Predictors of Revascularization in Patients with Unstable Angina.

BACKGROUND: The factors that determine the necessity of coronary artery revascularization in patients with unstable angina (UA) have been supported by limited data. Therefore, this study aimed to identify the predictors of revascularization in patients with UA. METHODS: The study included the recorded data of 3668 patients with UA who underwent cardiac catheterization (age 66 ± 9.2, men 70%); 2615 of them (71%) underwent revascularization (percutaneous transluminal coronary angioplasty (PTCA), coronary artery bypass graft (CABG), or hybrid revascularization. The remaining 1053 patients (29%) had no significant coronary stenosis and were regarded as controls. Multivariable logistic regression analysis was performed to separate the predictors of revascularization. RESULTS: It was found that severe angina (OR 2.7, 95%CI 1.9-3.7), male gender (OR 1.4, 95%CI 1.1-1.7), and hyperlipidemia were the predictors of revascularization. It was also noted that intraventricular conduction disorders including left and right bundle branch blocks and a history of previous revascularization and myocardial infarction were associated with lower odds of revascularization. CONCLUSION: Overall, however, the predictive value of the studied factors proved to be poor and may still point to the multifactorial nature of significant coronary artery stenosis and the need for revascularization in patients with UA.

Machine learning model for predicting late recurrence of atrial fibrillation after catheter ablation.

Late recurrence of atrial fibrillation (LRAF) in the first year following catheter ablation is a common and significant clinical problem. Our study aimed to create a machine-learning model for predicting arrhythmic recurrence within the first year since catheter ablation. The study comprised 201 consecutive patients (age: 61.8 ± 8.1; women 36%) with paroxysmal, persistent, and long-standing persistent atrial fibrillation (AF) who underwent cryoballoon (61%) and radiofrequency ablation (39%). Five different supervised machine-learning models (decision tree, logistic regression, random forest, XGBoost, support vector machines) were developed for predicting AF recurrence. Further, SHapley Additive exPlanations were derived to explain the predictions using 82 parameters based on clinical, laboratory, and procedural variables collected from each patient. The models were trained and validated using a stratified fivefold cross-validation, and a feature selection was performed with permutation importance. The XGBoost model with 12 variables showed the best performance on the testing cohort, with the highest AUC of 0.75 [95% confidence interval 0.7395, 0.7653]. The machine-learned model, based on the easily available 12 clinical and laboratory variables, predicted LRAF with good performance, which may provide a valuable tool in clinical practice for better patient selection and personalized AF strategy following the procedure.

Cognitive Impairment in Cardiovascular Patients after Myocardial Infarction: Prospective Clinical Study.

(1) Background: Assessment of cognitive function is not routine in cardiac patients, and knowledge on the subject remains limited. The aim of this study was to assess post-myocardial infarction (MI) cognitive functioning in order to determine the frequency of cognitive impairment (CI) and to identify factors that may influence it. (2) Methods: A prospective study included 468 patients hospitalized for MI. Participants were assessed twice: during the first hospitalization and 6 months later. The Mini-Mental State Examination was used to assess the occurrence of CI. (3) Results: Cognitive dysfunction based on the MMSE was found in 37% (N-174) of patients during the first hospitalization. After 6 months, the prevalence of deficits decreased significantly to 25% (N-91) (p < 0.001). Patients with CI significantly differed from those without peri-infarction deficits in the GFR, BNP, ejection fraction and SYNTAX score, while after 6 months, significant differences were observed in LDL and HCT levels. There was a high prevalence of non-cognitive mental disorders among post-MI patients. (4) Conclusions: There is a high prevalence of CI and other non-cognitive mental disorders, such as depression, sleep disorders and a tendency to aggression, among post-MI patients. The analysis of the collected material indicates a significant impact of worse cardiac function expressed as EF and BNP, greater severity of coronary atherosclerosis expressed by SYNTAX results, and red blood cell parameters and LDL levels on the occurrence of CI in the post-MI patient population.

