Prediction of adverse outcomes in the long-term follow-up period in patients with chronic heart failure who have suffered a myocardial infarction

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Introduction. Over the past two decades, chronic heart failure (CHF) has become an "epidemic." By now, CHF has a very wide prevalence worldwide and covers more than 60 million people, and according to experts, the number of people with this pathology will increase [1]. Ongoing scientific research has allowed us to accumulate an impressive array of data concerning not only the pathophysiology of heart failure (HF), but also the possibilities of surgical and drug treatment and prevention. However, despite the achievements of modern medicine, this pathology is still associated with significant morbidity and mortality, especially among the older age group [2-3].

The left ventricular ejection fraction (LVEF) is a fundamental factor for risk stratification in patients with coronary heart disease (CHD), in particular, after a myocardial infarction. However, being within the normal range, it does not allow us to fully recognize the degree of deformational changes in the myocardium. Currently, there is quite convincing evidence of the prognostic significance of global longitudinal LV deformity (GLS), which is more valuable than LVEF in terms of stratification of risks of adverse clinical outcomes in various groups of patients with cardiovascular diseases. It is noteworthy that GLS is an independent predictor of death, left ventricular remodeling, and HF hospitalization in patients with aortic stenosis, acute myocardial infarction (MI), and congestive heart failure, however, despite this, the indicator is not widely used in clinical practice [4-6].

Numerous studies on postinfarction myocardial remodeling confirm a close relationship between biological markers of endothelial dysfunction, fibrosis, and inflammation and the development/progression of HF [7-8]. However, despite the widespread knowledge of the processes underlying HF, the study of the prognostic capabilities of BM, reflecting the ongoing structural and functional changes in the cardiovascular system, in particular during the development of MI, in relation to the development of adverse cardiovascular events in both the short and long term remains one of the priorities in modern cardiology [9].

The most commonly used B-type natriuretic peptides in clinical practice, in particular, the N-terminal precursor of the brain natriuretic peptide (NT-proBNP), which are very useful in diagnosis, risk stratification and determining optimal treatment, have well-known limitations, since their level is influenced by factors such as renal dysfunction, age obesity, atrial fibrillation, as well as a number of other cardiac and noncardiological diseases [10].

Growth stimulating factor ST2 is a member of the interleukin (IL)-1 receptor superfamily, which exists in two forms: transmembrane receptor (ST2L) and soluble receptor (sST2). The natural ligand of ST2 is IL-33. Due to the complex action that IL-33 has on tissue damage and inflammation, it is involved in the pathogenesis of a number of diseases (e.g., allergies, autoimmune diseases, cancer, atherosclerosis, and diabetes). Most importantly, IL-33 plays a cardioprotective role, preventing myocardial fibrosis and hypertrophy in response to mechanical stress using ST2L. Myocardial injury or mechanical stress stimulates the release of sST2, which competes with ST2L for IL-33 binding, inhibiting the positive effects caused by the ST2L/IL-33 interaction, so that excess sST2 can contribute to the development of myocardial fibrosis and ventricular remodeling [11].

It has been proven that sST2 provides important information about the prognosis of HF (acute and chronic), and it is less affected by kidney function, age, body mass index, and etiology of the disease than by natriuretic peptides. Although sST2 is still not widely used, it can be easily and repeatedly measured in emergency situations and in everyday clinical practice [11].

Thus, GLS and sST2 represent promising tools that can significantly improve risk stratification and diagnostic and therapeutic support for patients admitted to emergency departments.

The aim of the study was to determine the prognostic significance of GLS and sST2 in patients with CHF who underwent MI during the annual follow-up period.

Material and methods: The study was conducted at the bases of cardiology departments No. 1 and No. 2 of the Samara State Medical University Clinics in the period from 2021 to 2022. The study included 96 patients with CHF who were admitted to the hospital for emergency indications in the acute period of myocardial infarction, no more than 24 hours ago.

Inclusion criteria: age of patients over 18 years old; signing of voluntary informed consent by the patient to participate in the study; previously diagnosed with "Chronic heart failure" of functional classes I, II and III; established diagnosis of "Myocardial infarction" at the time of signing the informed consent; coronary angiography (CAG).

Criteria for non-inclusion: decompensated diabetes mellitus (DM); confirmed autoimmune diseases; burdened oncological history; decompensated renal or hepatic insufficiency; diseases of the blood system; history of coronary artery bypass grafting (CABG); other factors of change in myocardial geometry (refractory arterial hypertension (AH), hemodynamically significant congenital and acquired heart defects, dilated and ischemic cardiomyopathy).

Diagnoses of MI and CHF were established according to current clinical guidelines [12-14].

