Associations between demographic, disease related, and treatment pathway related variables and health related quality of life in primary care patients with coronary heart disease

Gender differences in health-related quality of life and psychological distress among coronary patients: Does comorbidity matter? Results from the ESC EORP EUROASPIRE V registry

AIMS

This study aimed to provide an overview on contemporary gender differences in HRQoL/psychological distress and their relationship with comorbidity burden among European coronary heart disease (CHD) patients.

METHODS

Analyses were based on the cross-sectional ESC EORP EUROASPIRE V survey. Consecutive patients (aged 18-80 years), hospitalized for a first or recurrent coronary event were included in this study. Data at hospital discharge and at follow-up (6 to 24 months after hospitalisation) were collected.

RESULTS

Data were available for 8261 patients of which 25.8% women. Overall, women reported a worse EQ-5D-5L index score (0.73 vs. 0.81; P < 0.001), EQ-VAS (63.1 vs. 66.0; P = 0.001), global HeartQoL (1.94 vs. 2.26; P < 0.001), physical HeartQoL (1.96 vs. 2.30; P < 0.001), emotional HeartQoL (1.88 vs. 2.18; P < 0.001), HADS-A (6.69 vs. 4.99; P < 0.001), and HADS-D (5.73 vs. 4.62; P < 0.001) compared to men. Also, women were more likely to have comorbidities compared to men (1 comorbidity: 38.7% vs. 35.0%, 2 comorbidities: 9.7% vs. 7.5%; P < 0.001). There is indication that heart failure (EQ-VAS) and diabetes (global HeartQoL, emotional HeartQoL, physical HeartQoL, and HADS-D) interacted with gender and modulate the relationship with HRQoL, in disfavour of women.

CONCLUSION

Substantial gender-based health inequalities in terms of HRQoL and psychological distress were found, in disfavour of women. Women had worse HRQoL and psychological distress outcomes when having comorbidities. To a limited extent, comorbidity and women had a negative/synergistic effect on HRQoL. Special attention should be given to this population groups within daily clinical practice.

Factors associated with health-related quality of life in patients with coronary heart disease

Coronary heart disease (CHD) contributes to decreased health-related quality of life (HRQOL). This review article investigates the factors that can affect the HRQOL in CHD patients. A literature search from PubMed and EBSCO databases was performed until March 2021 with predetermined keywords. The review of 15 included articles showed that many factors that can affect the HRQOL by using EQ-5D instrument in CHD patients, such as education, gender, comorbidity, percutaneous coronary intervention (PCI)/coronary artery bypass graft (CABG) intervention, patient-physician interaction, obesity, physical activity, numbers of medication, smoking, self-efficacy, social/family life, alcohol drinking, income, employment, and behavioral risk factor profile. The top three factors associated with HRQOL in CHD patients were education, gender, and comorbidity. Therefore, we should pay more attention to CHD patients with lower education levels, females, and comorbidity.

The Associations Between Patients' Characteristics and the Quality of Life Among Acute Coronary Syndrome Patients in Jordan: A Cross-Sectional Study

Introduction

Acute coronary syndrome (ACS) is one of the most significant leading causes of death and disability in the world. The quality of life (QoL) score is used to evaluate the impact of ACS treatments on the patients' physical, emotional, and social functioning. It is considered a significant indicator of the progress of the patients' health status and is useful in predicting patients' needs for continuing, modifying, or changing their treatment plans.

Objective

To identify the associations between patients' characteristics and the QoL among ACS patients in Jordan.

Methods

A descriptive cross-sectional study was conducted using a convenience sample of 372 participants with ACS from six referral hospitals in Jordan.

Results

Jordanian patients with higher educational level and exercise had significant and positive association with QoL (β = 0.257, p < .001), (β = 0.191, p < .001), respectively. Also, patients who reported having dyslipidaemia and having unstable angina (UA) had lower score of QoL (β = -0.165, p < .001), (β = -0.149, p < .001), respectively. Finally, gender and working status did not significantly appear to have an association with the total QoL.

