Original article

Quality of life in patients receiving percutaneous coronary intervention and optimal medical therapy in Ho Chi Minh City, Vietnam

Thao Thanh Nguyena, Quyen Gia Tobhttps://orcid.org/0000-0002-3355-6326, Anh Do Nguyenc, Tien The Nguyenc, Van-Anh Ngoc Huynhd, Kien Gia Tod,*https://orcid.org/0000-0001-5038-5584
Author Information & Copyright
aCenter for Diseases Control of Ho Chi Minh City
bAppleton Institute, Central Queensland University, Australia
cDepartment of Interventional Cardiology, Nhan Dan Gia Dinh Hospital, Ho Chi Minh City, Vietnam
dFaculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City
*Address correspondence: Kien Gia To at Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam; E-mail: togiakien@ump.edu.vn

© Copyright 2020 MedPharmRes. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Jul 23, 2020; Revised: Aug 23, 2020; Accepted: Sep 17, 2020

Published Online: Dec 31, 2020



This study assessed Health-Related Quality of Life (HRQOL) of patients with Acute Coronary Syndrome (ACS) 6 to 12 months after receiving Percutaneous Coronary Intervention (PCI) and/or Optimal Medical Therapy (OMT) at a hospital in Ho Chi Minh City, Vietnam.


A cross-sectional study was conducted on 113 patients. Data on demographic, lifestyle behaviours, and HRQOL were collected using a structured questionnaire through face-to-face interviews. HRQOL was measured using EQ-5D-5L and EQ-VAS. Data on co-morbidity and other clinical characteristics were extracted from hospital records. Bivariate and multivariable linear regression models were run to test the differences in EQ-5D-5L utility index and EQ-VAS scores between PCI/OMT and OMT alone groups.


EQ-5D-5L utility index and EQ-VAS scores were lower in PCI/OMT compared to OMT groups, although the differences were not clinically meaningful. Weight status, smoking, and physical activity were associated with EQ-5D-5L utility index score, whereas only physical activity was associated with EQ-VAS score.


The findings suggested that improving sufficient physical activity levels and stopping smoking after PCI or/and OMT may help increase HRQOL among ACS patients.

Keywords: Acute coronary syndrome; EQ-5D-5L; EQ-VAS; Quality of life; Utility index


Cardiovascular disease (CVD) is a global public health concern with an estimated 17.9 million deaths in 2016, accounting for 31% of all global deaths [1]. It is estimated that 151,377 million disability-adjusted life years was lost due to CVD [2]. CVD is a group of heart and blood vessels disorders, including acute coronary syndromes (ACS) known as a “heart attack” [3]. Approximately 80% of ACS patients die within the first one hour before they are carried to the nearest hospital [3, 4]. Compared to the general population, ACS patients are more likely to have depression and confined mobility, resulting in lower health-related quality of life (HRQOL) [5], a measure of perceived health status and satisfaction in performing daily life activities [6].

Treatments for ACS is vital and should be provided urgently. The guidelines of European Society of Cardiology and European Association for Cardio-Thoracic Surgery recommended an invasive strategy for most of ACS patients [7]. Percutaneous coronary intervention (PCI) is the second most frequently performed invasive intervention for ACS in the U.S after cardiac catheterization in 2019 [8]. In PCI, a flexible thin tube is used to insert a stent into an artery to widen plague-build-up-narrowed blood vessels in the heart, an atherosclerosis. This non-surgical intervention is highly successful and causes few complications [7, 8, 9]. Optimal medical therapy (OMT), which includes antiplatelet agents, statins, β-blockers and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, is an initial and essential treatment that needed for ACS patients whether or not they receive PCI [10, 11].

Previous studies showed that PCI improve HRQOL among ACS patients [12, 13]. There were also few studies on this issue conducted in Vietnam where the population is aging quickly and CVD as the leading cause of deaths is accounting for 30% of total disability-adjusted life years [14, 15]. Although HRQOL is an important measure to assess clinical outcomes [16], data on HRQOL among ACS patients were limited in Vietnam. Therefore, this study was conducted to 1) evaluate HRQOL of ACS patients in Nhan Dan Gia Dinh Hospital, Ho Chi Minh City (HCMC), Vietnam, 2) determine whether HRQOL was different for those receiving both PCI/OMT compared to those receiving OMT alone 6 to 12 months after treatment, and 3) examine associations between HRQOL and potential correlates.


2.1. Study settings

Nhan Dan Gia Dinh Hospital is a public provincial hospital administrated by the Ho Chi Minh City Department of Health. The 1,500-bed hospital with modern-equipment, and experienced and high-skilled healthcare professionals, is capable for 4.000 outpatient-visits and 300 emergencies per day. This is a teaching hospital of the University of Medicine and Pharmacy at Ho Chi Minh City (http://bvndgiadinh.org.vn/home/about/).

