1. Introduction
Acute myocardical infarction becomes an important healthcare probleme along young pacients [
1,
2,
3,
4]. Age-related differences in cardiovascular risk profiles, coronary anatomy and therapeutic approaches may signicaly influence in-hospital outcomes [
5,
6,
7]. Previous studies has demonstrated rhat younger patients with myocardical infarction often exhibit clinical and angiographic phenotypes compared with older individuals, including a higher prevalence of non-traditional risk factors and different patterns of coronary artery involvement [
8,
9,
10].
Length of hospital stay represents an important marker of disease severity and prognosis in acute myocardical infarction.[
11,
12] Long in hospital stay has been associated with more rates of complications, increased costs and longer recovery. [
14,
15] However, most studies evaluating hospital stay focus on overall cohorts with less attention on age.[
16,
17,
18]
Beyond its well-established role as a cardiovascular risk factor, diabetes mellitus is associated with complex neurohumoral and microvascular alterations that may aggravate myocardial injury and impair recovery following acute myocardial infarction [
11,
12,
29]
. These mechanisms may be particularly relevant in explaining prolonged hospitalization and delayed clinical stabilization in diabetic patients.
The present study aimed to assess clinical and angiographic implications in long stay hospitalisation in patients with acute myocardical infarction, comparing young and older individuals. By comparing this matters, we look to provide insights relatevant to risk stratification and optimization of in-hospital management strategis. [
19,
20,
21,
22]
2. Materials and Methods
2.1. Study Design and Population
This was a retrospective observational study conducted at the Craiova Country Emergency Clinical Hospital, including consecutive patients admitted with acute ST-segment elevation myocardical infarction over two year period.
2.2. Definitions and Measurements
STEMI was diagnosed by the current international criteria guideline [
1,
2,
27] pacients with NSTEMI were excluded from this study. [
1,
2] A total of 200 patients with the diagnosis of STEMI were included in this study and were divided into two subgroups: <45 years and >45 years. [
3,
8]
Clinical and demographic data were collected at admission and during hospitalization: sex, age, smoking status, history of diabetes mellitus and arterial hypertension, lipid profile(LDL-C, HDL-C, total cholesterol), serum creatinine levels, presence of thrombophilia and documented inflammatory disease. [
9,
10,
23]
Left ventricular ejection fraction was estimated using transthoracic echocardiography during hospitalization.
Coronary angiography evaluation was performed in patients with an indication for invasive evaluation. Agiographic assessment included culpit vessel, number of diseased vessel, percutaneous coronary intervention, stent implantation and number of stents were also collected. Significant coronary stenosis was defined as >50% luminal narrowing.[
2,
24]
Length of hospital stay was defined as the numer of days from admission to hospital discharge. Hopsitalization duration was analyzed as a continuous variable and dichotomized into long hospital stay >7 days versus <shorter hospital day
. [
14,
15,
16]
2.3. Objectives
The primary objective of this study was to evaluate and compare significant cardiovascular risk factors between younger (<45 years) and older (>45 years) patients with STEMI, and to assess age related differences in angiographic finfings and left ventricular ejection fraction.
The secondary objective was to identify clinical and angiographic predictiors of long stay in hospital and to evaluate difference in hospitalization burden between younger and oler patients.
2.4. Statistical Analysis
Continuous variables were expressed as medians with interquartile ranges (IQR), and categorical variables as counts and percentages. Group comparisons were performed using the Mann–Whitney U test for continuous variables and the χ2 test or Fisher’s exact test for categorical variables, as appropriate.
Prolonged hospital stay was defined according to the predefined threshold and analyzed as a binary outcome. Univariate analyses were performed to identify variables associated with prolonged hospitalization, followed by multivariable logistic regression to determine independent predictors. Results were reported as odds ratios (OR) with 95% confidence intervals (CI).
All analyses were two-sided, and a p value <0.05 was considered statistically significant.A two-sided p value <0.05 was considered statistically significant. Statistical analyses were performed using jamovi (version 2.6.45.0), based on the R statistical computing environment.