Conclusions

This study sheds light on the importance of increasing the level of patients' awareness about their illness by educating them about it and encouraging them to engage in physical activity programs.

Methodology of the health economic evaluation of the Feel4Diabetes-study

BACKGROUND

The clinical and economic burden of type 2 diabetes mellitus on society is rising. Effective and efficient preventive measures may stop the increasing prevalence, given that type 2 diabetes mellitus is mainly a lifestyle-driven disease. The Feel4Diabetes-study aimed to tackle unhealthy lifestyle (unhealthy diet, lack of physical activity, sedentary behaviour, and excess weight) of families with a child in the first grades of elementary school. These schools were located in regions with a relatively low socio-economic status in Belgium, Bulgaria, Finland, Greece, Hungary and Spain. Special attention was paid to families with a high risk of developing type 2 diabetes mellitus.

METHODS

The aim of this paper is to describe the detailed methodology of the intervention's cost-effectiveness analysis. Based on the health economic evaluation of the Toybox-study, both a decision analytic part and a Markov model have been designed to assess the long-term (time horizon of 70 year with one-year cycles) intervention's value for money. Data sources used for the calculation of health state incidences, transition probabilities between health states, health state costs, and health state utilities are listed. Intervention-related costs were collected by questionnaires and diaries, and attributed to either all families or high risk families only.

CONCLUSIONS

The optimal use of limited resources is pivotal. The future results of the health economic evaluation of the Feel4Diabetes-study will contribute to the efficient use of those resources.

The Likert scale is a powerful tool for quality of life assessment among patients after minimally invasive coronary surgery

Introduction

Health-related quality of life (QoL) is an acknowledged index of treatment effectiveness. There are several methods of its evaluation which are predisposed to different risk of bias.

Aim

To investigate the agreement between objective and subjective tools of QoL assessment in patients who underwent endoscopic atraumatic coronary artery bypass (EACAB) grafting.

Material and methods

This prospective observational study covered 705 consecutive patients who underwent EACAB between April 1998 and December 2010. Quality of life was assessed in a follow-up of 2132 ±1313 days among 482 subjects using the WHOQoL-BREF questionnaire as an objective tool and the Likert scale as a more subjective method.

Results

There was good agreement between a 5-step Likert scale and a 5-step BREF Q1 (‘overall quality of life’) and Q2 (‘general health’) with a concordance correlation coefficient of CCC = 0.64 (95% CI: 0.58–0.69) and CCC = 0.49 (95% CI: 0.43–0.55), respectively. There was also a statistically significant correlation between answers reported using the Likert scale and all domains of BREF: physical health (R = 0.54, p < 0.001), psychological health (R = 0.56, p < 0.001), social relationships (R = 0.45, p < 0.001) and environment (R = 0.56, p < 0.001).

Conclusions

The Likert scale is useful in QoL assessment in patients after minimally invasive coronary surgery. This simple and easy-to-use screening method may be used interchangeably with a more reliable but also more complex questionnaire tool.

Health related quality of life among myocardial infarction survivors in the United States: a propensity score matched analysis

Background

Little is known regarding the health-related quality of life among myocardial infarction (MI) survivors in the United States. The purpose of this population-based study was to identify differences in health-related quality of life domains between MI survivors and propensity score matched controls.

Methods

This retrospective, cross-sectional matched case-control study examined differences in health-related quality of life (HRQoL) among MI survivors of myocardial infarction compared to propensity score matched controls using data from the 2015 Behavioral Risk Factor Surveillance System (BRFSS) survey. Propensity scores were generated via logistic regression for MI survivors and controls based on gender, race/ethnicity, age, body mass index (BMI), smoking status, and comorbidities. Chi-square tests were used to compare differences between MI survivors to controls for demographic variables. A multivariate analysis of HRQoL domains estimated odds ratios. Life satisfaction, sleep quality, and activity limitations were estimated using binary logistic regression. Social support, perceived general health, perceived physical health, and perceived mental health were estimated using multinomial logistic regression. Significance was set at p < 0.05.