2.2. Study designs and participants

A cross-sectional design was used to collect data from ACS patients at the Department of Interventional Cardiology, Nhan Dan Gia Dinh Hospital between March and May 2019. The hospital provided treatment for more than 750 ACS patients in 2018, of which 76% received PCI. A list of patients and their medical records were used to screen for participant’s eligibility. Patients who 1) were at least 18 years old; 2) diagnosed with ACS including unstable angina (UA)/non-ST elevation myocardial infarction (NSTEMI) or ST elevation myocardial infarction (STEMI); 3) had coronary angiography; and 4) underwent PCI plus OMT (PCI/OMT) or OMT alone for 6 to 12 months at the hospital. Those who were unable to answer the questions due to limited cognitive ability; had chronic coronary artery disease; or underwent the second invasive strategy were excluded from the study. Eligible patients were invited to participate in the study when they visited the hospital for medical check-up. The purpose of the study was explained, and information sheet was provided to the patients. Patients were required to return written consents if they agreed to participate.

2.3. Data collection

Face-to-face interviews were conducted using a structured questionnaire. Demographic and socio-economic characteristics collected included gender, age, marital status, education level, place of residence, working status, household economic and health insurance. Age was grouped into <65 years or ≥65 years as patients aged ≥65 years suffer higher risk of mortality [11]. Weight and height were measured using standard protocols [17]. Body Mass Index (BMI) calculated by [weight (kg)]/ [height squared (m2)] was used to determine patients’ weight status. A patient was classified as normal weight (BMI<23) and overweight/obese (BMI ≥23) as suggested by World Health Organization for Asian population [18]. Household economic was certified by the local authorities as poor and non-poor.

Lifestyle behaviours, including smoking, drinking alcohol, and being physically active, were self-reported. A patient was considered an active smoker if they smoked within the last 30 days. Non-smokers or those who stopped smoking within the last 30 days were grouped together. Similarly, those who drank at least one standard unit of alcohol per day or five units within the last 30 days were considered a drinker. In addition, a patient was considered active if they self-reported engaging in at least 30 minutes of moderate-vigorous physical activity in at least 5 days/week and within the last 30 days. These simple questions, adapted from STEPS instrument [19], were used to reduce the response burden due to reduced memory and cognitive capacity among aging populations [20].

Clinical records were used to determine patients’ comorbidity status. A patient was considered having a comorbidity if they had on their records at least one of these conditions: hypertension, dyslipidemia, diabetes, chronic kidney disease, chronic liver disease, and chronic lung disease. Other clinical data collected were history of myocardial infarction, history of brain stroke, family history of cardiovascular diseases, type of ACS (UA/NSTEMI or STEMI), duration of treatment in months, the number of damaged vessels, and Left Ventricular Ejection Fraction (LVEF) (<40%, 40-50%, >50%) [21].

HRQOL was assessed using EQ-5D-5L and EQ-VAS that were developed by the EuroQoL Group [22, 23, 24, 25]. The EQ-5D-5L covers five HRQOL dimensions including mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has five response options representing for a health status and ranging from having no, slight, moderate, severe, or extreme problems. Vietnamese value sets was then used to convert a health status into health utility index score [26]. EQ-VAS evaluates imaginable health status that ranges from 0 (worst condition) to 100 (best condition). EQ-5D-5L and EQ-VAS are not time-consuming and easy to use. Their validity and reliability have been tested in previous studies [27, 28, 29].

2.4. Data analysis

Data were entered using Epidata v3.1 and analysed using STATA v13. Frequency and percentage were calculated for categorical variables. Mean and standard deviation (SD) were generated for continuous variables. Descriptive statistics were presented for the whole sample and by treatment type (i.e. OMT vs. PCI/OMT). Differences in sample characteristics between two treatment types were tested using either Chi-squared/Fisher’s exact tests (for categorical variables) or two-sample t-tests (for continuous variables). These tests were also used to test associations between each HRQOL dimension and type of ACS treatment.

The outcomes were EQ-5D-5L and EQ-VAS scores which were analyzed separately using linear regressions. Two models were run for each outcome. Model 1 were to test bivariate associations between the outcomes and independent variables including types of ACS treatment, age group, gender, weight status, marital status, education level, employment status, smoking, drinking, co-morbidities, the number of damaged vessels and LVEF. Model 2 were multivariable models that tested associations of independent variables adjusting for the other covariates. Crude and adjusted regression coefficients with their 95% confidence interval were reported. A two-sided p-value of less than 0.05 was considered as statistical significance.

2.5. Ethical considerations

The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (No. 126/ÐHYD-HÐÐÐ on 20 March 2019) and Nhan Dan Gia Dinh Hospital (No. 07/KHTH-QLTTSL on 22 April 2019).


A total of 125 ACS patients were screened and 113 patients (90%) were agreed to participate in the study. Of these, 73 patients (65%) received PCI/OMT, and 40 patients (35%) received OMT alone. The mean age was 61 years (SD=11 years), ranging from 34 to 84 years. Table 1 shows sample characteristics. Majority of patients were <65 years old (57%), men (68%), overweight/obese (57%), and married (80%). About half completed senior high school (53%) and were not working (58%). Most lived inside HCMC (84%) and was non-poor (85%).