3. Results
The analysis of demographic and clinical characteristicts revealed several significant differences between patients aged <45 years and >45 years. (
Table 1) Male sex constituted the majority in both categories, representing 78,1% of patients in younger group and 70,1% in the older group, without a statistically significant difference between groups (p=0.196). Smoking status was similarly distributed across bouth groups, with no meaningful variation between younger and older individuals(p=0.426) [
3,
5]
In contrast, cardiometabolic comorbidities were markedly more prevalent among patients aged over 45 years. Diabetes mellitus affected nearly two-thirds of older patients (59,7%), compared with only 21,1% of those under 45 years (p<0.001). [
7,
21]A similar pattern was observed for hight blood pressure wich was documented in 90,3% pf older patients, significaly exceeding the prevalence observed in the younger cohort (65,2% p=<0.001). [
8,
9]
Analysis of lipid parameters revealed higher atherogenetic lipid levels amoung younger patients. Median LDL-cholesterol levels was significantly elevated in the <45 years group (158 mg/dL), compared with the older patients (130 mg/dL)(p=0.001). Total coholesterol followed the same trend, with higher median values in younger individuals (219 mg/dL vs 200 mg/dL, p=0.002). No significant difference was identified in HDL-cholesterol concentrations between age groups (p=0.407). Renal function differed significaly with higher serum creatinine values observed in patients age >45 years (p=0.008).
Thrombophilia and inflammatory diseases were more frenquently identified in younger patients, being present in 9 and 26 cases, respectively compared with only 1 and 10 cases in the older cohort (both p=<0.001). [
9,
18,
23]
Hepatic cytolysis was observed in a comparable proportion of patients in both groups, with no statistically significant difference between them (p=0.881), suggesting that liver enzyme elevation was not associated with the studied clinical phenotype.
With respect to infarction characteristics, a significant difference in infaction type was observed between the two age groups (p=0.002). Anterior and antero-lateral infraction were more common in patients <45 years, whereas inferior and infero-posterior infarction predominates in older patients. Unstable angina was rarely observed and occurred exclusively in the younger group.
Coronary angiograophy was performed significaly more often in patients younger than 45 years (95,5% vs 46,3% p<0.001). Accordingly, percutaneous coronary intervention with stent implantation was more freqvently performed in this group (87,5% vs 45,3% p<0.001). Younger patients predominantly predominantly presented with single-vessel diseases, most commonly involving the left anterior descending artery, while multivessel coronary artery disease was more prevalent in patients age >45 years (p<0.001) [
5,
8,
24]
Consistent with this findings, patients <45 years more freqvently required at least one coronary stent, whereas absence of stent implantation was more freqvently in the older age (p<0.001
). [
24,
25,
26]Thrombolytic therapy rates did not differ significantly between age groups. Left ventricular ejection was comparable overall, but showed a significally difference between the groups (p=0.006).(
Table 2)
Analysis of hospitalization duration (
Table 3) reveled significant age-related differences when stratified according age-related differences when stratified according to clinical, angiograohic, and procedural characteristics. A hospital stay longer than 7 days was significsly more frequent among with those younger than 45 years. [
11,
14,
16]
Diabetes mellitus showed a strng association with prolong hospitalization. Among patients hospitalized for more than 7 days, diabetes was significantluy more prevalent in the >45 years group than in the younger group (60,6% vs 2,8% p=0.002). Conversly, among patients with hospital stays shorter than 7 days, diabetes remaind significaly more frequent in older patients (28,7% vs 9,3& p<0.001).
Percutaneous coronary intervention with stent implantation also differented significaly according to age and hospitalization duration. In patients with hospital stays exceeding 7 days, PCI with stent implantation was more frequently performed in older age (16,9% vs 9,9%), while the absence of PCI was markedly more common in the >45 years (69% vs 4,2% p<0.001). Similary, among patients hospitalized for less than 7 days, PCI with stent implantation was more frequent in patients younger than 45 years (39,5% vs 26,4%), where lack of PCI predominated in older group.
Left anterior descending artery involvement demonstrated a significant association with hospitalization duration. For long hospital stay, LAD culpit lesions were more frequent in younge ages, while the absence of LAD involvement predominated in the older ages (p<0.001).
Left ventricular ejection fraction did not differ significantly between age group in relation with hospitalization duration. No significant differences were observed for EF <40% and >40% in either prolonged or shorter hospital stay (p=0.141).