Beneficial effects of empagliflozin on hematocrit levels in a patient with severe anemia.

INTRODUCTION: Sodium-glucose cotransporter (SGLT2) inhibitors may additionally benefit patients with diabetes by improving their erythropoiesis followed by the elevation of hemoglobin and hematocrit levels. REASON FOR THE REPORT: In the case described, severe normocytic normochromic anemia was resolved when empagliflozin had been introduced to the therapy. A 78-year-old male patient was admitted to our hospital with a non-ST-segment elevation myocardial infarction. His past medical history included diabetes, right coronary artery angioplasty, myocardial infarction and paroxysmal atrial fibrillation which required anticoagulant treatment. When examined, severe normocytic normochromic anemia was also diagnosed. About two years prior to his admission, the patient began suffering from persistent anemia despite the modification of his anticoagulant therapy with warfarin, rivaroxaban and dabigatran. An extensive evaluation failed to provide an explanation for his anemia. OUTCOME: Eventually, only the introduction of empagliflozin successfully increased the values of hemoglobin and hematocrit. Therefore, it transpires that SGLT2 enhances erythropoietin (EPO) secretion which subsequently raises hematocrit levels in patients with severe anemia.

A Review of Acute Coronary Syndrome and its Potential Impact on Cognitive Function.

According to the World Health Organization (WHO) forecasts, in 2030, the number of people suffering from dementia will reach 82 million people worldwide, representing a huge burden on health and social care systems. Epidemiological data indicates a relationship between coronary heart disease (CHD) and the occurrence of cognitive impairment (CI) and dementia. It is known that both diseases have common risk factors. However, the impact of myocardial infarction (MI) on cognitive function remains controversial and largely unknown. The main goal of this study is to attempt to summarize and discuss selected scientific reports on the causes, mechanisms and effects of CI in patients after acute coronary syndrome (ACS), especially after MI. The risk of CI can increase in patients after ACS, and can therefore also adversely affect the further course of treatment. A late diagnosis of CI can lead to serious clinical implications, such as an increase in the number of hospitalizations and mortality.

Patients with Non-Obstructive Coronary Artery Disease Require Strict Control of All Cardiovascular Risk Factors: Results from the Polish Local Population Medical Records.

The aim of the project was to compare patients treated with percutaneous transluminal coronary angioplasty (PTCA), who also had undergone PTCA in the past, with a group of people who had had no angiographic stenosis in the lumen of the coronary arteries in the past, and who also required PTCA during index hospitalization. The secondary aim was to compare the obtained data with the characteristics of a group of people who had undergone angiography twice and for whom no significant stenosis had been found in their coronary arteries. The study used registry data concerning 3085 people who had undergone at least two invasive procedures. Acute coronary syndrome (ACS) was significantly more often observed (Non-ST-segment elevation myocardial infarction (NSTEMI) OR 2.76 [1.91-3.99] and ST-segment elevation myocardial infarction (STEMI) OR 2.35 [1.85-2.99]) in patients with no significant coronary stenosis in the past (who required coronary angioplasty at the time of the study), compared to patients who had already had PTCA. They also demonstrated more frequent occurrence of 'multivessel disease'. This was probably most likely caused by inadequate control of cardiovascular risk factors, as determined by higher total cholesterol levels ([mg/dL] 193.7 ± 44.4 vs. 178.2 ± 43.7) and LDL (123.4 ± 36.2 vs. 117.7 ± 36.2). On the other hand, patients in whom no significant stenosis was found in two consecutive angiographies were more likely to be burdened with chronic obstructive pulmonary disease, atrial fibrillation and chronic kidney disease.

Clinical applications of artificial intelligence in cardiology on the verge of the decade.

