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PATIENTS WITH ACUTE CORONARY SYNDROME
Axmadjonova D.A.
Assistant Andijan State Medical Institute
Abstract
. ACS covers a range of conditions that include patients with recent changes in
clinical symptoms or signs, with or without changes on the electrocardiogram (ECG), and
with or without a sharp increase in cardiac troponin (cTn) concentrations. ACS is associated
with a wide range of clinical manifestations, including both asymptomatic patients and
patients with persistent symptoms of chest pain or discomfort, as well as patients with
cardiac arrest, electrical or hemodynamic instability, and cardiogenic shock [2]. Due to
significant successes in the organization of medical care for patients with ST-segment
elevation ACS (ST ACS), the introduction of percutaneous coronary interventions (PCI) into
widespread practice, over the past few years, it has been possible to reduce in-hospital
mortality from this pathology [3]. However, the mortality rate of patients with ACS,
especially with cardiogenic shock, is still high [4, 5]. Moreover, most of the deaths occur in
the early stages of the onset of ACS, i.e., in the first 24 hours of the patient's hospitalization
[3]. For this reason, when ST-elevation ACS or non-ST-elevation ACS (ST-elevation)
develops, the physician needs a "tool" to predict the risk of death, in order to make quick
decisions and optimize patient management. To date, such a "tool" for assessing the risk of
an adverse outcome in patients is scales based on multivariate analysis, the strength and
significance of which are confirmed by ROC analysis [4]. Currently, there are many scales
and methods for assessing the risk of death (GRACE, TIMI, PURSUIT, EuroSCORE II,
RECORD), however, they mainly take into account well-known "classical" risk factors [8,
9]. However, when analyzing the research data, it should be noted that the search for
universal predictors for assessing the risk of in-hospital mortality continues, combining a
number of criteria: ease of use, taking into account the impact of comorbidity, as well as the
results of laboratory and instrumental research methods [5]. That is why the establishment of
a set of prognostic factors can help optimize risk stratification and accurately assess the
probability of death at the hospital stage.
Key words:
ACS, predictors, lethality, comorbidity.
Materials and methods.
A sequential retrospective analysis was carried out that included
212 patients with ACS (n=101 – the main group of patients who died in hospital, n=124 –
the control group) hospitalized in the Department of Emergency Cardiology of the Regional
Vascular Department for the period from January 2022 to July 2024. The criteria for
inclusion of patients in the study were men and women aged 18 years and older with an
established diagnosis of ST ACS or ST ACS. Exclusion criteria: acute myocardial
infarction, which has become a complication of PCI or coronary artery bypass grafting. An
analysis of the clinical and demographic characteristics of patients with ACS was carried out:
gender, age, timing of admission to the PCI center, blood pressure (BP), heart rate (HR), etc.;
general clinical and biochemical blood analysis; the results of electrocardiography with ST-
segment evaluation, inversion of the T wave and the appearance of a pathological Q wave in
two or more adjacent leads; data obtained by transthoracic echocardiography and coronary
angiography. Statistical processing of the data was performed using Statistica version 10.0
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and MedCalc version 20.0. For each sample, the hypothesis about the normality of the
distribution of indicators was tested using the Shapiro-Wilk test.
Results
. As a result of data processing and comparative analysis, the following statistically
significant differences were obtained between the main group of patients who died in the
hospital and the control group: patients from the study group were older – the mean age was
73±10.2 years versus (vs 63.2±9.2 years in the control group (they refused coronary
angiography (CAG) followed by possible stenting of the infarction-associated artery, which
turned out to be an independent fatal predictor for patients with ACS (OR 159.34 (95% CI
21.41–1185.49); p<0.0001). It was also found that CAG was not performed in 20 patients
from the study group (20 (20%) patients out of 101) for other reasons, two of whom
underwent TLT. Thus, the overall percentage of correctly classified cases is 88.00%, which
indicates the high statistical significance of the multivariate prognostic model. This model,
evaluated using ROC analysis (Fig. 1), has a high predictive potential: AUC – 0.957 (95%
CI 0.921–0.979; p0.3756 increases the risk of in-hospital mortality, and the value of ≤
0.3756 is associated with a low risk of in-hospital mortality in patients with ACS.
Discussion.
Diagnosing ACS is not an easy task. Even the typical symptoms of ACS have
low sensitivity and specificity. For example, among patients admitted to the hospital with
chest pain characteristic of ACS, only 50% later confirmed the diagnosis of AMI or unstable
angina; at the same time, 30–50% of patients with AMI do not have typical chest pain.
Despite this, it is possible to assume the fact of the development of ACS in a patient only on
the basis of an analysis of complaints (there are no other ways yet), but for this it is
necessary to obtain the most complete anamnestic information. Analysis of the sensitivity
and specificity of individual symptoms of ACS has shown that it is impossible to diagnose
only one symptom. Localization and nature of pain. Typical symptoms of ACS include
squeezing, tightening, pressing or burning pain behind the sternum in the depth of the chest.
The pain does not have clear boundaries and is protracted - it lasts 10-20 minutes or more.
Often, chest pain in ACS has a characteristic radiation to the left arm, left shoulder, throat,
lower jaw, epigastric region, as well as to the back, the pain can migrate. In some cases,
ACS pain is localized only in the areas of irradiation, and there is no pain in the chest.
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