In multivariable logistic regression analysis (
Table 4) assessing predictors of hospitalization duration, diabetes mellitus emerged as an independent determinant of prolonged hospital stay with a more than twofold increase in risk (OR 2.450, 95% CI 122-4.97, p=0.011). Likewise, involvement of the left anterior descending artery was significantly associated with longer hospitalization (OR 2.014, 95%CI 1.67-6.01, p=0.021).
Conversely, the performanve of percutaneous coronary intervention was independently associated with significanly reduced likelihood of prolonged hospitalization, indicationg a strong predictive effect (OR 0.186, 95%CI 0.08-0.43, p<0.001).
No significant associations were observed for age <45 years, sex, or the presence of multivessel disease, all of which failed to predict hospitalization duration in the adjusted model.
4. Discussion
In this retrospective observational study, we evaluated age-related differences in clinical, biological, and angiographic characteristics of patients presenting with ST-segment elevation myocardial infarction (STEMI), with a particular focus on predictors of prolonged hospitalization. The main findings of our analysis indicate that diabetes mellitus and left anterior descending (LAD) artery involvement were independent predictors of longer hospital stay, while percutaneous coronary intervention (PCI) was associated with a significantly shorter hospitalization duration, irrespective of age.
Consistent with previous reports, younger patients (<45 years) [
3,
8,
18] exhibited a distinct cardiovascular risk profile compared with older individuals. Traditional cardiometabolic risk factors, such as diabetes mellitus and arterial hypertension, were significantly more prevalent in patients over 45 years, whereas younger patients more frequently presented with thrombophilia, inflammatory diseases, and a more atherogenic lipid profile. These findings support the concept that myocardial infarction in younger individuals is often driven by non-traditional or emerging risk factors, rather than by long-standing metabolic comorbidities alone.
Angiographic characteristics also differed markedly between age groups. Younger patients were more frequently evaluated invasively and were more likely to undergo PCI with stent implantation, predominantly for single-vessel disease, most commonly involving the LAD artery. In contrast, older patients more often exhibited multivessel coronary artery disease and were less frequently treated with PCI, reflecting both more complex coronary anatomy and a higher burden of comorbidities that may limit invasive strategies. These differences likely contribute to the observed variations in hospitalization duration between age groups. [
24,
25,
26,
27,
28]
With regard to hospitalization burden, prolonged hospital stay (>7 days) was more strongly associated with clinical and procedural factors than with age itself. Diabetes mellitus emerged as a robust predictor of longer hospitalization, a finding that aligns with previous evidence linking diabetes to increased in-hospital complications, delayed recovery, and higher resource utilization following acute myocardial infarction. Recent data have shown that SGLT2 inhibition with dapagliflozin can ameliorate neural damage in both cardiac and renal tissues in diabetic models, suggesting potential mechanisms through which optimized metabolic control may influence post-infarction recovery and hospitalization burden [
30]
.Similarly, LAD involvement was independently associated with prolonged hospitalization, likely reflecting the larger myocardial territory at risk, increased infarct size, and higher likelihood of complications such as left ventricular dysfunction. [
24,
25,
26,
27] In contrast, PCI demonstrated a strong protective effect against prolonged hospitalization. Early and successful revascularization may facilitate faster clinical stabilization, earlier mobilization, and reduced complication rates, ultimately translating into shorter hospital stays. Notably, left ventricular ejection fraction did not independently predict hospitalization duration in our cohort, suggesting that anatomical and procedural factors may play a more prominent role in determining in-hospital recovery than systolic function alone in the acute phase.
Importantly, age itself was not an independent predictor of hospitalization duration in the multivariable model. This finding underscores the concept that hospitalization burden in STEMI patients is primarily driven by comorbidities, infarct characteristics, and treatment strategies rather than chronological age per se. These results highlight the importance of individualized risk stratification and emphasize the potential benefits of timely invasive management, even in older patients, when clinically appropriate.
4.1. Limitation
Several limitations of this study should be acknowledged. First, the retrospective, single-center design inherently limits causal inference and may affect the generalizability of the results to other populations or healthcare settings. In addition, the relatively small sample size may have reduced the statistical power to detect more subtle associations, particularly in subgroup and interaction analyses.