Table 1: Demographic, clinical and angiographic characteristics of the sample (n=113)
Characteristics N (%) Sample (n=113) N (%) PCI (n=73) N (%) OMT (n=40) N (%) p-value
 <65 64 (57) 46 (63) 18 (45) 0.07
 ≥65 49 (43) 27 (37) 22 (55)
 Male 77 (68) 51 (70) 26 (65) 0.60
 Female 36 (32) 22 (30) 14 (35)
Weight status
 Normal 49 (43) 30 (41) 19 (48) 0.51
 Overweight/Obesity 64 (57) 43 (59) 21 (53)
Marital status
 Single/separated/divorced/widowed 23 (20) 16 (22) 7 (18) 0.58
 Married 90 (80) 57 (78) 33 (83)
Educational level
 Junior high school or lower 53 (47) 31 (43) 22 (55) 0.20
 Senior high school or higher 60 (53) 42 (58) 18 (45)
Place of residence
 Inside HCM city 95 (84) 65 (89) 30 (75) 0.05
 Outside HCM city 18 (16) 8 (11) 10 (25)
Working status
 No working 66 (58) 37 (51) 29 (73) 0.02
 Currently working 47 (42) 36 (49) 11 (28)
Household economic
 Poor 17 (15) 10 (14) 7 (18) 0.59
 Non-poor 96 (85) 63 (86) 33 (83)
Health insurance
 No 8 (7) 2 (3) 6 (15) 0.02 a
 Yes 105 (93) 71 (97) 34 (85)
 No 96 (85) 64 (88) 32 (80) 0.28
 Yes 17 (15) 9 (12) 8 (20)
Drinking alcohol
 No 101 (89) 65 (89) 36 (90) 0.87
 Yes 12 (11) 8 (11) 4 (10)
Physical activity
 No 51 (45) 32 (44) 19 (48) 0.71
 Yes 62 (55) 41 (56) 21 (53)
 No 15 (13) 10 (14) 5 (13) 0.86
 Yes 98 (87) 63 (86) 35 (88)
History of myocardial infarction
 No 104 (92) 68 (93) 36 (90) 0.72a
 Yes 9 (8) 5 (7) 4 (10)
History of brain stroke
 No 106 (94) 71 (97) 35 (88) 0.10a
 Yes 7 (6) 2 (3) 5 (13)
Family history of cardiovascular disease
 No 101 (89) 63 (86) 38 (95) 0.21a
 Yes 12 (11) 10 (14) 2 (5)
Type of ACS
 UA/NSTEMI 56 (50) 25 (34) 31 (78) <0.01
 STEMI 57 (50) 48 (66) 9 (23)
Duration of treatment in months (Mean ± SD) 9.4 ± 2.3 9.3 ± 2.2 9.7 ± 2.4 0.37b
The number of damaged vessels
  1 27 (24) 13 (18) 14 (35) 0.02
  2 33 (29) 27 (37) 6 (15)
  3 53 (47) 33 (45) 20 (20)
  <40% 16 (14) 9 (12) 7 (18) 0.35
  40-50% 15 (13) 12 (16) 3 (8)
  >50% 82 (73) 52 (71) 30 (75)

PCI: percutaneous coronary intervention; OMT: Optimal medical therapy; ACS: acute coronary syndromes; UA/NSTEMI: unstable angina/non-ST elevation myocardial infarction; STEMI: ST elevation myocardial infarction; LVEF: Left Ventricular Ejection Fraction; SD: Standard deviation.

* Co-morbidity was yes if patient had one of the following diseases including hypertension, dyslipidemia, diabetes, chronic kidney disease, chronic liver disease or chronic lung disease

Chi-square test used except otherwise stated

a Fisher exact test

b The two-sample t-test with equal variances

Download Excel Table

The percentage of smoking and drinking in the sample were 15% and 11%, respectively. More than half of patients engaged in at least 30 minutes of moderate-vigorous physical activity in at least 5 days/week and within 30 days (55%). Most patients (87%) had at least one co-morbidity. The percentage of patients had a history of myocardial infarction and a history of brain stroke was 8% and 6%, respectively. About one in 10 patients had a family history of cardiovascular disease and half was UA/NSTEMI. Nearly half of patients had three damaged vessels (47%), following by two (29%) and one (24%). Three quarter of patients had LVEF >50%, 13% had LVEF 40-50%, and 14% had LVEF <40%. The average duration of treatment was 9.4 ± 2.3 months, ranging from 6 to 12 months. There were differences between PCI/OMT and OMT groups in working status (p=0.02), health insurance (p=0.02), the number of damaged vessels (p=0.02), and place of residence (p=0.05).

Table 2 shows that more than one-third of the patients reported having problems with usual activity (43%), pain/discomfort (40%), or anxiety/depression (33%). About one-fifth had problem with mobility. Percentage of patients having problem with self-care was small (7%). Mean scores for EQ-5D-5L utility index and EQ-VAS scores were 0.88 (SD=0.15) and 65.6 (SD=13.3), respectively. There was no statistically significant difference in five HRQOL dimensions between PCI/OMT and OMT groups.