Artificial intelligence (AI) has been hailed as the fourth industrial revolution and its influence on people's lives is increasing. The research on AI applications in medicine is progressing rapidly. This revolution shows promise for more precise diagnoses, streamlined workflows, increased accessibility to healthcare services and new insights into ever-growing population-wide datasets. While some applications have already found their way into contemporary patient care, we are still in the early days of the AI-era in medicine. Despite the popularity of these new technologies, many practitioners lack an understanding of AI methods, their benefits, and pitfalls. This review aims to provide information about the general concepts of machine learning (ML) with special focus on the applications of such techniques in cardiovascular medicine. It also sets out the current trends in research related to medical applications of AI. Along with new possibilities, new threats arise - acknowledging and understanding them is as important as understanding the ML methodology itself. Therefore, attention is also paid to the current opinions and guidelines regarding the validation and safety of AI-powered tools.

Impact of genetic variants of selected cytochrome P450 isoenzymes on pharmacokinetics and pharmacodynamics of clopidogrel in patients co-treated with atorvastatin or rosuvastatin.

PURPOSE: Impaired antiplatelet effect of clopidogrel (CLP) can result from drug-drug interactions and genetic polymorphisms of drug-metabolizing enzymes. The aim of the study was to evaluate the effect of genetic polymorphisms of ABCB1 and the selected cytochrome P450 isoenzymes on the pharmacodynamics and pharmacokinetics of CLP and its metabolites in patients co-treated with atorvastatin or rosuvastatin. METHODS: The study involved 50 patients after coronary angiography/angioplasty treated with CLP and atorvastatin (n = 25) or rosuvastatin (n = 25) for at least 6 months. Plasma concentrations of CLP, diastereoisomers of thiol metabolite (inactive H3 and active H4), and inactive CLP carboxylic acid metabolite were measured by UPLC-MS/MS method. Identification of the CYP2C19*2, CYP2C19*17, CYP3A4*1G, CYP1A2*1F, and ABCB1 C3435T genetic polymorphisms was performed by PCR-RFLP, while platelet reactivity units (PRU) were tested using the VerifyNow P2Y12 assay. RESULTS: There were significant differences in the pharmacokinetic parameters of the H4 active metabolite of CLP in the atorvastatin and rosuvastatin group divided according to their CYP2C19 genotype. There were no significant associations between CYP3A4, CYP1A2, and ABCB1 genotypes and pharmacokinetic parameters in either statin groups. In the multivariate analysis, CYP2C19*2 genotype and non-genetic factors including BMI, age, and diabetes significantly affected platelet reactivity in the studied groups of patients (P < 0.01). In the atorvastatin group, CYP2C19*2, CYP3A4*1G, and ABCB1 C3435T TT genotypes were independent determinants of PRU values (P < 0.01). CONCLUSION: The CYP2C19*2 allele is the primary determinant of the exposition to the H4 active metabolite of clopidogrel and platelet reactivity in patients co-treated with atorvastatin or rosuvastatin.

Characteristics of circulating endothelial cells obtained from non-ST-segment elevation myocardial infarction patients with additional diastolic dysfunction of left ventricle observed in echocardiography.

BACKGROUND: Circulating endothelial cells (CEC) may be used to find new strategies for the early di-agnosis of cardiovascular diseases. The major objective of the project is to broaden knowledge of CEC biology by determining their phenotypic characteristics. The additional aim is to clarify whether on the basis of these information it is possible to identify the origin of CEC release (from various cardiovascular compartments). METHODS: Circulating endothelial cells were collected from arterial blood prior to angiography, as well as from arterial and venous blood obtained after angiography/coronary angioplasty, from 18 patients with non-ST-segment elevation myocardial infarction (NSTEMI). CECs were quantified by flow cytometry and defined as Syto16 (dye)+, CD45dim/neg, CD31+ and CD146+. The additional CD36+ was establish as a marker of endothelial cells released from small vessels of the microcirculation. RESULTS: The total number of CECs increased significantly after the percutaneous transluminal coronary angioplasty (PTCA) in the arterial system. Number of CECs isolated at similar time points (after invasive procedure) did not differ significantly between arteries and veins, but the number of CD36+ CECs after coronary angioplasty was significantly higher in the venous system, than in the arterial system. CONCLUSIONS: The number of CD36+ in artery samples obtained after coronary angioplasty (PTCA) had tendency to be decreased (in comparison to the sample obtained before angiography). It was major difference between those who had PTCA performed vs. those who had not.

