Marian Morenci

Background/Objectives: New-onset atrial fibrillation (NOAF) is a common complication of acute coronary syndrome (ACS) and is associated with adverse clinical outcomes. Although systemic inflammation has been implicated in the pathogenesis of NOAF, the contribution of different inflammatory biomarkers and their incremental value beyond established clinical factors remain incompletely understood. This study aimed to examine the association between inflammatory biomarkers and NOAF in patients hospitalized with ACS and to assess their contribution beyond established clinical risk factors. Materials and Methods: This prospective single-center cohort included 100 consecutive patients hospitalized with ACS and without a documented history of atrial fibrillation. Comprehensive demographic, clinical, laboratory, echocardiographic, and angiographic data were collected. Systemic inflammatory status was assessed using C-reactive protein (CRP), the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), and the systemic immune-inflammation index (SII). Univariable and multivariable logistic regression analyses were performed to identify factors associated with NOAF. The incremental contribution of inflammatory biomarkers to apparent in-sample model discrimination was explored using receiver operating characteristic (ROC) curve analysis and DeLong’s test. Sensitivity analyses were performed according to the timing of NOAF occurrence. Results: NOAF occurred in 33 of 100 patients (33%) during hospitalization. Patients who developed NOAF were older and exhibited greater left atrial enlargement, more extensive coronary artery disease, and higher inflammatory biomarker levels. In univariable analyses, CRP, NLR, and SII were significantly associated with NOAF. In exploratory multivariable analyses adjusted for clinically selected covariates, CRP remained associated with NOAF (adjusted OR 1.71, 95% CI 1.08–2.91; p = 0.031), whereas NLR, SII, NT-proBNP, and troponin did not retain statistically significant associations. CRP demonstrated the highest numerical improvement in model discrimination, although the increase in AUC compared with the baseline clinical model was not statistically significant. Sensitivity analyses confirmed the consistency of the association between CRP and NOAF. Conclusions: In this exploratory single-center cohort, CRP remained associated with NOAF after adjustment for clinically selected covariates, supporting further investigation of the relationship between systemic inflammation and NOAF development. These findings require confirmation in larger cohorts with internal and external validation.

Background and Objectives: Wearable health technologies have become increasingly important in the remote management of cardiovascular diseases (CVDs); however, their successful implementation depends not only on technical performance but also on patient usability and technology acceptance. This study aimed to evaluate the perceived usability and technology acceptance of a wearable monitoring system among patients with CVDs and to investigate whether demographic and clinical characteristics influenced these outcomes. Materials and Methods: A cross-sectional observational study was conducted among 60 patients with CVDs enrolled in a six-month wearable monitoring program at the Medical Rehabilitation Outpatient Clinic of the Avram Iancu Clinical Hospital, Oradea, Romania. Participants used a Garmin vívosmart^® 5 fitness tracker to continuously monitor physiological and behavioral parameters. At the end of the monitoring period, perceived ease of use (PEU) was assessed using the System Usability Scale (SUS), while technology acceptance was evaluated using a Technology Acceptance Model (TAM)-based questionnaire. Descriptive statistics, reliability analysis, Spearman’s rank correlation, and multiple linear regression analyses were performed. Results: The wearable monitoring system demonstrated high PEU, with a median SUS score of 82.5 (IQR = 23.1) and a mean score of 75.5 ± 17.6. Overall, 75.0% of participants rated the system as having good or excellent usability. The SUS questionnaire demonstrated acceptable internal consistency (Cronbach’s α = 0.730; McDonald’s ω = 0.741). Technology acceptance was generally favorable, with an overall median TAM-based score of 1.33 (IQR = 0.78). Age and comorbidity burden were not associated with PEU, and no participant characteristics independently predicted SUS scores. Although the overall regression model was not statistically significant, age showed a statistically significant association with the overall TAM-based score (β = 0.328, p = 0.037). Significant positive correlations were observed between PU, self-efficacy (SE), and reverse-scored technology anxiety (TA) measure (p < 0.001). Conclusions: Patients with CVDs reported high PEU and favorable acceptance of wearable monitoring technology. While usability appeared independent of demographic and clinical characteristics, technology acceptance showed an exploratory association with age, although the overall regression model was not statistically significant. These findings support the integration of wearable monitoring systems into routine cardiovascular care and highlight the importance of patient-centered implementation strategies to promote long-term engagement.