Table 2: EQ-ED-5L and EQ-VAS scores, and percentages of reporting problems in five dimensions of EQ-5D-5L (n=113)
Sample (n=113) PCI (n=73) OMT (n=40) p-value
Mobility (n, %)
 No problem 88 (78) 56 (77) 32 (80) 0.69
 Having problems 25 (22) 17 (23) 8 (20)
Self-care (n, %)
 No problem 105 (93) 69 (95) 36 (90) 0.45a
 Having problems 8 (7) 4 (6) 4 (10)
Usual activity (n, %)
 No problem 64 (57) 39 (53) 25 (63) 0.35
 Having problems 49 (43) 34 (47) 15 (38)
Pain/discomfort (n, %)
 No problem 68 (60) 43 (59) 25 (63) 0.71
 Having problems 45 (40) 30 (41) 15 (38)
Anxiety/depression (n, %)
 No problem 76 (67) 46 (62) 30 (75) 0.19
 Having problems 37 (33) 27 (37) 10 (25)
EQ-5D-5L (Mean ± SD) 0.88 ± 0.15 0.87 ± 0.15 0.89 ± 0.15 0.37b
EQ-VAS (Mean ± SD) 65.6 ± 13.3 64.7 ± 13.4 67.1 ± 13.1 0.36b

PCI: percutaneous coronary intervention; OMT: Optimal medical therapy; SD: Standard deviation; Higher EQ-5D-5L utility index score represents better quality of life. Higher EQ-VAS score represents better health status.

Chi-squared test used except otherwise stated

a Fisher exact test

b The two-sample t test with equal variances

Download Excel Table

Table 3 shows associations between EQ-5D-5L utility index and EQ-VAS scores with treatment groups and other variables. In the bivariate analysis with EQ-5D-5L utility index as an outcome, patients with overweight/obesity had 0.06 points (95%CI: 0.00, 0.11) higher than those normal weight; patients with senior high school had 0.09 points (95%CI: 0.04; 0.14) higher than those with junior high school; those smoking had 0.14 points (95%CI: -0.21; -0.07) lower than those without smoking; those who were active had 0.07 points (95CI%: 0.02; 0.13) higher than inactive ones; and those with three damaged vessels had 0.09 points (95%CI:-0.16; -0.03) lower than those with one damaged vessel.

Table 3: Linear regression to assess associations between independent variables with EQ-5D-5L and EQ-VAS scores (n=113)
Model l Coef. (95%CI) Model 2 Coef. (95%CI) Model l Coef. (95%CI) Model 2 Coef. (95%CI)
PCI vs. OMT -0.03 (-0.08; 0.03) -0.07 * (-0.14; -0.01) -2.39 (-7.58; 2.81) -6.86 * (-13.16; -0.56)
Age group (≥65 vs. <65) -0.01 (-0.07; 0.05) -5.54 * (-10.5; -0.62)
Gender (Female vs. Male) -0.02 (-0.08; 0.04) -5.26 (-10.52; 0.00)
BMI group (overweight/obese vs. normal weight) 0.06 * (0.00; 0.11) 0.06 * (0.00; 0.11) 1.07 (-3.96; 6.09)
Marital status (Other vs. Married) 0.04 (-0.03; 0.11) 5.54 (-0.56; 11.64)
Educational level (Senior vs. Junior high school) 0.09 ** (0.04; 0.14) 8.17 ** (3.42; 12.92)
Place of residence (Inside vs. Outside HCM city) -0.01 (-0.09; 0.06) -0.69 (-7.50; 6.11)
Working status (Currently working vs. No) 0.04 (-0.02; 0.09) 5.01 * (0.04; 9.98)
Health insurance (Yes vs. No) -0.03 (-0.14; 0.07) -1.79 (-11.50; 7.92)
Household economic (Non-poor vs. poor) 0.07 (0.00; 0.15) 5.81 (-1.07; 12.69)
Smoking status (Yes vs. No) -0.14 ** (-0.21; -0.07) -0.15 ** (-0.23; -0.06) -1.93 (-8.98; 5.03)
Drinking status (Yes vs. No) 0.03 (-0.06; 0.12) 1.77 (-6.31; 9.85)
Physical activity (Yes vs. No) 0.07 ** (0.02; 0.13) 0.07 * (0.02; 0.12) 5.78 * (0.89; 10.67) 5.59 * (0.43; 10.75)
Comorbidity (Yes vs. No) -0.05 (-0.14; 0.03) -4.78 (-12.07; 2.50)
History of myocardial infarction (Yes vs. No) -0.02 (-0.12; 0.08) -4.01 (-13.19; 5.16)
History of brain stroke (Yes vs. No) -0.10 (-0.22; 0.01) -5.95 (-16.23; 4.32)
Family history of cardiovascular disease (Yes vs. No) 0.04 (-0.05; 0.13) 7.46 (-0.51; 15.42)
ACS diagnosis (UA/NSTEMI vs. STEMI) 0.00 (-0.06; 0.05) 4.52 (-0.39; 9.43)
Duration of treatment in months The number of damaged vessels 0.00 (-0.01; 0.01) 0.49 (-0.60; 1.59)
 Two vs. One damaged vessel -0.02 (-0.09; 0.05) -4.23 (-10.88; 2.42)
 Three vs. One damaged vessel -0.09 * (-0.16; -0.03) -8.76 ** (-14.82; -2.70)
 40-50% vs. <40% -0.02 (-0.13; 0.08) -1.04 (-10.60; 8.51)
 >50% vs. <40% 0.03 (-0.05; 0.11) 0.48 (-6.79; 7.74)