Results

The final sample consisted of 16,729 MI survivors matched to 50,187 controls (n = 66,916). Survivors were approximately 2.7 times more likely to report fair/poor general health compared to control (AOR = 2.72, 95% CI: 2.43–3.05) and 1.5 times more likely to report limitations to daily activities (AOR = 1.46, 95% CI: 1.34–1.59). Survivors were more likely to report poor physical health >15 days in the month (AOR = 1.63, 95% CI: 1.46–1.83) and poor mental health >15 days in the month (AOR = 1.25, 95% CI: 1.07–1.46) compared to matched controls. There was no difference in survivors compared to controls in level of emotional support (rarely/never: AOR = 0.75, 95% CI: 0.48–1.18; sometimes: AOR = 0.73, 95% CI: 0.41–1.28), hours of recommended sleep (AOR = 1.14, 95% CI: 0.94–1.38), or life satisfaction (AOR = 1.62, 95% CI: 0.99–2.63).

Conclusion

MI survivors experienced lower HRQoL on domains of general health, physical health, daily activity, and mental health compared to the general population.

Comorbidities and characteristics of coronary heart disease patients: their impact on health-related quality of life

BACKGROUND

Patients with coronary heart disease (CHD) commonly present with more than one comorbid condition, contributing to poorer health-related quality of life (HRQoL). The aim of our study was to identify the associations between HRQoL and patient characteristics, vascular comorbidities and anxiety/depression disorders.

METHODS

This observational study was conducted in 36 family medicine practices selected by random stratified sampling from all regions of Slovenia. HRQoL was assessed using the European Quality of Life - 5 Dimensions (EQ-5D) questionnaire and EQ Visual Analogue Scale (EQ-VAS). The associations between HRQoL and patient characteristics stratified by demographics, vascular comorbidities, health services used, their assessment of chronic illness care, and anxiety/depression disorders were identified by ordinal logistic regression and linear regression models.

RESULTS

The final sample included 423 CHD patients with a mean age of 68.0 ± SD 10.8 years; 35.2% were female. Mean EQ-VAS score was 58.6 ± SD 19.9 (median: 60 with interquartile range of 45-75), and mean EQ-5D index was 0.60 ± SD 0.19 (median: 0.56 with interquartile range of 0.41-0.76). The statistically significant predictors of a lower EQ-VAS score were higher family physician visit frequency, heart failure (HF) and anxiety/depression disorders (R² 0.240; F = 17.368; p < 0.001). The statistically significant predictor of better HRQoL, according to EQ-5D was higher patient education, whereas higher family physician visit frequency, HF and peripheral artery disease (PAD) were predictors of poorer HRQoL (Nagelkerke R 2 = 0.298; χ 2 = 148.151; p < 0.001).

CONCLUSIONS

Results of our study reveal that comorbid conditions (HF and PAD), family physician visit frequency and years in education are significant predictors of HRQoL in Slovenian CHD patients.

Multivariate Meta-Analysis of Preference-Based Quality of Life Values in Coronary Heart Disease

BACKGROUND

There are numerous health-related quality of life (HRQol) measurements used in coronary heart disease (CHD) in the literature. However, only values assessed with preference-based instruments can be directly applied in a cost-utility analysis (CUA).

OBJECTIVE

To summarize and synthesize instrument-specific preference-based values in CHD and the underlying disease-subgroups, stable angina and post-acute coronary syndrome (post-ACS), for developed countries, while accounting for study-level characteristics, and within- and between-study correlation.

METHODS

A systematic review was conducted to identify studies reporting preference-based values in CHD. A multivariate meta-analysis was applied to synthesize the HRQoL values. Meta-regression analyses examined the effect of study level covariates age, publication year, prevalence of diabetes and gender.