Second, hospitalization duration was dichotomized using a predefined threshold (>7 days), which, although clinically relevant, may oversimplify the complex and continuous nature of in-hospital recovery following acute myocardial infarction.
Third, an important limitation relates to potential differences in symptom-to-door time between age groups. Older patients are more likely to present later after symptom onset due to atypical clinical presentation, delayed symptom recognition, or limited access to emergency medical services. This delayed presentation may have contributed to greater myocardial injury, more complex clinical courses, and longer hospitalization, independently of angiographic or procedural characteristics.
Furthermore, although multivariable logistic regression was used to adjust for confounding factors, residual confounding cannot be excluded. Variables such as infarct size assessed by cardiac biomarkers, procedural complexity, in-hospital complications, frailty status, and post-procedural care pathways were not systematically captured and may have influenced hospitalization duration.
Finally, the exclusion of patients with non–ST-segment elevation myocardial infarction limits the applicability of the findings to STEMI populations only and does not allow extrapolation to the broader spectrum of acute coronary syndromes.
5. Conclusions
This study higlights important age-related differences in clinical profiles, agiographic characteristics, and hospitalization burden amoung patients presenting with STEMI. While younger patients more frequently exhibited non-traditional risk factors and were more often treated with invasive strageties, older patients had a higher prevalence of cardiometabolic comorbidities and more complex coronary artery disease.
Importanly, hospitalization duration was primarily influenced by clinical and procedural factors rather than chronological age alone. Diabetes mellitus and left anterior descending artery involvement were identified as independent predictors of prolonged hospital stay, whereas percutaneous coronary intervention was associated with a significanly shorter hospitalization duration.
These finfings underscore the importance of early risk stratification and timely revascularization strategies in patients with acute myocardical infarction, irrespective of age. Targeted management of high-risk subgroups, particulary patients with diabetes mellitus and extensive coronary involvement, may contribute to reduced hospitalization burden and improved in-hospital outcomes.
Future prospective, multicenter studies with larger patient populations are warranted to confirm these findings and to further explore age-specific strategies aimed at optimizing in-hospital management and resource utilization in acute myocardical infarction.
Author Contributions
Conceptualization, S.I.C., P.A.C methodology, I.C,B.; resources, A.M.B, I.C.B, M.T.P, I.D, G.C.T, C.M, A.M.P, D.R.H,. writing—S.I.C., P.A.C and O.I.; writing—review and editing, . E.N.Ț and I.C.B., S.I.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding. A full waiver of the Article Processing Charge (APC) was granted by the Editorial Office to Prof. Octavian Istratoaie.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of University of Medicine and Pharmacy of Craiova (181/09.07.2024).