The clinical and anamnestic characteristics of the patients are presented in Table 1. Among the participants included in the study, males predominated, with a median age of 64.5 (57; 72.3) years. The vast majority of patients had a history of arterial hypertension (AH), as well as CHF of NYHA functional class II. They were previously reported in 25 (26%) of the subjects, and 7 (7.3%) had acute cerebrovascular accident (CVD). 18 (18.8%) people were diagnosed with diabetes. The most common (61.6% of cases) Q-forming MI was registered in the study participants, the frequency of anterior localization of MI was 46.9%. Signs of acute heart failure (ARF) according to the Killip II-III classification occurred in 14.6% of patients. The rhythm of atrial fibrillation (AF) was recorded in 10 patients, while 8 of them had it as a complication of the current MI. The median score on the scale of assessment of the clinical condition of a patient with CHF (SHOCK) was 5 (3; 6).

Inpatient treatment was also carried out in accordance with current clinical guidelines [12-14]. According to them, drug therapy in patients at the time of inclusion in the study contained: antiplatelet agents, anticoagulants (as indicated), beta-blockers (BAB), statins, angiotensin converting enzyme inhibitors (ACE inhibitors) or sartans, mineralocorticoid receptor agonists (AMP), loop diuretics, calcium channel blockers (CCBs) (table 1). All patients with AF received oral anticoagulants.

Based on the CAG data, the current condition of the coronary bed was assessed: damage to the trunk of the left coronary artery was assessed, the PA – the anterior descending artery, the OA – the circumflex branch, the PA – the right coronary artery, and then the severity of damage to the coronary bed was assessed on the Syntax scale. If stenosis was detected, more than 70% of the coronary artery lesion was assessed as significant. Stenosis of more than 50% was considered to be a hemodynamically significant lesion for the PA and the LCA trunk. Further, taking into account the clinical and angiographic picture, as well as the patient's consent, surgical tactics and timing of the intervention (CABG and/or stenting of the symptom-dependent artery) were determined.

During CT, 58 (60.4%) of the examined patients had a three–vessel lesion of the coronary bed, 24 (25%) patients had a hemodynamically significant lesion of two coronary arteries, 20 (20.8%) had a lesion of the LCA trunk. Percutaneous coronary intervention (PCI) was performed in more than 60% of cases. Further surgical tactics in the form of CABG were determined by 24 (25%) subjects; PCI in the second stage was recommended for 34 (35.4%) patients; conservative was indicated for 38 (39.6%) subjects (Table 1).

 

Characteristic

Abs.number

%

Gender

female

31

32.3

male

65

67.7

PIX

25

26

Smoking

3

3.1

AG

90

93.8

SD

18

8.8

ONMC

7

7.3

fp

10

10,4

FC HCN (NYHA)

II

88

91.7

III

8

8.3

Severity of OSN (according to Killip)

I

82

85.4

II

8

8,3

III

6

6,3

The view is

without the Q prong

59

61.5

with Q prong

37

38,5

Localization of IM

anterior wall of LV

45

46,9

posterior wall of LV

51

53.1

Prescribed therapy

YES.

94

97.9

Statins

93

96,9

Ace inhibitors/sartans

87

90,6

WOMEN

90

93.8

AMPS

70

72,9

Loop diuretics

52

54.2

BCC

33

34,4

Results of angiographic examination

PCI was performed in hospital

61

63.5

Surgical tactics at discharge

CABG is shown

24

25

PCI stage II is shown

34

35.4

Conservative management is shown

38

39,6

Table 1. Clinical and anamnestic characteristics of patients included in the study (n=96) Note: PIX – postinfarction cardiosclerosis; DAAT – dual antiplatelet therapy

Table 1. Clinical and anamnestic characteristics of the patients included in the study (n=96)

 

On the second day of hospitalization, patients underwent venous blood sampling to determine concentrations of such drugs as sST2 (Presage ST2 Assay test system from Critical Diagnostics, USA), vascular endothelial growth factor (VEGF) (Human VEGF-A ELISA Kit, Bender MedSystems GmbH, Austria) and NTproBNP (the NT-proBNP test system, Biomedica, Austria). Studies of indicators of general and biochemical blood analysis, as well as hemostasiograms, lipidograms, and C-reactive protein (CRP) were conducted as part of routine clinical practice.

The electrocardiogram was recorded on a CardiovitAT 2 "Schiller" device (country of origin: Switzerland) in twelve standard leads.

Echocardiography (EchoCG) and speckle-tracking (speckle-tracking) EchoCG in 2-dimensional mode were performed on a Philips EPIQ 5 device (USA) in accordance with the Recommendations of the American Echocardiographic Society and the European Association for Cardiovascular Imaging [15].

In addition, laser Doppler fluorometry (LDF) was performed on all patients during the hospital period using a laser microcirculation analyzer for a general practitioner named LACK-OP (Lazma Scientific and Production Enterprise LLC, Moscow, 2010).

