Assessment of prevalence and monitoring of outcomes in patients with heart failure in Russia

Шляхто, Е. В.; Звартау, Н. Э.; Villevalde, S.; Яковлев, А. Н.; Soloveva, A.; Федоренко, А. А.; Карлина, В. А.; Avdonina, N.; Ендубаева, Г. В.; Зайцев, В. В.; Неплюева, Г. А.; Павлюк, Е. И.; Дубинина, М. В.; Медведева, Е. А.; Ерастов, А. М.; Панарина, С. А.; Соловьев, А. Е.

doi:10.15829/1560-4071-2020-4204

Cited by 8 publications

(3 citation statements)

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“…Точная региональная и глобальная оценка бремени заболеваний имеет ключевое значение для определения приоритетных направлений лечения, профилактики осложнений, определения потребности и планирования использования ресурсов системы здравоохранения, а также научно-исследовательской работы. Особенности статистического учета СН в сочетании с гетерогенностью данного синдрома ограничивают возможности получения точных эпидемиологических сведений о заболевании как в РФ, так и в мире [10]. В представленном исследовании реальной клинической практики, с использованием масштабной региональной базы данных, впервые в РФ выполнен анализ распространенности СН на основе кодов МКБ-10 в диагнозах по данным обращаемости.…”

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ICD-10 code-based definition of heart failure in Saint Petersburg electronic health records: prevalence, health care utilization and outcomes

et al. 2021

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Aim. To analyze prevalence of heart failure (HF), clinical and demographic characteristics, health care utilization, and outcomes according to the used International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) codes in regional integrated electronic health record database in Saint Petersburg.Material and methods. The retrospective analysis of the Saint Petersburg regional integrated electronic health record database for 2019 was performed. At least one of the following ICD-10 codes has been considered as HF case: I50.x (standard coding) and/or I11.0, I13.0, I13.2, I25.5, I42.0, I42.9, I09.9, I43.0, I43.1, I43.2, I43.8, I42.5, I42.6, I42.7, I42.8 (extended coding).Results. A total of 64070 adult patients with HF had medical encounters in 2019, 34,5% of whom were identified using standard coding, 65,5% — using extended coding. The combination of codes was observed in 9,9% of cases. HF prevalence/mortality was 1,4%/6,8% in general, as well as 0,49%/15,7% and 0,93%/2,1% with standard and extended coding, respectively. HF patients had high healthcare utilization with the mean number of 14 encounters per patient per year. Actually, 24% of patients had more than 20 both inpatient and outpatient encounters and 54% of patients — at least 1 all-cause hospitalization during the year. Encounters of patients with HF accounted for 4,3% of all visits, 6,5% of all hospitalizations, 4,1% of all outpatient visits and 9,7% of all emergency contacts during the year. Patients identified by the standard coding compared with the extended coding had older age and higher incidence of comorbidities, as well as greater hospitalization and death rates, but lower number of outpatient visits.Conclusion. The prevalence of HF among the adult population of Saint. Petersburg in 2019 was 1,4%. HF was characterized by a high health care utilization and mortality rate reaching 15,7 % per year. The use of different approaches to coding presumably could help to identify different groups of patients with HF, which requires the adaptation of healthcare models and an active monitoring system to reduce the risk of adverse events.

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ICD-10 code-based definition of heart failure in Saint Petersburg electronic health records: prevalence, health care utilization and outcomes

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“…Chronic heart failure (CHF) is one of the main causes of hospitalization and mortality in the world, including the Russian Federation [1,2]. The progressive nature of the course, early disability, the need for long-term pharmacotherapy and cardiac surgery are associated with significant economic costs for the healthcare system.…”

Section: Introductionmentioning

confidence: 99%

“…The widespread introduction of high-tech methods for the treatment of acute MI has led to a decrease in hospital mortality; this has been accompanied, however, by an increase in the number of patients with CHF [1,6]. Due to the very typical prolongation of myocardial revas cularization terms, adverse postinfarction remodeling often develops being a key pathogenetic element of CHF and a significant predictor of mortality.…”

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confidence: 99%

Prediction of Adverse Post-Infarction Left Ventricular Remodeling Using a Multivariate Regression Model

et al. 2022

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Background. In order to provide personalized medicine and improve cardiovascular outcomes, a method for predicting adverse left ventricular remodeling (ALVR) after ST-segment elevation myocardial infarction (STEMI) is needed. Methods. A total of 125 STEMI patients, mean age 51.2 (95% CI 49.6; 52.7) years were prospectively enrolled. The clinical, laboratory, and instrumental examinations were performed between the 7th and 9th day, and after 24 and 48 weeks, including plasma analysis of brain natriuretic peptide (BNP), transthoracic echocardiography, analysis of left ventricular-arterial coupling, applanation tonometry, ultrasound examination of the common carotid arteries with RF signal amplification. Results. Patients were divided into 2 groups according to echocardiography: “ALVR” (n = 63)—end-diastolic volume index (EDVI) >20% and/or end-systolic volume index (ESVI) >15% after 24 weeks compared with initial values; “non-ALVR” (n = 62)—EDVI <20% and ESVI <15%. In the ALVR group, hard endpoints (recurrent myocardial infarction, unstable angina, hospitalization for decompensated heart failure, ventricular arrhythmias, cardiac surgery, cardiovascular death) were detected in 19 people (30%). In the non-ALVR group, hard endpoints were noted in 3 patients (5%). The odds ratio of developing an adverse outcome in ALVR vs. non-ALVR group was 8.5 (95% CI 2.4–30.5) (p = 0.0004). According to the multivariate analysis, the contribution of each of the indicators to the relative risk (RR) of adverse cardiac remodeling: waist circumference, RR = 1.02 (95% CI 1.001–1.05) (p = 0.042), plasma BNP—RR = 1.81 (95% CI 1.05–3.13) (p = 0.033), arterial elastance to left ventricular end-systolic elastance (Ea/Ees)—RR = 1.96 (95% CI 1.11–3.46) (p = 0.020). Conclusion. Determining ALVR status in early stages of the disease can accurately predict and stratify the risk of adverse outcomes in STEMI patients.

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Comparison of International Guidelines for Managing Chronic Heart Failure with Reduced Ejection Fraction

Nabil

2023

Current Problems in Cardiology

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Assessment of prevalence and monitoring of outcomes in patients with heart failure in Russia

Cited by 8 publications

References 25 publications

ICD-10 code-based definition of heart failure in Saint Petersburg electronic health records: prevalence, health care utilization and outcomes

ICD-10 code-based definition of heart failure in Saint Petersburg electronic health records: prevalence, health care utilization and outcomes

Prediction of Adverse Post-Infarction Left Ventricular Remodeling Using a Multivariate Regression Model

Comparison of International Guidelines for Managing Chronic Heart Failure with Reduced Ejection Fraction

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