PCI: percutaneous coronary intervention; OMT: Optimal medical therapy; ACS: acute coronary syndromes; UA/NSTEMI: unstable angina/non-ST elevation myocardial infarction; STEMI: ST elevation myocardial infarction; LVEF: Left Ventricular Ejection Fraction; Coef.: regression coefficient; 95%CI: 95% confidence interval

Model 1: crude bivariate model between each independent variable with EQ-5D-5L utility index and EQ-VAS scores.

Model 2: multivariable model included treatment group, age group, gender, weight status, marital status, educational level, place of residence, working status, household economic, health insurance, smoking status, drinking status, physical activity, co-morbidity, history of myocardial infarction, history of brain stroke, family history of cardiovascular diseases, type of ACS, duration of treatment in months, the number of damaged vessels, and LVEF.

* p<0.05,

** p<0.01

Download Excel Table

Bivariate analysis with EQ-VAS score as an outcome showed that patients ≥65 years had 5.54 points (95%CI: -10.5; -0.62) lower than those <65 years. Those completing senior high school had 8.17 points (95CI%: 3.42; 12.92) higher than those with only junior high school. Patients with a job had 5.01 points (95%CI: 0.04; 9.98) higher than those unemployed. Those being active had 5.78 points (95%CI: 0.89; 10.67) higher than inactive ones. Patients with three damaged vessels had 8.76 points (95%CI: -14.82; -2.7) lower than those with one damaged vessel.

In multivariable analyses, weight status, physical activity and smoking were independently associated with EQ-5D-5L utility index. Overweight/obese patients had 0.06 points (95%CI: 0.00; 0.11) lower than non-overweight/obese patients; active patients had 0.07 points (95%CI: 0.02; 0.12) higher than inactive patients; and smokers had 0.15 points (95%CI: -0.23; -0.06) lower than non-smokers. However, only physical activity remained significantly associated with EQ-VAS score. Active patients had 5.59 points (95%CI: 0.43; 10.75) higher than inactive ones. Although EQ-5D-5L utility index was not different between PCI/OMT and OMT groups in the bivariate analysis, the PCI/OMT group had 0.07 points (95%CI: -0.1; -0.01) lower than the OMT group after controlling for other variables. Similar results were found for EQ-VAS score that was 6.86 points (95%CI: -13.16 to -0.56) lower for the PCI/OMT group compared to the OMT group after controlling for other variables.


The EQ-5D-5L utility index (0.88, SD=0.15) among ACS patients in this study was similar to that of the Vietnamese general population aged 35+ (0.89, SD=0.16), but EQ-VAS score (65.6, SD=13.3) was lower (86.4, SD=13.4) [30]. Additionally, the percentages of ACS patients reporting a problem in five HRQOL domains were also higher than those of the Vietnamese general population aged 35+ including usual activities (43% vs. 28%), pain/discomfort (40% vs. 13%), anxiety/depression (33% vs. 18%), and mobility (22% vs. 7%), and self-care (7% vs. 4%) [30]. This is expected because participants in this study were ACS patients and a half of whom were 65 years or older who may rate their EQ-VAS score worse [31]. It is noted that EQ-VAS score is a one-item general patients’ perspective scale whereas EQ-5D-5L utility index reflects societal perspectives and addresses five dimensions of life.

For all HRQOL domains, no difference in percentages of self-reported problems between PCI/OMT and OMT groups was found. However, it seemed that PCI/OMT groups had lower HRQOL scores than OMT groups. It is important to point out that while the differences in HRQOL scores were statistically significant, they may not be clinically significant due to small effect. Given the cross-sectional nature of this study, it is also likely that patients with PCI/OMT had worse health status than those with OMT and therefore lower HRQOL before treatment [32]. Studies with stronger designs found that PCI/OMT groups had better HRQOL than OMT groups 6-12 months after medical interventions, however, the difference was not found after 12 months [13, 33, 34]. Although the two medical interventions had been proved to be generally safe [7, 8, 9], there are reports on complications that might decrease HRQOL [35, 36]. For example, using antiplatelet agents in OMT can cause major bleeding by erosive gastritis [36] and that could affect HRQOL [37]. Severe hemodynamic compromise or even death can occur during PCI procedure [38]. Despite the potential complications, both PCI/OMT and OMT alone were found to provide similar benefits in reducing mortality rate and releasing angina [35].

In this study, overweight/obese patients had EQ-5D-5L utility index slightly higher, but no difference was observed in EQ-VAS score. The association between BMI and HRQOL was inconsistent, complex and could not be generalizable [39, 40]. A study showed that those with BMI>30 was 30% had lower HRQOL compared to those with BM<I25 adjusting for age, gender, education level, and social class [40]. However, another study showed a non-linear association between BMI and HRQOL with interaction by age and gender in each domain of HRQOL [39]. In sum, after adjusting for age, gender, co-morbidity, diet and physical activity, 70-year old normal weight men had 0.03 points higher than 70-year old obese men but women with higher weight had lower physical HRQOL [39].