During the first stage of the study, no cases of hospital mortality were reported. The second stage was a telephone survey to assess the course of the disease and the clinical outcome over a period of 12 months. The combined endpoint (CCT) in the work is reflected by cases of death (due to cardiovascular pathology) of patients and relapses of cardiovascular events: stroke, new cases of MI, unstable angina (NS), as well as hospital admissions due to decompensation of CHF.

Statistical data analysis was performed using the environment for statistical computing R 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). Descriptive statistics are presented in the form of absolute and relative frequencies for qualitative variables, medians (Me) with an interquartile range (Q1; Q3) for quantitative variables. Intergroup differences for quantitative variables were assessed using the Mann-Whitney test between two independent samples; for categorical variables, the Fisher exact test. The prognostic factors for the occurrence of repeated events were determined using a one-factor regression analysis with the calculation of the odds ratio (OR) and the determination of its 95% confidence interval (CI). The prediction of criteria in the study was also evaluated when performing a ROC analysis (Receiver Operator Characteristic, operational characteristic curve), during which the Area Under Curve (AUC) indicators were calculated.

Результаты исследования: В течение 12 месяцев наблюдения развитие ККТ зарегистрировано у 44 (45,8%) участников исследования: сердечно-сосудистая смертность имела место в 2 (2,1%) случаях, 8 (8,3%) пациентов были госпитализированы по поводу нестабильной стенокардии и столько же – по поводу развития повторного ИМ, 24 (25%) человека госпитализировались в связи с декомпенсацией ХСН и 2 (2,1%) – в связи с развитием ОНМК. На этом основании были выделены группы пациентов: с благоприятным и неблагоприятным течением отдаленного постинфарктного периода.

При оценке влияния клинико-анамнестических характеристик на вероятность развития повторных сердечнососудистых событий (ККТ) в течение 12 месяцев с момента включения пациентов в исследование не было выявлено статистически значимых ассоциаций с полом, возрастом, видом и локализацией ИМ, тяжестью ОСН по Killip, проведением ЧКВ в госпитальный период, наличием в анамнезе перенесенного ИМ, СД, АГ, ОНМК, а также наличием ФП и по ФК ХСН по nyha (р>0,05 во всех случаях) (таблица 2).

 

Показатель

Нет ККТ,

n=52

Развитие ККТ,

n=44

ОШ

(95%ДИ)

р

Медиана возраста, лет

61,5 (56,5; 72)

66 (59,5; 73)

1,02 (0,98; 1,07)

0,257

Мужской пол, n (%)

35 (67,3)

30 (68,2)

1,04 (0,44; 2,46)

0,927

SD, n (%)

10 (19,2

8 (18,2)

1,08 (0,4; 2,95)

0,881

∆ P, n (%)

7 (13,5)

3 (6,8)

0,47 (0,11; 1,94)

0,288

ОНМК в анамнезе, n (%)

3 (5,8)

4 (9,1)

1,63 (0,35; 7,73)

0,533

Количество в анамнезе, n (%)

12 (23,1)

13 (29,5)

1,4 (0,56; 3,49)

0,472

AG, n (%)

50 (96,2)

40 (90,9)

0,4 (0,07; 2,3)

0,29

Q-общий объем, n (%)

17 (32,7)

20 (45,5)

1,72 (0,74; 3,93)

0,2

Средний ИМ, n (%)

24 (46,2)

21 (47,7)

1,07 (0,48; 2,38)

0,878

Коэффициент полезного действия II–III, n (%)

5 (9,6)

9 (20,5)

2,42 (0,75; 7,85)

0,134

Доля в общей численности населения,

n (%)

34 (65,4)

27 (61,4)

0,84 (0,37; 1,94)

0,683

Таблица 2. Клинико-анамнестические факторы, влияющие на развитие неблагоприятных сердечно-сосудистых событий в течение 1 года

Таблица 2. Клинико-анамнестические факторы, влияющие на развитие неблагоприятных сердечно-сосудистых событий в течение 1 года

 

Однако у пациентов, имевших неблагоприятный клинический исход в годовом периоде наблюдения, регистрировался статистически значимо более высокий балл по ШОКС (5 (4; 7) против 4 (3; 5) у пациентов с благоприятным течением отдаленного постинфарктного периода, р<0,001). При регрессионном анализе было выявлено, что высокий балл по ШОКС являлся значимым предиктором развития повторных сердечнососудистых событий у пациентов с ХСН в течение года после перенесенного ИМ (ОШ=1,44 (95% ДИ: 1,17; 1,82), Р=0,001).

