## 3 Results
### 1-Year Mortality and MPV Value Relationship  
As for the results regarding the relationship between MPV and rehospitalization at 3 and 6 months, based on the value of MPV, we applied the logistic regression model to identify a statistical link between the MPV value and 1-year mortality in patients with HF. The statistical results regarding this hypothesis were revealing, indicating that patients with HF who died 1 year after the previous discharge versus patients who did not die after 1 year had a higher MPV value. The data obtained are shown numerically in Table 7 and graphically in Figure 14.  
By applying the logistic regression model, the estimated coefficients for which are shown in Table 7, we were able to predict the probability of a patient with HF dying at 1 year based on the MPV value.  
The model applied in this case is the following: score (event occurrence = mortality at 1 year) = \(-\)8.6367 + 0.7459 \(\times\) MPV. To be able to interpret the results as probabilities, we apply the following equation: \(\mathbf{p}=\frac{1}{1+\epsilon^{\frac{1}{2}\mathbf{p}\mathbf{\times}\mathbf{\times}}}\).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Dep.** & **Mortality\_1** & **No.** & & & & \\
**Variable:** & **Year** & **Observations:** & & & & \\ \hline Model: & Logit & Df Residuals: & 258 & & & \\ Method: & MLE & Df Model: & 1 & & & \\  & & Pseudo R-squ.. & 0.04536 & & & \\ Converged: & TRUE & LL-Null: & \(-\)102.72 & & & \\ \hline  & coef & std err & Z & \(p>\mid\mathbf{z}\mid\) & [0.025 & 0.975] \\ \hline Intercept & \(-\)8.6367 & 2.305 & \(-\)3.746 & 0 & \(-\)13.155 & \(-\)4.118 \\ MPV & 0.7459 & 0.249 & 2.994 & 0.003 & 0.258 & 1.234 \\ \hline \hline \end{tabular}
\end{table}
Table 7: The relationship between MPV and the probability of 1-year mortality in HF patients, explained by the logistic regression model.  
Figure 13: The probability that patients with HF will be rehospitalized at 6 months starting from the MPV value by applying the logistic regression model.  
The mathematical model described and applied above to HF patients who died at 1 year is statistically significant because the \(p\)-value associated with the coefficient for MPV (0.7459) is 0.003. The results obtained following the application of the above-mentioned mathematical formula are illustrated graphically in the figure below (Figure 14), in which it can be seen that, as the MPV value increases, the probability that an HF patient will die at 1 year also increases (patients with an MPV value of 7 fl had a probability below 5% to die at 1 year versus patients with an MPV value of 9 fl who had a probability of over 10%). Thus, we can predict the probability that a patient with HF will die at 1 year based on the MPV value, and state that the probability of this event increases as the value of the MPV increases.  
At the same time, this phenomenon is illustrated in the graphs represented in Figure 15, in which it can be observed that patients with HF who died at 1 year (1) had a higher MPV value (over 9 fl) compared to those who did not die at 1 year (0).  
Figure 14: The probability of 1-year mortality in HF patients based on MPV value by applying the logistic regression model.  
Figure 15: MPV value in HF patients who died at 1 year (1) versus HF patients who did not die at 1 year (0).