## 5 Discussion and Conclusions  
In this paper, a novel approach based on an NME model was proposed for the analysis of cardiac-biomarkers release in AMI patients of the STEMI subclass. In particular, the inter-individual variability in the cTnT release time course was investigated, identifying the clinical covariates that have a significant influence on the parameters of the underlying release model. The proposed approach paves the way for the development of novel strategies to exploit cardiac-biomarkers acquisition in a clinical context, to gain patient-specific detailed valuable information for both diagnosis and prognosis. From the preliminary analysis conducted in this work, despite the limited number of patients and the reduced number of considered covariates, we found a statistically significant relationship between dyslipidemia and the shape of the cTnT release curve. In particular, the results highlight its implications for the parameter related to the clear  
Figure 10: Distribution of the \(-2\)LL values for each iteration among all the five trajectors. Figure 9: Population parameter estimates with respect to the iterations of SAEM during the convergence assessment of the model. Each color refers to a trajectory. ance of cTnT from the circulatory system. Further assessments of the proposed model concerned the evaluation of its ability to explain the experimental data by exploiting an MCMC strategy to sample the parameters model from a conditional distribution. Of note is that, despite the known clinical implication of dyslipidemia in cardiovascular disease, its direct influence on the cTnT release curve is not yet investigated in the literature. Notice that, despite the limited number of patients, the number of subjects with dyslipidemia in our dataset (9 out of 27) is coherent with the incidence rate encountered in AMI patients (20-40%). Furthermore, the statistical significance of the adjusted \(p\) value for the dyslipidemia covariate adds to the importance of our findings, providing a direction for future and more comprehensive investigation. On the other hand, other covariates with a known clinical impact on cTnT levels, such as the presence of diabetes, do not show a statistically significant influence, according to the NME analysis, probably due to the limited number of subjects analyzed. Another interesting finding is that dyslipidemic patients exhibit, on average, lower cTnT values with respect to non-dyslipidemic ones. This counter-intuitive finding, if confirmed in a larger cohort of patients, might be explained in several ways: one possibility is that it relates to the treatment with statins, a lipid-lowering drug, which exerts a protective function beyond their effect on blood cholesterol levels, by stabilizing the plaques and providing an anti-inflammatory effect. Since age and gender represent two other important risk factors for AMI, [42], we proceeded to evaluate their impact on the dynamics of cTnT release: in relation to the experimental data of the analyzed population, and as reported in [43], their effects may be mainly on the basal level of cTnT in the systemic circulation, specifically in male patients of ages greater than 65 years. However, due to the characteristics of the analyzed population, these two factors did not show a significant impact on the release curve. Future analysis is planned of another clinically interesting model suggested by the analysis and reported in Table 1, i.e., model 3: this model suggests taking into account both dyslipidemia and age. In particular, from the analysis emerges that age could influence the parameter \(T_{d}\), i.e., the threshold which allows modeling the release from sarcomere. Furthermore, a more thorough study on a larger dataset, including other potentially relevant covariates, e.g. renal failure (not available in the current dataset as none of the patients included had any impairment of renal function), and the circadian clock, will be the objective of our future work.