При сравнительном анализе основных эхокардиографических показателей и результатов КАГ (таблица 3) было установлено, что в случае развития неблагоприятных сердечнососудистых событий пациенты исходно имели статистически значимо более низкие показатели фракции выброса левого желудочка (ФВ ЛЖ) и глобальной продольной деформации ЛЖ (ГЛС), а также статистически значимо более высокие показатели конечного систолического (КСР) и диастолического (КДР) размеров ЛЖ, конечного систолического объема ЛЖ (КСО), индекса массы миокарда ЛЖ (ИММ ЛЖ), индекса нарушения локальной сократимости (ИНЛС), базовый диамет выводного тракта LZH (ВТ ЖЖ), он же более высокий балл по синтаксису. Кроме того, у пациентов с неблагоприятным отдаленным исходом значимо чаще (70,5%) выявлялась диастолическая дисфункция ЛЖ (ДД ЛЖ). Статистические данные, свидетельствующие о том, что программы развивают правительственные средне-государственные компании (oШ (95% DI) – 0,9 (0,84; 0,95), р<0,001), КДР, КСР, КСО, базовый показатель ВТЖ (∆ (95% ДИ) – 1,08 (1; 1,18), r=0,045), GLS (оШ (95% ДИ) – 0,37 (0,26; 0,54), r<0,001), IM LJ (оШ (95% ДИ) – 1,02 (1; 1,04), r=0,018), INLS (оШ (95% ДИ) – 4,6 (1,55; 15,4), r=0,009), скорость трехполюсной регуляции (Втр) (oШ (95% ДИ) – 3,27 (1,09; 9,82), r=0,033), наибольшее значение (oШ (95% ДИ) – 2,39 (1,02; 5,55), r=0,042) и количество баллов по Синтаксис шkale (О (95% DI) – 1,2 (1,13; 1,29), r<0,001) (таблица 4). Примечательно, что ни количество пораженных коронарных артерий, ни наличие гемодинамически значимого поражения ствола ЛКА не оказывали значимого влияния на отдаленный прогноз пациентов после перенесенного ИМ.

 

Показатель

Нет ККТ, n=52

Рост ККТ, n=44

прибыль

(95%)

прибыль до налогообложения

ФВ ЛЖ*, %

54 (49,5; 57,7)

48 (39; 54)

<0,001

0,9 (0,84; 0,95)

<0,001

КДР*, мм

48 (44,5; 50)

51 (48; 53,5)

0,002

1,11 (1,02; 1,21)

0,018

КСР*, мм

33 (30; 37)

36 (32; 42)

0,004

1,09 (1,02; 1,17)

0,013

КДО*, мл

118,5 (106,5; 139)

129 (114; 151,5)

0,15

1,01 (0,99; 1,02)

0,261

Совокупный доход (KCO)*, млн.

55 (45,5; 70,5)

65,5 (56; 86,5)

0,003

1,03 (1,01; 1,05)

0,013

Диаметр ВТ ЛЖ, мм

проксимальный*

28,5 (27; 31)

30 (27; 32)

0,416

1,06 (0,95; 1,19)

0,273

дистальный*

25 (25; 26,5)

25 (24; 26,5)

0,732

0,98 (0,86; 1,11)

0,748

базальный *

35 (32; 38)

38 (35; 40)

0,01

1,08 (1; 1,18)

0,045

средний*

29,5 (27; 31)

30 (27; 32)

0,744

1,02 (0,92; 1,14)

0,699

GLS (ГЛС)*, %

19,8 (18,45; 20,3)

16,65 (15,1;17,65)

<0,001

0,37 (0,26; 0,54)

<0,001

ИММ ЛЖ*, г/м2

100 (80,5; 110,35)

107 (97,5; 124)

0,013

1,02 (1; 1,04)

0,018

ИНЛС*

1,19 (1; 1,4)

1,41 (1,1; 1,8)

0,008

4,6 (1,55; 15,4)

0,009

Объем ЛП*, мл

62 (53,5; 68)

65,5 (57; 79,5)

0,089

1,02 (0,99; 1,04)

0,202

ДЛАсист. *, мм рт.ст.

30,5 (27; 35,5)

32,5 (27,5; 40,5)

0,145

1,05 (1; 1,1)

0,073

ИО ЛП*, мл/м2

334 (28; 40)

335 (30,75; 42,33)

0,264

1,0 (0,98; 1,01)

0,526

ИО ПП*, мл/м2

25,2 (22; 28)

26,6 (22,8; 30,55)

0,197

1,01 (0,96; 1,07)

0,639

Втр*, м/с

2,39 (2,22; 2,6)

2,53 (2,25; 2,8)

0,094

3,27 (1,09; 9,82)

0,033

Количество дней, n (%)

26 (50)

31 (70,5)

0,042

2,39 (1,02; 5,55)

0,042

Синтаксис*, баллы

15,5 (8,5; 21,25)

38 (31; 41)

<0,001

1,2 (1,13; 1,29)

<0,001

Количество пораженных коронарных артерий

Общественное мнение, n (%)

11 (21,2)

3 (6,8)

0,14

1,58 (0,96; 2,74)

0,081

Акустическое отображение, n (%)

12 (23,1)

12 (27,3)

 

 

 

Пространственное отображение, n (%)

29 (55,8)

29 (65,9)

 

 

 