Background/Objectives: Acute coronary syndromes (ACS) encompass a spectrum of clinical entities from unstable angina to non–ST-segment elevation myocardial infarction (NSTEMI) and ST-segment elevation myocardial infarction (STEMI), all associated with significant morbidity and mortality. Inflammation plays a central role in the pathophysiology of ACS, contributing to atherosclerotic plaque destabilization, myocardial injury, and adverse clinical outcomes. Inflammatory biomarkers, together with N-terminal pro–B-type natriuretic peptide (NT-proBNP), are increasingly used for risk stratification, yet their prognostic value across different ACS presentations remains unclear. This study aimed to assess the prognostic value of inflammatory status in patients with acute coronary syndromes in a single-center cohort. Methods: This prospective observational study included 100 consecutive patients with ACS and elevated inflammatory biomarkers, enrolled in 2024–2025 at a tertiary cardiovascular center. Inflammatory status was assessed by using C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII); NT-proBNP was also measured. The primary endpoint was in-hospital MACE, defined as cardiovascular death, recurrent myocardial infarction, stroke, urgent coronary revascularization, or acute heart failure requiring escalation of therapy. Multivariable logistic regression and ROC analyses were performed. Results: Among the 100 ACS patients, half experienced in-hospital MACE. Compared with those without events, patients with MACE were older (p = 0.003) and had higher inflammatory biomarkers—CRP (p < 0.001; strongest association), NLR (p = 0.030), and SII (p = 0.042)—as well as higher NT-proBNP (p = 0.002). Patients with MACE also showed reduced renal function (p < 0.001) and lower left ventricular systolic function, reflected by reduced LVEF (p = 0.001), indicating concomitant renal impairment and ventricular dysfunction. Hypertension was more prevalent in the MACE group (p = 0.028), and new-onset atrial fibrillation was significantly more common among these patients (p < 0.001). In multivariable analysis, LVEF emerged as an independent predictor of short-term outcomes (OR 0.934 per 1% increase; p = 0.047). Conclusions: Inflammatory activation appears closely linked to the occurrence of in-hospital adverse events in patients with acute coronary syndromes. While left ventricular ejection fraction remained an independent determinant of short-term outcomes, inflammatory biomarkers may provide complementary insight into the inflammatory burden accompanying ACS.

Background: Aging is associated with increased adiposity, sarcopenia risk, and metabolic vulnerability. Digital tools may enhance adherence to nutritional strategies, but their impact on detailed body composition remains insufficiently explored. Methods: This 6-month prospective controlled longitudinal intervention study included 60 middle-aged and older adults. All participants received a smart watch and smart scale for self-monitoring. The control group attended evaluations only at baseline and study completion, while the intervention group received monthly follow-up and remote feedback. Body composition was assessed using multi-frequency BIA. Statistical analyses included paired tests, effect sizes, correlations, and linear mixed-effects models. Results: Significant reductions were observed in BMI (p < 0.001), fat mass (p = 0.003), and visceral fat (p = 0.003; Cohen’s d = 0.41). The sarcopenic index improved (p = 0.001), while skeletal muscle mass remained stable. ECW increased significantly (p = 0.010). Age was inversely associated with the magnitude of improvement. Mixed-effects modeling confirmed a time-dependent reduction in visceral fat independent of age and sex. Conclusions: A 6-month digitally assisted nutritional monitoring program was associated with favorable changes in adiposity, muscle quality, and hydration status. Multi-frequency BIA provides valuable integrative markers for monitoring nutritional interventions in aging populations.