since the purpose of this study was to investigate the role of miRNAs in predicting the risk of death within a group of older patients with cardiovascular MM, the results of the adjusted Cox regression analysis of survival are reported in Table 3. The adjusted HR for miR-17 ≥ 4.59 at 24 months FU was 0.64 (0.42–0.97), suggesting that high levels of miR-17 could be protective for the risk of death at 2 years (Table 3). Age, NLR, and eGFR were confirmed as predictors of mortality.

Table 3 Multivariate Cox proportional hazards regression analysis of overall survival at different FU

The adjusted HR for miR-126-3p ≥ 6.66 was 0.56 (0.34–0.92) at 12 months FU and 0.54 (0.35–0.84) at 24 months FU, suggesting that high miR-126 levels are protective for risk of death at 1–2 years from hospitalization (Table 3).

Notably, in both cases, female gender and hypertension were not associated with the risk of death.

miR-17 and miR-126-3p pathway analysis

To improve the functional characterization of selected miRNAs, we performed the pathway analysis through the platform DIANA-miRPath. The Pathway Union study revealed all the pathways in which miR-126-3p and miR-17 are involved, as well as the number of targeted mRNAs. We selected 21 pathways containing mRNAs targeted by miR-126-3p and miR-17. Some of these pathways are associated with human diseases, such as cancer, metabolic diseases, and atherosclerosis, and mechanisms involved in the aging process, such as autophagy, cellular senescence, and longevity regulating pathways (Table 4).

Table 4 Pathway union analysis of miR-126-3p and miR-17 by miRPath.v4

The Target Union analysis highlighted 7 mRNAs targets of both miR-126-3p and miR-17. Table 5 displays the gene target corresponding IDs, as obtained by the DIANA miRpath.v4 analysis.

Table 5 Target union analysis of miR-126-3p/miR-17 by miRPath.v4