Изменение структуры РЫНКА, n (%)

11 (21,2)

9 (20,5)

0,933

0,96 (0,35; 2,58)

0,933

Таблица 3. Руководящий состав коллегиально-графических органов и аналитиков как в системе управления от развития ККТ, так и за ее пределами. Примечание: * - значение информация представлена здесь (Q1; Q3); КДО – постоянный системный пользователь; ЛП - левое окружение; администратор. – систолическое давление в легочной артерии; ИО ЛП – индексированный объем левого предсердия; ИО ПП – индексированный объем правого предсердия

Таблица 3. Сравнительный анализ эхокардиографических параметров и результатов коронарографии в зависимости от развития КЭП

 

When analyzing the microcirculation parameters obtained during LDF, it was found that patients who developed repeated adverse cardiovascular events during 12 months of follow-up initially had statistically significantly lower values of the microcirculation index (PM), indicators of the amplitudes of blood flow fluctuations in myogenic (Am), neurogenic (Ah) and endothelial (Ae) frequency ranges, the respiratory test index (IDP) and the Hurst index (R/S), as well as statistically significantly higher rates of capillary blood flow reserve (RCC) (Table 4). The data obtained indicate that patients with an unfavorable prognosis had more pronounced microvascular hemodynamic disorders during the year, as well as a decrease in the amplitude-frequency spectrum of perfusion fluctuations.

The chances of developing repeated cardiovascular events during the year were statistically significantly associated with IDP (OR (95% CI) – 0.81 (0.66; 0.97), p=0.025) and RCC (OR (95% CI) – 1.15 (1.05; 1.27), p=0.005). In addition, with an increase of 0.1 units in the Ae index, the odds ratio of developing an unfavorable outcome was 0.58 (95% CI: 0.37; 0.88), Ah – 0.32 (95% CI: 0.14; 0.67), Am – 0.52 (95% CI: 0.32; 0.8), R/S – 0.62 (95% CI: 0.39; 0.96) and D2 – 0.68 (95% CI: 0.46; 0.97).

 

Indicator

No CCT, n=52

Development of CCT, n=44

p

OR (95% CI)

p for

OR PM, pf units

15.3 (14.4; 16.3)

14,5 (13,7; 15,9)

0,042

0,76 (0,57; 1)

0,055

Kv, %

6,93 (5,06; 8,51)

6,18 (4,73; 7,81)

0,194

0,89 (0,75; 1,06)

0,205

Ae, pf.ed.

0,58 (0,52; 0,64)

0,52 (0,44; 0,61)

0,007

0,58 (0,37; 0,88)

0,013

An, pf.ed.

0,57 (0,54; 0,61)

0,54 (0,48; 0,57)

0,002

0,32 (0,14; 0,67)

0,004

Am, pf.ed.

0,51 (0,44; 0,55)

0,42 (0,37; 0,51)

0,002

0,52 (0,32; 0,8)

0,004

IDP, %

35,5 (34,2; 37)

34,2 (32,6; 38,7)

0,038

0,81 (0,66; 0,97)

0,025

RKK, %

127 (124; 129)

130 (125; 133)

0,008

1,15 (1,05; 1,27)

0,005

Sm, conl.units.

4,35 (4,03; 4,6)

4,08 (3,87; 4,65)

0,175

0,58 (0,22; 1,46)

0,249

I, conl.units

33.7 (30.8; 36)

32,1 (29,8; 34,7)

0,229

0,95 (0,85; 1,05)

0,282

R/S

0,47 (0,4; 0,52)

0,4 (0,32; 0,48)

0,02

0,62 (0,39; 0,96)

0,036

H0

0,34 (0,31; 0,38)

0,34 (0,3; 0,36)

0,197

0,58 (0,24; 1,39)

0,23

D2

1,43 (1,36; 1,5)

1,39 (1,25; 1,49)

0,063

0,68 (0,46; 0,97)

0,039

Table 4. Comparative analysis of microcirculation parameters depending on the development of CCT Note: the values of the indicators are presented in the form of Iu (Q1; Q3); Kv is the coefficient of variation; Sm is an indicator of relative perfusion oxygen saturation in the bloodstream; I is an indicator of specific oxygen consumption in tissues; H0 is relative entropy; D2 is the correlation dimension of the phase portrait

Table 4. Comparative analysis of microcirculation parameters depending on the development of

 

When analyzing the levels of the main laboratory parameters depending on the development of adverse cardiovascular events during the year from after the index MI, it was found that in patients with unfavorable outcomes, the levels of CRP, NTproBNP and sST2 were significantly higher, and the estimated glomerular filtration rate (GFR) was significantly lower compared with patients with a favorable course the long-term follow-up period (Table 5). Statistically significant predictors of repeated events were the GFR value calculated using the CKD-EPI formula (OR (95% CI) – 0.95 (0.92; 0.98), p=0.006), glucose levels (OR (95% CI) – 1.17 (1.01; 1.36), p=0.029), CRP (OR (95% CI) – 1.06 (1.02; 1.11), p=0.004), NT-proBNP (OR (95% CI) – 1.03 (1.02; 1.08), p<0.001) and sST2 (OR (95% CI) – 1.13 (1.07; 1.2), p<0.001).