The risk for subsequent coronary interventions in a local Polish population.

INTRODUCTION: Paradoxically, the literature lacks an assessment of the impact of various factors on subsequent coronary interventions in patients with coronary artery disease (CAD). AIM: To assess the impact of various factors on subsequent percutaneous transluminal coronary angioplasty (PTCA), as well as to characterize the clinical profile of people undergoing repeated diagnostic coronary angiography without significant coronary artery changes. MATERIAL AND METHODS: We investigated retrospective data from 4041 subjects according to the clinical factors which may affect the occurrence of unplanned future PTCA. RESULTS: The strongest risk factors for subsequent PTCA were significant stenosis of left descending artery (OR = 2.17, 95% CI: 1.09-4.32) during baseline coronary angiography, the atherosclerotic burden (number of critically narrowed vessels) (OR for narrowing lesions in 3 epicardial arteries 12.13, 95% CI: 5.40-27.27), and restenosis in a previously implanted stent (OR = 4.34, 95% CI: 1.96-9.62). A strong positive relationship between total mortality and the number of critically narrowed coronary arteries (during baseline hospitalization) was observed. Patients without significant coronary artery stenosis in two diagnostic angiographies (control group) differed from subjects with hemodynamic relevant CAD in: higher creatinine levels, more frequent presence of chronic obstructive pulmonary disease and more frequent symptoms of intermittent claudication. CONCLUSIONS: The results of the study are in accord with real clinical practice. The arteriosclerotic burden is a major cause of recurrent PTCA, but an important clinical issue is the qualification for recurrent coronary-angiography in those patients whose previous coronary angiography did not show significant stenosis, because other clinical causes may explain their symptoms.

Influence of statin treatment on pharmacokinetics and pharmacodynamics of clopidogrel and its metabolites in patients after coronary angiography/angioplasty.

Possible interaction between clopidogrel and CYP3A4-metabolised atorvastatin or non-CYP3A4-metabolised rosuvastatin was investigated based on pharmacokinetic parameters of clopidogrel and its metabolites as well as the platelet reactivity test in patients undergoing coronary angiography/angioplasty. The study involved 50 patients (62.7 ±â€¯7.8 years old) who underwent coronary angiography/angioplasty and were treated with clopidogrel and atorvastatin or rosuvastatin during the six months after the procedure. The P2Y12 reaction units (PRU) and pharmacokinetic parameters of clopidogrel, diastereoisomers of thiol metabolite (inactive H3 and active H4), and inactive carboxylic metabolite were measured 12-18 h and six months after the coronary angiography/angioplasty. There were no significant differences in concentrations of clopidogrel and its metabolites including the H4 active metabolite in plasma of patients co-treated with clopidogrel and atorvastatin or rosuvastatin. The use of statins did not affect the pharmacokinetic parameters of the studied compounds. A significant correlation was found between the Cmax and AUC0-t of the active H4 isomer and platelet aggregation in a group of patients treated with rosuvastatin but not in the atorvastatin group. No significant differences in PRU values were observed between the atorvastatin and rosuvastatin groups at the beginning of the study (171.4 ±â€¯54.3 vs 146.3 ±â€¯48.1 PRU, p = 0.192) as well as at six months (173.7 ±â€¯45.8 vs 157.3 ±â€¯54.9 PRU, p = 0.562). However, in a small group of patients, who were discharged from atorvastatin to rosuvastatin, an increase in the PRU values accompanied by a decreased AUC of the H4 active isomer was observed. The study confirmed that the systemic exposure to clopidogrel and its active H4 isomer of thiol metabolite, as well as the antiplatelet effect of the drug, were not negatively affected by co-administration of atorvastatin as compared with rosuvastatin.

Predicting Long-Term Mortality after Acute Coronary Syndrome Using Machine Learning Techniques and Hematological Markers.