Informed Consent Statement
Informed consent for participation was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author due to (Data are not publicly available due to privacy and ethical restrictions.).
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| AMI |
Acute Myocardial Infarction |
| ACS |
Acute Coronary Syndrome |
| CI |
Confidence Interval |
| EF |
Ejection Fraction |
| HDL-C |
High-Density Lipoprotein Cholesterol |
| HBP |
High Blood Pressure |
| IQR |
Interquartile Range |
| LAD |
Left Anterior Descending (artery) |
| LCX |
Left Circumflex (artery) |
| LDL-C |
Low-Density Lipoprotein Cholesterol |
| LV |
Left Ventricle |
| OR |
Odds Ratio |
| PCI |
Percutaneous Coronary Intervention |
| RCA |
Right Coronary Artery |
| STEMI |
ST-Segment Elevation Myocardial infarction |
References
- Thygesen, K.; Alpert, J.S.; Jaffe, A.S.; Chaitman, B.R.; Bax, J.J.; Morrow, D.A.; White, H.D. Fourth Universal Definition of Myocardial Infarction. Circulation 2018, 138, e618–e651. [Google Scholar] [CrossRef]
- Ibanez, B.; James, S.; Agewall, S.; Antunes, M.J.; Bucciarelli-Ducci, C.; Bueno, H.; Caforio, A.L.P.; Crea, F.; Goudevenos, J.A.; Halvorsen, S. 2017 ESC Guidelines for the Management of Acute Myocardial Infarction in Patients Presenting with ST-Segment Elevation. Eur. Heart J. 2018, 39, 119–177. [Google Scholar] [CrossRef] [PubMed]
- Puymirat, E.; Simon, T.; Cayla, G.; Cottin, Y.; Elbaz, M.; Coste, P.; Lemesle, G.; Motreff, P.; Popovic, B.; Khalife, K. Acute Myocardial Infarction in Young Adults. Lancet 2012, 380, 789–798. [Google Scholar]
- Gupta, A.; Wang, Y.; Spertus, J.A.; Geda, M.; Lorenze, N.; Nkonde-Price, C.; D’Onofrio, G.; Krumholz, H.M. Trends in Acute Myocardial Infarction in Young Patients and Differences by Sex and Race. J. Am. Coll. Cardiol. 2014, 64, 337–345. [Google Scholar] [CrossRef] [PubMed]
- Zimmerman, F.H.; Cameron, A.; Fisher, L.D.; Ng, G. Myocardial Infarction in Young Adults: Angiographic Characterization, Risk Factors and Prognosis. J. Am. Coll. Cardiol. 1995, 26, 654–661. [Google Scholar] [CrossRef]
- Cole, J.H.; Miller, J.I.; Sperling, L.S.; Weintraub, W.S. Long-Term Follow-Up of Coronary Artery Disease Presenting in Young Adults. Am. Heart J. 2004, 148, 528–533. [Google Scholar] [CrossRef]
- Yusuf, S.; Hawken, S.; Ounpuu, S.; Dans, T.; Avezum, A.; Lanas, F.; McQueen, M.; Budaj, A.; Pais, P.; Varigos, J. Effect of Potentially Modifiable Risk Factors Associated with Myocardial Infarction in 52 Countries (INTERHEART Study). Lancet 2004, 364, 937–952. [Google Scholar] [CrossRef]
- Cojocaru, P.A.; Țieranu, M.L.; Piorescu, M.T.; Buciu, I.C.; Belu, A.M.; Cureraru, S.I.; Țieranu, E.N.; Istratoaie, O. Myocardical Infarction in Young Adults: Revisiting Risk Factors and Atherothrombotic Pathways. Medicina 2025, 61, 1615. [Google Scholar] [CrossRef]
