Effect and significance of hyperlipoproteinemia on stent thrombosis in patients with implanted drug-eluting stents: The 5-year follow up study.

BACKGROUND: Elevated blood lipid level, also known as hyperlipoproteinemia (HLP), is the most common metabolic disorder in the general population. According to US National Heart Institute data, about 36% of adults and 10% of children aged 9 to 12 have elevated cholesterol levels. The risk of ischemic heart disease increases by 2-3% with every 1% increase in total cholesterol levels. Therefore, men aged 55-65 with a 10% increase in total cholesterol have about 38% increased ischemic heart disease mortality. The study's main objective is to determine the occurrence of thrombotic complications in patients in whom first-generation drug-eluting stents are implanted and how these events are influenced by the presence of HLP. METHODS: The study is retrospective, clinical, and non-interventional with a five-year follow-up period for each patient. Initially, 800 patients undergoing index percutaneous coronary angioplasty with sirolimus-eluting and paclitaxel-eluting stent implantation were enrolled. Clinical data collected included cardiac disorders, the presence of diabetes mellitus, hyperlipoproteinemia, and smoking as a risk factor. In the examined group of patients, stent thrombosis was monitored according to Academic Research Consortium (ARC) criteria. RESULTS: The study included 800 patients who underwent percutaneous coronary angioplasty index. At the end of the follow-up period, 701 patients (87.6%) completed the clinical trial and were included in the statistical analysis. Stent thrombosis, determined according to ARC criteria, was reported as 'definitive stent thrombosis' in 22 patients (3.06%), 'probable stent thrombosis' in 1 patient (0.14%), and 'possible stent thrombosis' in 1 patient (0.14%). Of the 404 patients with HLP, 120 patients had a total cholesterol value >300 mg/dL. Twenty patients with definitive stent thrombosis had cholesterol >300 mg/dL. Patients with probable and possible stent thrombosis did not have HLP. A comparison of patients with stent thrombosis, with HLP and without HLP, revealed a statistically significant difference (16.67% vs. 1.35%, p <0.001). Comparing patients with unstable angina pectoris, with cholesterol value >300 mg/dL and without HLP, a statistically significant difference was observed (71.7% vs. 17.2%, p <0.001). CONCLUSIONS: We report on the long-term follow up of patients with stent thrombosis after drug-eluting stent insertion with and without HLP. The results suggest that HLP influences the development of coronary disease, with a significant influence on complications following percutaneous coronary intervention.

Performance of Charlson and Elixhauser Comorbidity Index to Predict in-Hospital Mortality in Patients with Stroke in Sumadija and Western Serbia.

BACKGROUND: Comorbidities are major predictors of in-hospital mortality in stroke patients. The Charlson comorbidity index (CCI) and the Elikhauser comorbidity index (ECI) are scoring systems for classifying comorbidities. We aimed to compare the performance of the CCI and ECI to predict in-hospital mortality in stroke patients. METHODS: We included patients hospitalized for stroke in the Clinical Center of Kragujevac, Serbia for the last 7 years. Hospitalizations caused by stroke, were identified by the International Classification of Diseases-10 (ICD-10) codes I60.0 - I69.9. All patients were divided into two cohorts: Alive cohort (n=3297) and Mortality cohort (n=978). RESULTS: There were significant associations between higher CCIS and increased risk of in-hospital mortality (HR = 1.07, 95% CI = 1.01-1.12) and between higher ECIS and increased risk of in-hospital mortality (HR = 1.04, 95% CI = 0.99-1.09). Almost 2/3 patients (66.9%) had comorbidities included in the CCI score and 1/3 patients (30.2%) had comorbidities included in the ECI score. The statistically significant higher CCI score (t = -3.88, df = 1017.96, P <0.01) and ECI score (t = -6.7, df = 1447.32, P <0.01) was in the mortality cohort.Area Under the Curve for ECI score was 0.606 and for CCI score was 0.549. CONCLUSION: Both, the CCI and the ECI can be used as scoring systems for classifying comorbidities in the administrative databases, but the model's ECI Score had a better discriminative performance of in-hospital mortality in the stroke patients than the CCI Score model.