 

Indicator

No CCT (n=52)

Development of CCT (n=44)

p

OR (95% CI)

p for OR

Glucose, mmol/l

6,0 (5,3; 7,3)

6,6 (5,6; 8,4)

0,06

1,17 (1,01; 1,36)

0,029

Troponin, pg/ml

708,5 (174; 2283,1)

616,4 (89,8; 3205,5)

0,953

1,0 (1,0; 1,0)

0,146

CFRP, UNITS/l

306,9 (120; 778,2)

315,5 (143,5; 796,8)

0,678

1,0 (1,0; 1,0)

0,707

CFRP MV, UNITS/l

31,1 (21,3; 70,6)

47,5 (21,3; 77,8)

0,617

0,99 (0,82; 1,0)

0,439

GFR CKD-EPI, ml/min/1.73 m2

77 (74; 80)

67 (61; 77)

0,003

0,95 (0,92; 0,98)

0,006

OH, mmol/l

5,1 (4,4; 5,65)

5,05 (4,75; 5,4)

0,8

0,86 (0,58; 1,22)

0,396

LDL, mmol/l

3,07 (2,58; 3,9)

3,28 (2,74; 3,32)

0,376

0.94 (0.61; 1.42)

0.759

PPM, mg/l

14,9 (7,9; 21,1)

22,3 (12,5; 31,9)

0,004

1,06 (1,02; 1,11)

0,004

NT-proBNP, pg/ml

192,4 (111,2; 517,8)

1339,7 (605,4; 1886,9)

<0,001

1.03 (1.02; 1.08)

<0.001

sST2, ng/ml

27,2 (21,3; 34,8)

45,8 (37; 63,4)

<0,001

1,13 (1,07; 1,2)

<0,001

VEGF, pg/ml

387 (187,5; 461,6)

249,7 (153,8; 370)

0,116

0,79 (0,53; 1,17)

0,248

Table 5. Levels of basic laboratory parameters depending on the development of CT

Table 5. Levels of the main laboratory parameters depending on the development of

 

Thus, the development of adverse cardiovascular events in patients with CHF who underwent MI during the following year is associated with a decrease in global LV deformity, severity of coronary atherosclerosis, microcirculation disorders, renal dysfunction, hyperglycemia, and an increase in BM such as CRP, NTproBNP, and sST2, while clinical and anamnestic characteristics They fade into the background as predictors of long-term adverse outcomes.

To predict the risk of recurrent cardiovascular events, a mathematical model was developed using a step-by-step selection of predictors that have shown their importance in the development of the combined endpoint according to single-factor analysis, as well as predictors with an extensive evidence base in relation to riskometry, with an exception based on the Akaike information criterion (AIC). The analysis included predictors that showed their prognostic significance according to a single-factor analysis, as well as generally accepted risk factors with an extensive evidence base: the patient's age and gender, the presence of a history of diabetes, previous history of diabetes, type of MI and severity of acute respiratory failure according to the Killip classification, the number of SHOCK and Syntax scores, the number of affected coronary arteries, the values of LVEF, GLS, LV IMM, INLS, CDR, CSR, CSR, the basal diameter of LV VT and Vtr, the presence of LV DD, the values of IDP and RCC, the values of the Hurst index, the correlation dimension of the phase portrait and the amplitude-frequency spectrum of perfusion oscillations, as well as the concentrations of glucose, CRP, NT-proBNP, sST2, OHC and LDL, and the GFR level calculated using the CKD-EPI formula.

As a result of the analysis, the final model (Table 6) included such factors as the GLS value, the number of points on the Syntax scale, the levels of NTproBNP and sST2. The risk ratio (HR) for NTproBNP was 2.9 (1.45; 5.1), for the Syntax scale – 3.05 (2.2; 6.8), for sST2 – 3.3 (1.65; 7.51), for GLS – 0.51 (0.39; 0.72).

 

The predictor

β (SE)

OR

95% CI

p

VIF

The constant

1,32

-

-

-

–

NTproBNP, ng/ml

0,012

2,9

1,45; 5,1

0,018

1,34

GLS, %

-0,74

0,51

0,39; 0,72

0,032

1,27

Syntax, points

0.13

to 3.05

2,2; 6,8

0,002

1.05

sST2, ng/ml

0.15

3,3

1,65; 7,51

0,041

1,08

Table 6. Coefficients in the obtained model for predicting the risk of recurrent cardiovascular events

Table 6. Coefficients in the model for predicting the risk of recurrent cardiovascular events

 

The resulting model was characterized by a Nigelkerke pseudo-R2 value of 0.7 (adjusted value – 0.66), a Sommers DXY coefficient of 0.89 (adjusted value – 0.86) and an AUC of 0.94 (95% CI: 0.89–0.97) (adjusted value – 0.93) (Figure 1).