- Cureraru, S.I.; Cojocaru, P.A.; Buciu, I.C.; Belu, A.M.; Donoiu, I.; Țieranu, E.N.; Istratoaie, O. Clinical Relevance of Lipoprotein(a) in Young Patients with Acute Myocardial Infarction. Biomedicines 2025, 13, 2662. [Google Scholar] [CrossRef]
- Fox, K.A.A.; Steg, P.G.; Eagle, K.A.; Goodman, S.G.; Anderson, F.A.; Granger, C.B.; Flather, M.D.; Budaj, A.; Quill, A.; Gore, J.M. Decline in Rates of Death and Heart Failure in Acute Coronary Syndromes, 1999–2006. Eur. Heart J. 2006, 27, 217–224. [Google Scholar] [CrossRef]
- Udell, J.A.; Steg, P.G.; Scirica, B.M.; Smith, S.C.; Ohman, E.M.; Eagle, K.A.; Goto, S.; Gurfinkel, E.P.; Lopez-Sendon, J.; Montalescot, G. Diabetes Mellitus, Cardiovascular Risk, and Outcomes in Acute Coronary Syndromes. Eur. Heart J. 2014, 35, 1869–1878. [Google Scholar]
- Donahoe, S.M.; Stewart, G.C.; McCabe, C.H.; Mohanavelu, S.; Murphy, S.A.; Cannon, C.P.; Antman, E.M.; Braunwald, E. Diabetes and Mortality Following Acute Coronary Syndromes. JAMA 2007, 298, 765–775. [Google Scholar] [CrossRef] [PubMed]
- Shah, B.R.; Cowper, P.A.; O’Brien, S.M.; Granger, C.B.; Ohman, E.M.; Peterson, E.D.; Mark, D.B. Economic Outcomes after Acute Myocardial Infarction. Circulation 2012, 126, 299–307. [Google Scholar]
- Krumholz, H.M.; Chen, J.; Murillo, J.E.; Cohen, D.J.; Radford, M.J.; Wang, Y.; Vaccarino, V. Length of Stay, Quality of Care, and Outcomes in Myocardial Infarction. Circulation 1998, 97, 127–133. [Google Scholar]
- Bueno, H.; Rossello, X.; Pocock, S.J.; Van de Werf, F.; Chin, C.T.; Danchin, N.; Lee, S.W.; Medina, J.; Verheugt, F.W.A.; Fox, K.A.A. In-Hospital Length of Stay and Mortality in Acute Coronary Syndromes. Eur. Heart J. Acute Cardiovasc. Care 2017, 6, 30–39. [Google Scholar]
- Southern, D.A.; Quan, H.; Ghali, W.A. Comparison of Length of Stay and Outcomes after Acute Myocardial Infarction. Can. J. Cardiol. 2004, 20, 141–146. [Google Scholar]
- Auerbach, A.D.; Katz, R.; Pantilat, S.Z.; Bernacki, R.; Schnipper, J.L.; Wachter, R.M. Factors Associated with Prolonged Hospitalization. Arch. Intern. Med. 2004, 164, 733–740. [Google Scholar]
- De Luca, G.; Suryapranata, H.; Ottervanger, J.P.; Antman, E.M. Time Delay to Treatment and Mortality in STEMI. Am. J. Cardiol. 2004, 93, 1181–1185. [Google Scholar]
- Steg, P.G.; James, S.K.; Atar, D.; Badano, L.P.; Blömstrom-Lundqvist, C.; Borger, M.A.; Di Mario, C.; Dickstein, K.; Ducrocq, G.; Fernandez-Aviles, F. ESC Guidelines for the Management of Acute Myocardial Infarction. Eur. Heart J. 2012, 33, 2569–2619. [Google Scholar]
- Tegn, N.; Abdelnoor, M.; Aaberge, L.; Endresen, K.; Smith, P.; Aakhus, S.; Gjertsen, E.; Dahl-Hofseth, O.; Ranhoff, A.H.; Gullestad, L. Invasive versus Conservative Strategy in Elderly Patients with MI. N. Engl. J. Med. 2016, 374, 1943–1953. [Google Scholar]
- Singh, M.; Rihal, C.S.; Lennon, R.J.; Spertus, J.A.; Nair, K.S.; Roger, V.L. Influence of Frailty on Outcomes after PCI. J. Am. Coll. Cardiol. 2014, 63, 747–753. [Google Scholar]
- Mehta, S.R.; Cannon, C.P.; Fox, K.A.A.; Wallentin, L.; Boden, W.E.; Spacek, R.; Widimsky, P.; McCullough, P.A.; Hunt, D.; Braunwald, E. Routine versus Selective Invasive Strategies in Acute Coronary Syndromes. Lancet 2005, 366, 914–920. [Google Scholar]