INTRODUCTION: Hematological indices including red cell distribution width and neutrophil to lymphocyte ratio are proven to be associated with outcomes of acute coronary syndrome. The usefulness of machine learning techniques in predicting mortality after acute coronary syndrome based on such features has not been studied before. OBJECTIVE: We aim to create an alternative risk assessment tool, which is based on easily obtainable features, including hematological indices and inflammation markers. PATIENTS AND METHODS: We obtained the study data from the electronic medical records of 5053 patients hospitalized with acute coronary syndrome during a 5-year period. The time of follow-up ranged from 12 to 72 months. A machine learning classifier was trained to predict death during hospitalization and within 180 and 365 days from admission. Our method was compared with the Global Registry of Acute Coronary Events (GRACE) Score 2.0 on a test dataset. RESULTS: For in-hospital mortality, our model achieved a c-statistic of 0.89 while the GRACE score 2.0 achieved 0.90. For six-month mortality, the results of our model and the GRACE score on the test set were 0.77 and 0.73, respectively. Red cell distribution width (HR 1.23; 95% CL 1.16-1.30; P < 0.001) and neutrophil to lymphocyte ratio (HR 1.08; 95% CL 1.05-1.10; P < 0.001) showed independent association with all-cause mortality in multivariable Cox regression. CONCLUSIONS: Hematological markers, such as neutrophil count and red cell distribution width have a strong association with all-cause mortality after acute coronary syndrome. A machine-learned model which uses the abovementioned parameters can provide long-term predictions of accuracy comparable or superior to well-validated risk scores.

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value of laboratory and clinical parameters responsible for early recurrence of atrial fibrillation (ERAF) following cryoballoon ablation (CBA) using statistical assessment and machine learning algorithms. This study group comprised 118 consecutive patients (mean age, 62.5 ± 7.8 years; women 36%) with paroxysmal (54.1%) and persistent (45.9%) AF who underwent their first pulmonary vein isolation (PVI) performed by CBA (Arctic Front Advance 2nd generation 28 mm). The biomarker concentrations were measured at baseline and after CBA in a 24-h follow-up. ERAF was defined as at least a 30-s episode of arrhythmia registered by a 24 h-Holter monitor within the 3 months following the procedure. 56 clinical, laboratory and procedural variables were collected from each patient. We used two classification algorithms: support vector machines, gradient boosted tree. The synthetic minority over-sampling technique (SMOTE) was used to provide a balanced training data set. Within a period of 3 months 21 patients (17.8%) experienced ERAF. The statistical analysis indicated that the lowered levels of post-ablation TnT (p = 0.043) and CK-MB (p = 0.010) with the TnT elevation (p = 0.044) were the predictors of ERAF following CBA. In addition, diabetes and statin treatment were significantly associated with ERAF after CBA (p < 0.05). The machine learning algorithms confirmed the results obtained in the univariate analysis.

Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes.

BACKGROUND: Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in predicting short-term outcomes of acute coronary syndrome (ACS). METHODS: We analyzed the predictive importance of laboratory and clinical features in 6769 hospitalizations of patients with ACS. Two binary classifications were considered: significant coronary lesion (SCL) or lack of SCL, and in-hospital death or survival. SCL was observed in 73% of patients. In-hospital mortality was observed in 1.4% of patients and it was higher in the case of patients with SCL. Ensembles of decision trees and decision rule models were trained to predict these classifications. RESULTS: The best performing model for in-hospital mortality was based on the dominance-based rough set approach and the full set of laboratory as well as clinical features. This model achieved 81 ± 2.4% sensitivity and 81.1 ± 0.5% specificity in the detection of in-hospital mortality. The models trained for SCL performed considerably worse. The best performing model for detecting SCL achieved 56.9 ± 0.2% sensitivity and 66.9 ± 0.2% specificity. Dominance rough set approach classifier operating on the full set of clinical and laboratory features identifies presence or absence of diabetes, systolic and diastolic blood pressure and prothrombin time as having the highest confirmation measures (best predictive value) in the detection of in-hospital mortality. When we used the limited set of variables, neutrophil count, age, systolic and diastolic pressure and heart rate (taken at admission) achieved the high feature importance scores (provided by the gradient boosted trees classifier) as well as the positive confirmation measures (provided by the dominance-based rough set approach classifier). CONCLUSIONS: Machine learned models can rely on the association between the elevated inflammatory markers and the short-term ACS outcomes to provide accurate predictions. Moreover, such models can help assess the usefulness of laboratory and clinical features in predicting the in-hospital mortality of ACS patients.