 

 

Drawing 1. ROC curve for predictions obtained using the model

Figure 1. ROC-curve for predictions obtained using the model

 

Based on the results of multifactorial regression analysis, we derived the regression equation using the following mathematical formula:

P=1/ (1+e-(Bo + B1*x1 + B2*x2 + B3*x3 + B4*x4)), in which

e is the base of the natural logarithm (2,718);

First– the constant (1.32);

B1 is the coefficient for NTproBNP (0.012);

B2 is the coefficient for GLS (-0.74);

B3 is the coefficient for the number of Syntax points (0.13);

B4 is the coefficient for sST2 (0.15);

x1 is the concentration of NTproBNP, pg/ml;

x2 is the GLS value, %

x3 is the number of points on the Syntax scale;

x4 is the concentration of sST2, ng/ml;

Thus, this equation can be written as:

P=1/ (1+e-(1.32 + 0.012*x1 - 0.74*x2 + 0.13*x3 + 0.15*x4).

For the convenience of using the presented formula, a calculator was developed based on it to calculate the probability of developing repeated cardiovascular events in patients with CHF within a year after they suffered. After entering the required parameters (concentrations of NTproBNP and sST2, the number of points on the Syntax scale and the GLS value), the program outputs the result of the probability of developing adverse outcomes within 12 months in % (Figure 2).

 

 

Figure 2. An example of using a calculator for riskometry in patients with CHF who have had MI

Figure 2. Example of using a calculator for riskometry in patients with CHF who have had MI

 

When using 60% of the predicted probability of an event as the threshold value, the resulting model was characterized by 87.5% (95% CI: 84.2; 91.3) accuracy, 81.8% (95% CI: 72.6; 90.8) sensitivity and 92.3% (95% CI: 87.8; 98.1) specificity. The prognostic value of a positive result was 92.3% (95% CI: 83.9; 96.4).

 

Discussion of the results.

Heart failure (HF) is a complex clinical syndrome that occurs in various diseases, including myocardial infarction (MI), characterized by pathological changes in the structure and/or function of the heart [16].

Currently, there are many studies confirming the prognostic significance of various predictors of an unfavorable outcome in patients with HF, which include data from echocardiography, exercise tests, and levels of BM such as NTproBNP, galectin-3, highly sensitive troponin T, and CRP. However, despite the identification of many prognostic markers, clinical decision-making in CHF is still based primarily on such parameters as the presence of symptoms of heart failure (NYHA class), LVEF, duration and morphology of the QRS complex [17].

Despite the fact that LVEF is an important indicator in the diagnosis and monitoring of patients with CHF, in some cases, the assessment of LVEF may not be informative enough and may not reflect the severity of the clinical condition, in particular in the onset of HF. Recent studies report that myocardial tension is a more sensitive parameter for assessing cardiac function than LVEF. So, P. Janwetchasil and co-authors investigated the prognostic value of global longitudinal deformation of the left ventricle (GLS) using magnetic resonance imaging of the heart in patients with known or suspected coronary artery disease with preserved systolic function of the left ventricle. Multifactorial analysis showed that patients with GLS of less than 14.4% had a significantly higher risk of adverse cardiovascular events compared to patients with GLS of more than 14.4% [6]. In addition, L. Caunite et al. demonstrated that GLS improves LVEF risk stratification in patients who have had ST-segment elevation MI (STeMI). The study included 1,409 patients with STEMI, with an average follow-up period of 69 months. The cumulative 10-year survival rate was 91% in patients with improved or slightly decreased GLS, compared with 85% in patients with decreased GLS >7% within a year after the index event. In multivariate regression analysis, a decrease in GLS >7% of baseline parameters remained independently associated with endpoint development after adjustment of clinical and echocardiographic parameters of left and right ventricular function. Thus, speckle-tracking strain echocardiography can potentially improve risk stratification in patients with STEMI, even with preserved or moderately reduced LVEF at baseline and follow-up [4]. The relationship between the GLS value and the BNP level with the development of pathological remodeling after an earlier experience was demonstrated in a study by Oleinikov V. E. and co-authors. Patients with pathological LV remodeling on days 7-9 of MI had statistically significantly lower GLS values, and within 6 months the proportion of patients with low and intermediate LVEF was 24.4% and 60%, respectively. A decrease in GLS of less than 11.7% was a highly sensitive and specific predictor of the development of postinfarction pathological dilation of the left ventricle [18]. In this study, no dynamic assessment of the GLS value was performed, but only the effect of GLS on the development of long-term adverse cardiovascular events was evaluated, however, the prognostic significance of GLS was demonstrated by both single-factor and multifactorial analyses, which makes this indicator a valuable marker of early risk stratification in patients with CHF who have undergone MI, regardless of its dynamics.