- Valgimigli, M.; Gagnor, A.; Calabró, P.; Frigoli, E.; Leonardi, S.; Zaro, T.; Rubartelli, P.; Briguori, C.; Andò, G.; Repetto, A. Radial versus Femoral Access in Acute Coronary Syndromes. Lancet 2015, 385, 2465–2476. [Google Scholar] [CrossRef] [PubMed]
- Anderson, J.L.; Morrow, D.A. Acute Myocardial Infarction. N. Engl. J. Med. 2017, 376, 2053–2064. [Google Scholar] [CrossRef]
- Roffi, M.; Patrono, C.; Collet, J.P.; Mueller, C.; Valgimigli, M.; Andreotti, F.; Bax, J.J.; Borger, M.A.; Brotons, C.; Chew, D.P. 2015 ESC Guidelines for the Management of Acute Coronary Syndromes. Eur. Heart J. 2016, 37, 267–315. [Google Scholar] [CrossRef] [PubMed]
- Steg, P.G.; Dabbous, O.H.; Feldman, L.J.; Cohen-Solal, A.; Aumont, M.C.; López-Sendón, J.; Budaj, A.; Goldberg, R.J.; Klein, W.; Anderson, F.A. Determinants and Prognosis of Early Discharge after Acute Myocardial Infarction. Eur. Heart J. 2004, 25, 190–199. [Google Scholar]
- O’Gara, P.T.; Kushner, F.G.; Ascheim, D.D.; Casey, D.E.; Chung, M.K.; de Lemos, J.A.; Ettinger, S.M.; Fang, J.C.; Fesmire, F.M.; Franklin, B.A. 2013 ACCF/AHA Guideline for the Management of STEMI. Circulation 2013, 127, e362–e425. [Google Scholar]
- Roffi, M.; Patrono, C.; Collet, J.P.; Mueller, C.; Valgimigli, M.; Andreotti, F.; Bax, J.J.; Borger, M.A.; Brotons, C.; Chew, D.P. 2015 ESC Guidelines for the Management of Acute Coronary Syndromes without ST-Segment Elevation. Eur. Heart J. 2016, 37, 267–315. [Google Scholar] [CrossRef]
- Donoiu, I.; Târtea, G.; Sfredel, V.; Raicea, V.; Țucă, A.M.; Preda, A.N.; Cozma, D.; Vătășescu, R. Dapagliflozin Ameliorates Neural Damage in the Heart and Kidney of Diabetic Mice. Biomedicines 2023, 11, 3324. [Google Scholar] [CrossRef]
- Donoiu, I.; Târtea, G.; Sfredel, V.; Raicea, V.; Țucă, A.M.; Preda, A.N.; Cozma, D.; Vătășescu, R. Dapagliflozin Ameliorates Neural Damage in the Heart and Kidney of Diabetic Mice. Biomedicines 2023, 11, 3324. [Google Scholar] [CrossRef]
Table 1.
Baseline clinical, biological and laboratory characteristics of the study population.
Table 1.
Baseline clinical, biological and laboratory characteristics of the study population.
| |
|
Age group |
|
| |
<45 year n= 66 No. (%) Median(IQR) |
>45 years n= 134 No. (%) Median(IQR) |
p |
| Gender |
Men |
52(78,1%) |
94(70,1%) |
0.196 |
| Women |
14 (21,2%) |
40( 29,9%) |
| Smoking status |
Smoke |
48 (35,8%) |
86 (64,2%) |
0.426 |
| Non-smoke |
20 (30,3%) |
48 (35,8%) |
| Diabetes mellitus |
YES |
14 (21,2%) |
80 (59,7%) |
< 0.001 |
| NO |
52 (78,8%) |
54 (40,3%) |
| HBP status |
YES |
43 (65,2%) |
121 (90,3%) |
< 0.001 |
| NO |
23 (34,8%) |
13 (9,7%) |
| LDL Cholesterol |
158 (69 – 238) |
130 (45 – 302) |
0.001 |
| HDL Cholesterol |
39,5 (23 – 76) |
40,0 (7 – 100) |
0.4071 |
| Cholesterol |
219(109-290) |
200(100-394) |
0.002 |
| Serum creatinine (mg/dl) |
0,82(0,54-2,10) |
1,13(0,66-3,10) |
0.008 |
| Thrombophilia |
9 |
1 |
<0.001 |
| Inflammatory disease |
26 |
10 |
<0.001 |
| Hepatic cytolysis |
YES |
34(17%) |
71(35,5%) |
0.881 |
| NO |
32(16%) |
63(31,5%) |
Table 2.
Infarction characteristics and angiographyc findings.
Table 2.
Infarction characteristics and angiographyc findings.