The bivariate analysis showed positive association between education level and EQ-5D-5L utility index and EQ-VAS scores; however, the association was disappeared in the multivariable analysis that was consistent with a previous study conducted in Vietnamese general population [30], although studies conducted in other countries suggested people with higher education level had better HRQOL [41, 42]. The Vietnamese study explained that those who had higher education were more likely to suffer mental disorder that could reduce HRQOL [30]. However, the association between education level with anxiety/depression domain of EQ-5D-5L was tested but no association was found in this study. It is also noted that higher education level is associated with higher income, better working status and better living condition thus result in better HRQOL [43]. Working status is an important factor affecting quality of life because it shows one’s socio-economic status and types of activities and levels of functions [30, 42, 44, 45].

In this study, the percentage of smoking (15.0%) was lower compared to that reported in Global Adult Tobacco Survey in Vietnam (22.5%) [46] and the percentage of drinking (11.0%) was lower compared to that from a survey of rural district in the north of Vietnam (35%) [47]. This may be due to the fact that our study population is ACS patients, many of whom were likely to minimize or even stop smoking and drinking after learning about their health condition [48]. Although smoking and drinking increase the risk of morbidity and mortality [49], only smoking was associated with HRQOL in this study. Smoking has negative effects on health that has been clearly demonstrated in many populations [50]. Smoking was also the only factor with a clinically meaningful effect on EQ-5D-5L utility index in this study [32]. This is consistent with a previous longitudinal study reporting that smokers had HRQOL scores after PCI improved less than non-smokers [51].

Physical activity were another lifestyle factor with positive effect on HRQOL and this is consistent with previous findings [52]. At least 30 minutes of moderate-vigorous physical activity in at least 5 days/week was beneficial to ACS patients although this is just a recommendation and should be conditional on individual health status [53]. It is also worth noting that prevalence of insufficient physical activity was about 30% in general populations worldwide [54]. As the Vietnamese population is quickly aging that increased age-related health problems [14], providing physical activity programs which are mostly unavailable at the moment, could be an effective way to improve HRQOL among older populations [55, 56].

This study has some limitations. Firstly, it is a cross-sectional study and therefore, causal relationship between HRQOL and other factors could not be assessed. Secondly, although some clinical characteristics were extracted from hospital records, other data were self-reported and therefore subject to recall bias. Another limitation was that angina’s characteristics such as severity, frequency or reliefs were not collected as the effectiveness of PCI significantly depends on angina’s characteristics [16]. Lastly, data were collected in only one hospital and the sample was not large and therefore, generalizability of the findings may be limited.


In conclusion, differences in EQ-5D-5L utility index and EQ-VAS scores between PCI/OMT and OMT groups were not clinically meaningful. Smoking and physical activity are important factors influencing HRQOL among older Vietnamese populations. Interventions to improve lifestyle behaviours, particularly smoking and physical activity, are needed to improve HRQOL among ACS patients.



Acute Coronary Syndrome


Coronary Heart Disease


Cardiovascular disease


Optimal Medical Therapy


Percutaneous coronary intervention


non-ST elevation myocardial infarction


ST elevation myocardial infarction


unstable angina


The authors declared no conflict of interests.


TTN and KGT designed the study. TTN collected data. ADN and TTN supported in data collection. TTN and KGT drafted the manuscript. KGT, TTN, HNVA and QGT did the analysis and edited the manuscript. All authors contributed to interpretation of the data, critically reviewed and approved the manuscript.

We thank the Executive Board of Nhan Dan Gia Dinh Hospital for approving this study; doctors, nurses and staff-members of the Department of Interventional Cardiology, Nhan Dan Gia Dinh Hospital for supporting and assisting with data collection; and all patients for participating in this study.


No funding.



World Health Organization. Fact sheets - Cardiovascular diseases. 2017 [[29 Oct 2018]]. Available from: https://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).


Global Atlas on cardiovascular disease prevention and control. Geneva: World Health Organization. 2011.


Sanchis-Gomar F, Perez-Quilis C, Leischik R, Lucia A. Epidemiology of coronary heart disease and acute coronary syndrome. Ann Transl Med. 2016; 4(13):256


Chugh SS, Reinier K, Teodorescu C, Evanado A, Kehr E, Al Samara M, et al. Epidemiology of sudden cardiac death: clinical and research implications. Prog Cardiovasc Dis. 2008; 51(3):213-28


Bach JP, Riedel O, Pieper L, Klotsche J, Dodel R, Wittchen HU. Health-related quality of life in patients with a history of myocardial infarction and stroke. Cerebrovasc Dis. 2011; 31(1):68-76


Eckermann E. The quality of life of adults.In In: Land KC, Michalos AC, Sirgy MJ, editors.editors Handbook of Social Indicators and Quality of Life Research. Dordrecht: Springer. 2012; p p. 373-80


Neumann F-J, Sousa-Uva M, Ahlsson A, Alfonso F, Banning AP, Benedetto U, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. European Heart Journal. 2019; 40(2) pp:87-165


Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, et al. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation. 2019; 139(10):e56-e528


Panduranga P, Al-Rashidi M, Hajri FA. In-Hospital and One-Year Clinical Outcome of Percutaneous Coronary Intervention in a Tertiary Hospital in Oman: Oman PCI Registry. Oman Medical Journal. 2017; 32(1) pp:54-61


Iqbal J, Serruys PW. Optimal medical therapy is vital for patients with coronary artery disease and acute coronary syndromes regardless of revascularization strategy. Annals of Translational Medicine. 2017; 5(6):140


Vietnam Ministry of Health. Decision No. 2187/QÐ-BYT on 03/06/2019 about “Hướng dẫn chẩn đoán và xử trí hội chứng mạch vành cấp”. 2019.


Li R, Yan BP, Dong M, Zhang Q, Yip GW-K, Chan C-P, et al. Quality of life after percutaneous coronary intervention in the elderly with acute coronary syndrome. International Journal of Cardiology. 2012; 155 pp:90-6


de Quadros AS, Lima TC, Rodrigues AP, Modkovski TB, Welter DI, Sarmento-Leite R, et al. Quality of life and health status after percutaneous coronary intervention in stable angina patients: results from the real-world practice. Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions. 2011; 77(7):954-60


Vietnam Ministry of Health, Health Partnership Group. Joint Annual Health Review 2016: Towards Health Aging in Vietnam. Hanoi. 2017.


World Health Organization. Cardiovascular diseases (CVD) in Viet Nam. 2016.


Blankenship JC, Marshall JJ, Pinto DS, Lange RA, Bates ER, Holper EM, et al. Effect of percutaneous coronary intervention on quality of life: a consensus statement from the Society for Cardiovascular Angiography and Interventions. Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions. 2013; 81(2):243-59


World Health Organization. Physical status: The use of and interpretation of anthropometry, Report of a WHO Expert Committee. 1995 [[cited 07/08/2017]]. Available from: http://apps.who.int/iris/bitstream/10665/37003/1/WHO_TRS_854.pdf.


Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157-63


World Health Organization. The WHO STEPwise approach to chronic disease risk factor surveillance (STEPS): The STEPS Instrument and support materials. 2019 [[02 Jan 2020]]. Available from: https://www.who.int/ncds/surveillance/steps/instrument/en/.


Knäuper B, Carrière K, Chamandy M, Xu Z, Schwarz N, Rosen NO. How aging affects self-reports. Eur J Ageing. 2016; 13(2):185-93


Agra Bermejo R, Cordero A, García-Acuña JM, Gómez Otero I, Varela Román A, Martínez Á, et al. Determinants and Prognostic Impact of Heart Failure and Left Ventricular Ejection Fraction in Acute Coronary Syndrome Settings. Revista Española de Cardiología (English Edition). 2018; 71(10):820-8


Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013; 22(7):1717-27


Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011; 20(10):1727-36


Brooks R. EuroQol: the current state of play. Health Policy. 1996; 37(1):53-72


EuroQol G. EuroQol--a new facility for the measurement of health-related quality of life. Health Policy. 1990; 16(3):199-208


Vu QM, Hoang VM, Sun S, Kim BG, Klas GS. Valuing Health - Related Quality of Life: An EQ-5D-5L Value Set for Vietnam. 2018.


Schweikert B, Hahmann H, Leidl R. Validation of the EuroQol questionnaire in cardiac rehabilitation. CARDIOVASCULAR MEDICINE. 2006; 92(1) pp:62-7


Dyer MT, Goldsmith KA, Sharples LS, Buxton MJ. A review of health utilities using the EQ-5D in studies of cardiovascular disease. Health Qual Life Outcomes. 2010; 8 pp:13


Tran BX, Ohinmaa A, Nguyen LT, Nguyen TA, Nguyen TH. Determinants of health-related quality of life in adults living with HIV in Vietnam. AIDS Care. 2011; 23(10) pp:1236-45


Nguyen LH, Tran BX, Hoang Le QN, Tran TT, Latkin CA. Quality of life profile of general Vietnamese population using EQ-5D-5L. Health Qual Life Outcomes. 2017; 15(1):199


Kim S-H, Jo M-W, Ock M, Lee S-i. Exploratory Study of Dimensions of Health-related Quality of Life in the General Population of South Korea. J Prev Med Public Health. 2017; 50(6):361-8


Chen P, Lin KC, Liing RJ, Wu CY, Chen CL, Chang KC. Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation. Qual Life Res. 2016; 25(6):1585-96


Weintraub WS, Spertus JA, Kolm P, Maron DJ, Zhang Z, Jurkovitz C, et al. Effect of PCI on Quality of Life in Patients with Stable Coronary Disease. New England Journal of Medicine. 2008; 359(7):677-87


Azmi S, Goh A, Fong A, Anchah L. Quality of life among Patients with Acute Coronary Syndrome in Malaysia. Value In Health Regional Issues. 2015; 6 pp:80-3