Recently, the prognostic significance of ST2 and its advantages over natriuretic peptides have been actively studied. The clinical effectiveness of assessing sST2 levels in HF has been confirmed by numerous studies conducted over the past 20 years. Thus, a meta-analysis conducted in 2016, covering 7 clinical trials with more than 6,372 participants, confirmed the prognostic value of sST2 in relation to adverse outcomes in patients with CHF [19]. It is known that an increase in sST2 levels after MI has a long-term prognostic value for the development of CHF. According to clinical observations, patients with elevated sST2 levels after MI were more susceptible to subsequent maladaptive myocardial remodeling and HF progression [20]. It has also been established that sST2 is a powerful predictor of adverse clinical events in acute renal failure. Xue-Qing Guan et al. increased the predictive value for risk stratification in patients with acute renal failure over a three-year follow-up period by assessing the incidence of serious adverse cardiovascular events, defined as repeated hospitalization for heart failure and/or all-cause mortality. The authors found that the optimal threshold value for sST2 is 34 ng/ml. Patients exceeding this threshold had higher rates of readmission and mortality, which emphasized the prognostic importance of elevated sST2 levels in the study group of patients. The diagnostic value of sST2 differed in different groups of HF patients, especially in patients with a history of MI, which indicated the importance of taking into account prognostic differences between patient groups when monitoring sST2 levels in clinical practice [21].

To assess the risks of developing adverse outcomes during the year for the study cohort of patients, we proposed a mathematical model for determining the risk of recurrent cardiovascular events and death within 12 months in patients with CHF who underwent MI. In the course of a multifactorial regression analysis, the following factors were identified as independent predictors of the development of adverse clinical outcomes: the GLS value, the number of points on the Syntax scale, as well as the concentrations of sST2 and NTproBNP, determined no later than the second day after the development of MI. It is worth noting that NTproBNP has not lost its independent prognostic significance in this study. It has been proven that the inclusion of new BM in addition to well-known natriuretic peptides in multiparametric models significantly improves risk stratification, while highly sensitive troponins and sST2 appear to be more reliable BM for risk stratification [22-23].

 

Conclusion. Assessment of GLS and sST2 in patients with MI, along with assessment of the severity of coronary atherosclerosis and the level of NTproBNP, represent a promising tool that can improve early risk stratification and diagnostic and therapeutic support for patients admitted to emergency departments. The increase in sST2 levels in blood plasma is probably associated with significant activation of both neurohormonal and profibrotic mechanisms, which may help identify patients at high risk of adverse left ventricular remodeling in the early stages after MI. Thus, the use of the proposed prognostic model in clinical practice, in particular at the hospital stage, will allow not only to stratify the risk of recurrent cardiovascular events in patients with CHF after they have suffered and to identify in a timely manner those who have a high probability of developing adverse clinical events over the next year, but also to provide a more personalized approach to therapeutic and preventive measures for a specific patient.

Conclusions. 1. In patients with CHF who have undergone MI, an unfavorable annual prognosis is associated with the degree of systolic and diastolic LV myocardial dysfunction, severity of coronary atherosclerosis, microcirculation disorders, as well as increased levels of CRP, NT-proBNP, sST2 and glycemia, and decreased renal function.

2. GLS and sST2 are more sensitive markers of systolic dysfunction and fibrotic changes in the myocardium and have greater prognostic value compared to traditional risk factors for the development of recurrent cardiovascular events in the long term after MI.

3. The developed model for predicting a long-term adverse outcome within 12 months after heart failure in people with CHF includes concentrations of NTproBNP and sST2, the number of points on the Syntax scale and the GLS value and has an accuracy of 87.5% (95% CI: 84.2; 91.3), sensitivity 81.8% (95% CI: 72.6; 90.8) and the specificity was 92.3% (95% CI: 87.8; 98.1).

About the authors

Yurii А. Trusov

Samara State Medical University

Author for correspondence.
Email: yu.a.trusov@samsmu.ru
ORCID iD: 0000-0001-6407-3880

MD, cardiologist at the Clinics of SamSMU, assistant at the Department of Propaedeutic Therapy with a course in cardiology

Russian Federation, Samara

Yurii V. Shchukin

Samara State Medical University

Email: yu.v.shchukin@samsmu.ru
ORCID iD: 0000-0003-0387-8356

MD, Dr. Sci. (Medicine), Professor, Professor of the Department of Propaedeutic Therapy with a course in Cardiology

Russian Federation, Samara

Larisa V. Limareva

Samara State Medical University

Email: l.v.limareva@samsmu.ru
ORCID iD: 0000-0003-4529-5896

MD, Dr. Sci. (Medicine), Head of the Laboratory of Flow Cytometry

Russian Federation, Samara

References

Supplementary files