Real-World Heart Failure Burden in Thai Patients

INTRODUCTION

Heart failure (HF) is one of the leading causes of hospitalization worldwide. In Thailand, data on HF burden remains limited. This study aimed to describe comprehensive evidence detailing the HF prevalence, hospital admission rates, in-hospital mortality, and overall mortality rates at the hospital level.

METHOD

All eligible adult patients' medical records from 2018 and 2019 were analyzed retrospectively at five hospitals in different regions. The patients were diagnosed with HF, as indicated by the International Classification of Diseases (ICD)-10 code I50. Descriptive statistics were used to examine the hospital burden as well as patients' clinical and outcome data.

RESULTS

A total of 7384 patients with HF were identified from five tertiary hospitals. Around half of the patients were male. The mean age was 67 years, and the main health insurance scheme was the Universal Coverage Scheme. The prevalence of HF was 0.1% in 2018 and 0.2% in 2019. Heart failure with preserved ejection fraction (HFpEF) was the most common type of HF in both visits, followed by heart failure with reduced ejection fraction (HFrEF) and heart failure with mildly reduced ejection fraction (HFmrEF). The proportion of HF hospitalizations was 1.2% in 2018 and 1.5% in 2019. The proportion of HF rehospitalizations versus hospitalizations in patients with HF was 22.7% in 2018 and 23.9% in 2019. The risk of rehospitalization was highest at 180 days after hospital discharge (87.8%). Among the patients with HF, the proportion of all-cause mortality was 9.1% in 2018 and 8.0% in 2019. Most of the deaths occurred within 30 days after hospitalization.

CONCLUSION

Our study demonstrated that the burden of HF in terms of hospitalization and in-hospital mortality was notably high when compared to similar studies conducted in Thailand and other countries.

A retrospective study of characteristics and burden of heart failure in Thailand: an interim analysis

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): Novartis (Thailand) Limited

Background/Introduction

Heart failure (HF) is a major health problem due to its significant prevalence, disease burden and cost, mainly driven by high rates of hospitalization and mortality. Although numerous studies have demonstrated HF burden in western countries, data on current burden of HF in Thailand are limited.

Purpose

To describe characteristics and burden of HF, in terms of HF subgroups, hospital visits/hospitalization from HF and mortality, in participating hospitals in Thailand in 2019.

Methods

We retrospectively reviewed hospital profiles and medical records of HF adult patients at the five study sites which located in different regions across Thailand. All patients were diagnosed (newly and existing) with HF during 2018-2019, as identified by the International Classification of Diseases (ICD)-10 coding "I50". The interim data cutoff was scheduled when 4,000 patients were included. Hospital burden and the patients’ clinical and outcome data were collected and analyzed with descriptive statistics.

Results

From 4,000 patients, a total of 2,826 patients had follow-up visits in 2019 and then included in this analysis. Most of them were female (51.8%) and the overall patients’ mean (SD) age was 67.6 (15.0). Among 1,668 patients with available baseline left ventricular ejection fraction (LVEF), HF with preserved EF (HFpEF) was the most common subgroup (47.3%), followed by HF with reduced EF (HFrEF (39.0%) and HF with mid-range EF (HFmrEF) (13.7%). Of the total hospital visits from HF, 11.5% (95% CI 10.8-12.3) were from unscheduled visits to emergency or outpatient departments. HFpEF accounted for the highest number of hospital visits for HF, both scheduled and unplanned visits (46.4%, 48.9%), followed by HFrEF (39.0%, 41.5%) and HFmrEF (14.6, 9.6%), respectively. Among these 2,826 HF patients, the numbers of hospitalizations and rehospitalization from HF were 2,553 and 447. The total rate of HF rehospitalization was highest at 30 days (39.1%, 95% CI 34.6-43.7), followed by at 180 days (26.8%, 95% CI 22.7, 30.9), and 60 days (23.5%, 95% CI 19.6-27.4), respectively. The rates of all-cause and CV deaths within identified HF patients were 8.6% (95% CI 7.6-9.7) and 7.2% (95% CI 6.3-8.2). HFrEF accounted for the highest proportions of both (re) hospitalization and deaths (all-cause and CV) while HFpEF had the highest number of total beds.

Conclusion

Among the studied patients, HFpEF was the most common form of HF and HF was associated with a substantial healthcare burden in Thailand. The hospitalization rates from HF were especially high during the first 30 days after discharge, with a number of visits being unplanned or emergency visits leading to high hospital resource utilization.

Differentiation of Takotsubo Cardiomyopathy from ST Elevation Myocardial Infarction in Patients Activated for Fast-Track Coronary Angiography

OBJECTIVE

To compare clinical and electrocardiographic (ECG) features between Takotsubo cardiomyopathy (TC) and ST-elevation myocardial infarction (STEMI).

MATERIAL AND METHOD

We retrospectively reviewed clinical, electrocardiographic, and laboratory features of 20 consecutive TC patients and 155 consecutive STEMI patients who were activated for fast-track coronary angiography and were ultimately diagnosed with either TC or STEMI and compared these data between the two groups.

RESULTS

Patients with TC were older (p = 0.001), more often female (p = 0.001), had more often been triggered by intense emotional or physical stress (p = 0.001) or illness (p = 0.001), and had a lower rate of smoking (p = 0.005) than STEMI patients. Compared with patients who presented with anterior wall STEMI, those with TC less commonly had Q waves (30.0% vs. 62.9%, p = 0.007) and reciprocal change (0.0% vs. 37.1%, p = 0.001), and had a lower rate of ST-segment elevation in lead V1 (5.0% vs. 59.8%, p = 0.001). ST-segment depression was also more common in TC in lead aVR (20.0% vs. 2.1%, p = 0.008). Previously proposed ECG criteria had low sensitivity, but high specificity in our patients. Our proposed point scoring model includes the use of both clinical and ECG findings. According to our proposed model, a score ≥4 had 90% sensitivity and 98% specificity in differentiating TC from acute anterior STEMI (AUC = 0.976, p<0.001).

CONCLUSION

In patients activated for fast-track coronary angiography because of acute coronary ST-segment elevation syndrome, a number of clinical and ECG features differ between TC patients and patients with true STEMI. Our proposed point scoring model that uses clinical and ECG findings demonstrated improved diagnostic accuracy in differentiating TC from acute anterior STEMI.