Stergiopoulos K, Boden WE, Hartigan P, Mobius-Winkler S, Hambrecht R, Hueb W, et al. Percutaneous coronary intervention outcomes in patients with stable obstructive coronary artery disease and myocardial ischemia: a collaborative meta-analysis of contemporary randomized clinical trials. JAMA internal medicine. 2014; 174(2):232-40


Al-Lamee R, Thompson D, Dehbi HM, Sen S, Tang K, Davies J, et al. Percutaneous coronary intervention in stable angina (ORBITA): a double-blind, randomised controlled trial. Lancet. 2018; 391(10115):31-40


Wen Z, Li X, Lu Q, Brunson J, Zhao M, Tan J, et al. Health related quality of life in patients with chronic gastritis and peptic ulcer and factors with impact: a longitudinal study. BMC Gastroenterol. 2014; 14:149


Giannini F, Candilio L, Mitomo S, Ruparelia N, Chieffo A, Baldetti L, et al. A Practical Approach to the Management of Complications During Percutaneous Coronary Intervention. JACC: Cardiovascular Interventions. 2018; 11(18):1797-810


Apple R, Samuels LR, Fonnesbeck C, Schlundt D, Mulvaney S, Hargreaves M, et al. Body mass index and health-related quality of life. Obes Sci Pract. 2018; 4(5):417-26


Arrospide A, Machón M, Ramos-Goñi JM, Ibarrondo O, Mar J. Inequalities in health-related quality of life according to age, gender, educational level, social class, body mass index and chronic diseases using the Spanish value set for Euroquol 5D-5L questionnaire. Health Qual Life Outcomes. 2019; 17(1):69


Xu RH, Cheung AWL, Wong EL-Y. Examining the health-related quality of life using EQ-5D-5L in patients with four kinds of chronic diseases from specialist outpatient clinics in Hong Kong SAR, China. Patient preference and adherence. 2017; 11:1565-72


Grochtdreis T, Dams J, Konig HH, Konnopka A. Health-related quality of life measured with the EQ-5D-5L: estimation of normative index values based on a representative German population sample and value set. The European journal of health economics : HEPAC : health economics in prevention and care. 2019; 20(6):933-44


Edgerton JD, Robert LW, Below Sv. Education and Quality of life.In In: Land KC, Michalos AC, Sirgy MJ, editors.editors Handbook of Social Indicatiors and Quality of Life Research. Dordrecht: Springer. 2012; p p. 265-96.


Green S, Cooper AB. Occupation as a quality of life consituent: A nursing home perspective. Bristish Journal of Occupational Therapy. 2000; 63(1):17-24


Flor LS, Campos MR, Laguardia J. Quality of life, social position and occupational groups in Brazil: evidence from a population-based survey. Revista Brasileira de Epidemiologia. 2013; 16:748-62


Van MH, Giang KB, Ngoc NB, Hai PT, Huyen DT, Khue LN, et al. Prevalence of tobacco smoking in Vietnam: findings from the Global Adult Tobacco Survey 2015. International journal of public health. 2017; 62(Suppl 1):121-9


Bao GK, Van MH, Allebeck P. Alcohol consumption and household expenditure on alcohol in a rural district in Vietnam. Global Health Action. 2013; 6(1):18937


Shaper AG, Wannamethee G, Walker M. Alcohol and mortality in British men: explaining the U-shaped curve. Lancet. 1988; 2(8623):1267-73


Song T, Ding Y-w, Sun Y, He Y-N, Qi D-j, Wu Y, et al. A population-based study on health-related quality of life among urban community residents in Shenyang, Northeast of China. BMC Public Health. 2015; 15(1):921


World Health Organization. Tobacco. 2019 [[cited 27/01/2020]]. Available from: https://www.who.int/news-room/fact-sheets/detail/tobacco.


Xue C, Bian L, Xie YS, Yin ZF, Xu ZJ, Chen QZ, et al. Impact of smoking on health-related quality of Life after percutaneous coronary intervention treated with drug-eluting stents: a longitudinal observational study. Health Qual Life Outcomes. 2017; 15(1):1


Halaweh H, Willen C, Grimby-Ekman A, Svantesson U. Physical Activity and Health-Related Quality of Life Among Community Dwelling Elderly. J Clin Med Res. 2015; 7(11):845-52


Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn Ellen J, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease. Circulation. 2019; 0(0) CIR.0000000000000678


Masquelier B, Hug L, Sharrow D, You D, Hogan D, Hill K, et al. Global, regional, and national mortality trends in older children and young adolescents (5–14 years) from 1990 to 2016: an analysis of empirical data. The Lancet Global Health. 2018; 6(10):e1087-e99


Deandrea S, Lucenteforte E, Bravi F, Foschi R, La Vecchia C, Negri E. Risk factors for falls in community-dwelling older people: a systematic review and meta-analysis. Epidemiology. 2010; 21(5):658-68


Tonet E, Maietti E, Chiaranda G, Vitali F, Serenelli M, Bugani G, et al. Physical activity intervention for elderly patients with reduced physical performance after acute coronary syndrome (HULK study): rationale and design of a randomized clinical trial. BMC Cardiovascular Disorders. 2018; 18(1):98