The Role of Hematological Indices in Patients with Acute Coronary Syndrome.

An increased systemic and local inflammation plays a key role in the pathophysiology of acute coronary syndrome (ACS). This review will discuss the role of hematological indices: white blood cells (WBC), neutrophil to lymphocyte ratio (NLR), red cell distribution width (RDW), and platelet indices, that is, platelet to lymphocyte ratio (PLR), mean platelet volume (MPV), and platelet distribution width (PDW) in the case of ACS. In recent years, a strong interest has been drawn to these indices, given that they may provide independent information on pathophysiology, risk stratification, and optimal management. Their low-cost and consequent wide and easy availability in daily clinical practice have made them very popular in the laboratory testing. Furthermore, many studies have pointed at their effective prognostic value in all-cause mortality, major cardiovascular events, stent thrombosis, arrhythmias, and myocardial perfusion disorders in terms of acute myocardial infarction and unstable angina. The most recent research also emphasizes their significant value in the combined analysis with other markers, such as troponin, or with GRACE, SYNTAX, and TIMI scores, which improve risk stratification and diagnosis in ACS patients.

Association between adjunctive metformin therapy in young type 1 diabetes patients with excess body fat and reduction of carotid intima-media thickness.

INTRODUCTION    Lipoprotein-associated phospholipase A2 (Lp-PLA2) and cholesteryl ester lipase (CEL) may oxidize low-density lipoproteins (oxLDL). OBJECTIVES    The aim of the study was to determine the influence of metformin on the metabolism of atherogenic lipid fractions in relation to Lp-PLA2 and CEL levels, as well as assess consequent improvement in the intima-media thickness (IMT) of the common carotid artery in young type 1 diabetes patients with excess body fat. PATIENTS AND METHODS    It was an open-label randomized clinical trial that lasted 6 months. It included a total of 84 people with metabolic decompensation (glycated hemoglobin >7.5%, >58.5 mmol/mol) of diabetes. Adjunctive metformin therapy (in addition to insulin) was administered in 42 patients, and the remaining 42 patients received insulin alone. Glycated low-density lipoproteins (LDLs), oxLDL, Lp-PLA2, and CEL were assessed by commercially available enzyme-linked immunosorbent assay kits. Cartoid IMT was measured using the Carotid Analyser for Research tool. Biochemical analyses were performed using routine laboratory techniques. RESULTS    The reduction of mean carotid IMT was observed in young type 1 diabetic adults treated additionally with metformin (0.6 ±0.1 cm vs 0.53 ±0.1 cm; P = 0.002). This effect was probably due to weight reduction (90 ±16 kg vs 87 ±15 kg, P = 0.054) and the decrease in atherogenic glycated LDL levels (1.5 ±0.5 mg/dl vs 1.6 ±1.046 mg/dl, P = 0.006). No such correlations were observed in patients treated with insulin alone. Additionally, in patients receiving metformin, glycated LDL levels were inversely correlated with Lp-PLA2 levels (r = -0.31, P <0.05). CONCLUSIONS    Additional use of metformin in young type 1 diabetic patients with excess body fat leads to a significant reduction of mean IMT in the common carotid artery. Concentrations of CEL and Lp-PLA2 were significantly increased in both study arms despite improved glucose metabolism.

Evaluation of plasma PCSK9 concentrations, transcript of LDL receptor, as well as the total number of monocyte LDL receptors in acute coronary syndrome patients.