| |
|
Age group |
|
| |
<45 year n= 66 |
>45 years n= 134 |
p |
| Type of infarction |
Anterior 67(33,5%) |
16(8%) |
51(25,5%) |
0.002 |
Anterolateral 19(9,5%) |
9(4,5%) |
10(5%) |
Inferior 41(20,5%) |
11(5,5%) |
30(15%) |
Inferolateral 3(1,5%) |
2(1%) |
1(0,5%) |
Inferoposterior 54(27%) |
15(7,5%) |
39(19,5%) |
Inferoposterolateral 5(2,5%) |
4(2%) |
1(0,5%) |
Posterior 2(1%) |
1(0,5%) |
1(0,5%) |
Posterolateral 2(1%) |
1(0,5%) |
1(0,5%) |
Inferoposterior with RV 3(1,5%) |
3(1,5%) |
0(0%) |
Inferoposterolateral with RV 1(0,5%) |
1(0,5%) |
0(0%) |
Lateral 2(1%) |
2(1%) |
0(0%) |
Unstable angina 1(0,5%) |
1(0,5%) |
0(0%) |
| Angiographically evaluated |
YES 124(62%) |
63(95,5%) |
6145,5%) |
<0.001 <0.001 |
No 76(38%) |
3(4,5%) |
73(54,5%) |
| PCI with stent implantation |
YES 104(52%) |
58 (87,9%) |
46(34,3%) |
<0.001
< 0.001 |
NO 96(48%) |
8(12,1%) |
88 (65,7%) |
| Coronary artery involvemnt |
None 6(3%) |
4 (6,1%) |
2 (1,5%) |
<0.001 |
LAD 32(16,0%) |
22(34,3%) |
10(7,5%) |
LCX 10(5,0%) |
6(9,1%) |
4(3%) |
RCA 32(16,0%) |
13(19,7%) |
19(14,2%) |
Two vessel disease 19(9,5%) |
10(14,1%) |
9(7,4%) |
Three vessel disease 25(12,5%) |
8(12,5%) |
17(12,5%) |
No angiographically evaluated 76(38%) |
3(4,7%) |
73(53,7%) |
| Number of stents |
0 stents 99(49,5%) |
11(16,7%) |
88(65,7%) |
<0.001 |
1 stent 71(35,5%) |
46(69,7%) |
25(18,7%) |
2 stents 18(9%) |
6(9,1%) |
12(9%) |
3 stents 9(4,5%) |
2(3%) |
7(5,2%) |
4 stents 3(1,5%( |
1(1,5%) |
2(1,5%) |
| Thrombolysis |
YES 53(26,1%) |
20(29,2%) |
33(24,6%) |
0.496 |
NO 146(73,9%) |
46(70,8%) |
101(75,4%) |
| EF% |
|
45±6,95 |
45±7,73 |
0.006 |
| Hospital stay |
|
4,32(1-10, 2.00) |
6,78(1-20,3.00) |
<0.001 |
Table 3.
Hospitalization duration.
Table 3.
Hospitalization duration.
| Long hospital stay Parameter |
|
Age group |
|
| |
<45 days n= 66 No. (%) Median(IQR) |
>45 days n= 134 No. (%) Median(IQR) |
p |
| >7 days |
Diabetes mellitus YES |
2(2,8%) |
43(60,6%) |
0.002 |
Diabetes mellitus NO |
8(11,3%) |
18(25,4%) |
| <7 days |
Diabetes mellitus YES |
12 ( 9,3%) |
37 (28,7%) |
<0.001 |
Diabetes mellitus NO |
44 (34,1%) |
36 (27,9%) |
| >7 days |
PCI with stent implantation YES |
7(9,9%) |
12(16,9%) |
<0.001 |
| PCI with stent implantation NO |
3(4,2%) |
49(69%) |
| <7 days |
PCI with stent implantation YES |
51(39,5%) |
34(26,4%) |
<0.001 |
| PCI with stent implantation NO |
5(3,9%) |
39(30,2%) |
| >7 days |
LAD culpit YES |
5(7%) |
3(4,2%) |
<0.001 |
LAD culpit NO |
5(7%) |
58(8,1%) |
| <7 days |
LAD culpit YES |
17(13,2%) |
7(5,4%) |
0.003 |
LAD culpit NO |
39(30,2%) |
66(51,2%) |
| >7 days |
EF<40% |
4(5,6%) |
35(49,3%) |
0.306 |
| EF>40% |
6(8,5%) |
26(36,6%) |
| <7 days |
EF<40% |
16(12,4%) |
30(23,3%) |
0.141 |
| EF>40% |
40(31,0%) |
43(33,3%) |
Table 4.
Predictors of hospitalization duration.
Table 4.
Predictors of hospitalization duration.
| Predictor |
OR |
CI |
p |
| Age <45 years vs >45 years |
0.531 |
00.20-1.35 |
0.187 |
| Diabetes mellitus(yes vs no) |
2.450 |
1.22-4.97 |
0.011 |
| Gender(man vs woman) |
0.689 |
0.33-1.42 |
0.316 |
| PCI(yes vs no) |
0.186 |
0.08=0.43 |
<0.001 |
| Multivesse disease |
1.338 |
0.53-3.32 |
0.532 |
| LAD involvement |
2.014 |
1.67-6.01 |
0.021 |
|
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).