ABSTRACT
Background: Acute coronary syndrome (ACS) remains a cause of high morbidity and mortality among adults, despite advances in treatment. Treatment modality and outcomes of ACS mainly depend on the time yielded since the onset of symptoms. Prehospital delay is the time between the onset of myocardial ischemia/infarction symptoms and arrival at the hospital, where either pharmacological or interventional revascularization is available. This delay remains unacceptably long in many countries worldwide, including Bangladesh. The current study investigates several sociodemographic characteristics as well as clinical, social, and treatment-seeking behaviors, with an aim to uncover the factors responsible for the decision time to get medical help and home-to-hospital delay. Materials and Methods: A prospective cross-sectional study was conducted between July 2019 and June 2020 in 21 district hospitals and 6 medical college hospitals where cardiac care facilities were available. The population selected for this study was patients with ACS who visited the studied hospitals during the study period. Following confirmation of ACS, a semi-structured data sheet was used to collect the patient data and was subsequently analyzed. Results: This study evaluated 678 ACS patients from 30 districts. The majority of the patients were male (81.9%), married (98.2%), rural residents (79.2), middle-aged (40-60 years of age) (55.8%), low-income holders (89.4%), and overweight (56.9%). It was found that 37.5% of the patients received their first medical care after 12 h of first symptom presentation. The study found that the patients' age, residence, education, and employment status were significant factors associated with prehospital delay. The patients with previous myocardial infarction (MI) and chest pain arrived significantly earlier at the hospital following ACS onset. Location of symptom onset, first medical contact with a private physician, distance from symptom onset location to location of first medical contact, the decision about hospitalization, ignorance of symptoms, and mode of transportation were significantly associated with prehospital delay. Conclusions: Several factors of prehospital delay of the ACS patients in Bangladesh have been described in this study. The findings of this study may help the national health management system identify the factors related to treatment delay in ACS and thus reduce ACS-related morbidity and mortality.
Subject(s)
Acute Coronary Syndrome , Emergency Medical Services , Acute Coronary Syndrome/complications , Acute Coronary Syndrome/therapy , Adult , Bangladesh/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Prospective Studies , Time FactorsABSTRACT
Background and aims: Identification of coronary artery disease by non-invasive means is a subject of interest for all. Myocardial strain has shown some promising results. This study intends to see if change in strain value correlates with the angiographic findings in patients with stable angina. It is also assessing whether myocardial strain can predict the presence of coronary artery disease (CAD) in stable angina patients. Method: This cross-sectional study was carried out on 84 stable angina patients with no previous cardiac history and normal LV function undergoing coronary angiogram for guideline-based indication. After careful history, clinical examination and investigations, including conventional echocardiography, selected participants underwent 2-D speckle tracking echocardiography for measurement of myocardial strain by automated functional imaging. All participants underwent coronary angiogram and stenosis >70% was considered significant. Gensini score was calculated. The myocardial strain value and Gensini score were correlated. Results: Global longitudinal strain (GLS) was significantly lower in patients with significant CAD than those with non-significant CAD (-16.1±2.6% vs -19.4±2.2%; p < 0.001). The optimal cut-off value of GLS, which discriminated between patients with and without significant coronary artery disease, was -18.05% (sensitivity=81.8% and specificity=85%). Also, GLS declined incrementally with the increasing severity of CAD defined by increasing number of stenotic vessels. There was an inverse correlation between GLS and severity of CAD (expressed in Gensini score) in this study (r = 0.669, p< 0.001), meaning that GLS decreased with increasing severity of CAD. GLS remained an independent predictor for the presence of significant CAD after multivariate adjustment for other significant baseline characteristics and echocardiographic parameters. Conclusions: The myocardial strain by 2DSE correlates with the angiographic severity by coronary angiogram in patients with stable angina. It is an independent predictor of significant coronary artery disease, which it can detect with good sensitivity and specificity.