BACKGROUND: Before our study, there were no data concerning complex evaluation of: plasma PCSK9 concentrations, transcript LDL receptor (LDLR), as well as the total amount of monocytes' LDLR in acute coronary syndrome (ACS) patients. PCSK9 levels in a few cohort studies were found to correlate with the number of white blood cells (WBC) or platelets (PLT). The study aims to evaluate PCSK9-LDLR concentrations, as well as to find any association between PCSK9 and WBC or PLT. METHODS: The study group included 95 consecutive patients with acute myocardial infarction, in whom angiography/angioplasty of the culprit vessel was performed. The control group consisted of 10 healthy young volunteers. Thirty patients from the studied group were qualified for further percutaneous revascularization after 3 months. Laboratory tests were performed using commercially available kits. LDLR expression on monocyte surface was measured by flow cytometry, but the mRNA level for LDLR was established by real time polymerase chain reaction. The PCSK9 plasma concentration was measured by ELISA kits. RESULTS: Higher concentration of PCSK9 and amount of LDLR on monocytes surface were observed in patients with ACS compared with healthy young volunteers (number of LDLRs on monocytes [reaction units] 10.8 ± 9.6 vs. 41.8 ± 11.8, p < 0.001, PCSK9 [ng/mL] 295.4 ± 76.4 vs. 213 ± 63.2, p < 0.001). A similar relationship was observed after application of 3-month intensive lipid-lowering therapy in patients with ACS (n = 30, PCSK9 [ng/mL] 281.1 ± 59.5 vs. 358.5 ± 74.7, p < 0.001, LDLR transcript [reaction units] 0.6 ± 0.32 vs. 1.87 ± 0.24, p < 0.001, number of LDLRs on monocytes [reaction units] 5.9 ± 3.1 vs. 22.3 ± 3.8, p < 0.001). There were no significant differences in levels of PCSK9, LDLR between patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). There was no relation of the PCSK9 with WBC as well as with PLT. CONCLUSIONS: We observed significantly higher concentration of PCSK9, and significantly higher levels of mRNA LDLR transcript in patients with ACS compared with healthy young volunteers. A similar pattern was observed after 3 months of intensive statin therapy among patients with ACS. There were no differences in these parameters between patients with STEMI vs. NSTEMI. The results of the study require confirmation in a larger population of patients.

Lack of Serum Creatinine Decrease After Coronary Angiography Despite Prophylactic Hydration After Routine Coronary Angiography/Angioplasty in Stable Angina Patients--Pilot Study.

BACKGROUND/AIMS: To prevent contrast induced renal dysfunction a periprocedural prophylactic hydration is applied. Due to dilution it should cause a drop in serum creatinine concentration (SCR). Surprisingly, no reduction in SCR after contrast admission is found in up to 25% of patients as early as 12-18 hours after coronary angiography/angioplasty. This study aims to find a clinical explanation as well as predict circumstances for this phenomenon. METHODS: Retrospective clinical and laboratory data was used from 341 patients who underwent elective coronary angiography/angioplasty, received a prophylactic hydration, and had serum creatinine concentration measured prior to, and 12-18 hours after invasive procedure with iodine contrast administration. To exclude an improper hydration due to no creatinine decrease, the number of red blood cells was analysed as well as hemoglobin and hematocrit in blood donations collected during the study time points. RESULTS: The resulting lack of serum creatinine reduction could be explained by dehydration (measured by increase in number of RBC, HGB and HCT) only in 13.5% , 10.8%, and 20% of cases, respectively. Any form of abnormal glucose metabolism combined with either baseline serum creatinine concentration <0.87 mg/dL or creatinine clearance >86.77 mL/min, or GFR by CKD EPI >80.08 mL/min/1.73 m2, or GFR by MDRD >74.48 mL/min/1.73 m2 were the predictors for no creatinine decrease at outcome. Additionally, it was demonstrated that the lack of creatinine decrease was more often observed among those patients whose initial renal function was better than in the subjects with reduction of SCR. CONCLUSIONS: This observation requires further prospective investigation on extended group of patients.