[Dynamics of Parameters of Transmitral Blood Flow and Markers of Myocardial Fibrosis in Patients with Myocardial Infarction].

Aim      To study possible correlations between echocardiography (EchoCG) indexes and markers of myocardial fibrosis, procollagen I C-terminal propeptide (PICP) and procollagen III N-terminal propeptide (PIIINP) during one year following ST-segment elevation myocardial infarction (STEMI).Material and methods  120 patients with STEMI were evaluated. EchoCG was used to assess dimensions and volumes of heart chambers, left ventricular (LV) systolic function, mean pulmonary arterial pressure (mPAP), and indexes of LV diastolic function (Em, early diastolic lateral mitral annular velocity; e', peak early diastolic septal mitral annular velocity; E / e', ratio of peak early diastolic transmitral inflow velocity and mitral annular velocity  -, Е / А, ratio of peak early and late transmitral inflow velocities; DT, deceleration time of LV early diastolic filling). EchoCG indexes and serum concentrations of PICP and PIIINP were determined at 1 (point 1) and 12 (point 2) days of disease and one year after STEMI (point 3). The sample was divided into two groups: group 1 (n=86; 71.7 %) included patients with a LV ejection fraction (EF) ≥50 % and group 2 (n=34; 28.3 %) consisted of patients with LV EF ≤49 %.Results At one year, the number of patients with signs of diastolic dysfunction increased by 10% in group 1 whereas myocardial systolic dysfunction worsened in both groups. LV EF decreased in 15 (17.4%) patients of group 1 and in 4 (11.8%) patients of group 2. Concentrations of PIIINP were correlated with Em, E / e', mPAP, PICP, e', and LV EF.Conclusion      Direct correlations between PIIINP concentrations and Em, E / e', and mPAP were found in the group with LV EF ≥50 %. In the group with LV EF <50 %, correlations were observed between PICP concentrations, LV EF, and e'. Also, in this group, the increase in PIIINP was statistically more significant. These results indicate continuing formation of myocardial fibrosis in a year following MI, which may underlie progression of chronic heart failure.

[Renal function estimation formulas in predicting long-term cardiovascular outcomes in patients with myocardial infarction concurrent with diabetes mellitus]. / Formuly otsenki funktsii pochek pri prognozirovanii otdalennykh serdechno-sosudistykh iskhodov u bol'nykh infarktom miokarda v sochetanii s sakharnym diabetom.

AIM: To comparatively assess formulas for estimating glomerular filtration rate (GFR) in the prediction of poor outcomes in patients with type 2 diabetes mellitus (DM) within one year after myocardial infarction (MI). MATERIALS AND METHODS: The investigators examined 89 patients with ST-segment elevation myocardial infarction (STEMI) within 24 hours after the onset of clinical symptoms of the disease. All the patients underwent standard laboratory and instrumental tests. GFR was calculated using the Modified of Diet in Renal Diseases (MDRD) formulas in terms of serum creatinine levels, the Hoek equation: GFR [ml/min/1.73 m2] = (80.35/cystatin C [mg/l]) - 4.3 (CKD-EPI), as well as from cystatin C levels, and the creatinine clearance rate was determined using the Cockcroft and Gault formula (ml/min). During a year after STEMI, the investigators recorded cardiovascular events (CVEs), such as death, recurrent MI, progressive angina pectoris, emergency coronary revascularization, and decompensated chronic heart failure (CHF). The examinees were divided into two groups: 1) 70 (78.6%) patients with MI and no DM; 2) 19 (21.3%) patients with MI and DM. RESULTS: Comparative analysis revealed a tendency towards a difference in the detection rate of GFR <60 ml/min/1.73 m2 calculated using the Hoek formula from cystatin C levels: 42.1% in Group 2 and 21.4% in Group 1 (р=0.067). There were no great differences in the GFR estimated using other formulas. Logistic regression analysis was carried out to determine the most sensitive formula for estimating GFR to assess the risk of CVEs in the patients within a year after MI concurrent with and without type 2 DM. A univariate analysis showed that GFR calculations using the CKD-EPI (odds ratio (OR), 13.5; p=0.046) and MDRD (OR, 6.5; р=0.040) formulas and creatinine clearance estimation (OR, 2.4; p=0.025) were most sensitive in selecting MI patients without DM and with poor outcomes. This analysis revealed that GFR estimates using the Hoek formula from cystatin C levels (OR, 6.15; p=0.018) were most sensitive for patients with MI concurrent with type 2 DM. In both models, multivariate analysis included none of the analyzed indicators. CONCLUSION: To estimate cardiovascular risk in the long-term post-infarction period, the CKD-EPI formula in the patients without type 2 DM and the Hoek formula from cystatin C levels were noted to be of the greatest prognostic value in patients with DM.