RESULTS

A total of 40 studies providing preference-based values were detected. Synthesized estimates of HRQoL in post-ACS ranged from 0.64 (Quality of Well-Being) to 0.92 (EuroQol European"tariff"), while in stable angina they ranged from 0.64 (Short form 6D) to 0.89 (Standard Gamble). Similar findings were observed in estimates applying to general CHD. No significant improvement in model fit was found after adjusting for study-level covariates. Large between-study heterogeneity was observed in all the models investigated.

CONCLUSIONS

The main finding of our study is the presence of large heterogeneity both within and between instrument-specific HRQoL values. Current economic models in CHD ignore this between-study heterogeneity. Multivariate meta-analysis can quantify this heterogeneity and offers the means for uncertainty around HRQoL values to be translated to uncertainty in CUAs.

Development and validation of the coronary heart disease scale under the system of quality of life instruments for chronic diseases QLICD-CHD: combinations of classical test theory and Generalizability Theory

Background

Quality of life (QOL) for patients with coronary heart disease (CHD) is now concerned worldwide with the specific instruments being seldom and no one developed by the modular approach.

Objectives

This paper is aimed to develop the CHD scale of the system of Quality of Life Instruments for Chronic Diseases (QLICD-CHD) by the modular approach and validate it by both classical test theory and Generalizability Theory.

Methods

The QLICD-CHD was developed based on programmed decision procedures with multiple nominal and focus group discussions, in-depth interview, pre-testing and quantitative statistical procedures. 146 inpatients with CHD were used to provide the data measuring QOL three times before and after treatments. The psychometric properties of the scale were evaluated with respect to validity, reliability and responsiveness employing correlation analysis, factor analyses, multi-trait scaling analysis, t-tests and also G studies and D studies of Genralizability Theory analysis.

Results

Multi-trait scaling analysis, correlation and factor analyses confirmed good construct validity and criterion-related validity when using SF-36 as a criterion. The internal consistency α and test-retest reliability coefficients (Pearson r and Intra-class correlations ICC) for the overall instrument and all domains were higher than 0.70 and 0.80 respectively; The overall and all domains except for social domain had statistically significant changes after treatments with moderate effect size SRM (standardized response mea) ranging from 0.32 to 0.67. G-coefficients and index of dependability (Ф coefficients) confirmed the reliability of the scale further with more exact variance components.

Conclusions

The QLICD-CHD has good validity, reliability, and moderate responsiveness and some highlights, and can be used as the quality of life instrument for patients with CHD. However, in order to obtain better reliability, the numbers of items for social domain should be increased or the items’ quality, not quantity, should be improved.

Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease

Background

A number of studies have shown an association between health-related quality of life (HRQL) and socioeconomic status (SES). Indicators of SES usually serve as potential confounders; associations between SES and HRQL are rarely discussed in their own right. Also, few studies assess the association between HRQL and SES among those with a chronic disease. The study focuses on the question of whether people with the same state of health judge their HRQL differently according to their SES, and whether a bias could be introduced by ignoring these differences.

Methods

The analyses were based on a representative sample of the adult population in Germany (n = 11,177). HRQL was assessed by the EQ-5D-3 L, i.e. the five domains (e.g. ‘moderate or severe problems’ concerning mobility) and the Visual Analog Scale (VAS). SES was primarily assessed by educational level; age, sex and family status were included as potential confounders. Six chronic diseases were selected, each having a prevalence of at least 1% (e.g. diabetes mellitus). Multivariate analyses were conducted by logistic and linear regression.

Results

Among adults with a chronic disease, most ‘moderate or severe problems’ are reported more often in the low (compared with the high) educational group. The same social differences are seen for VAS values, also in subgroups characterized by ‘moderate or severe problems’. Gender-specific analyses show that for women the associations with VAS values can just be seen in the total sample. For men, however, they are also present in subgroups defined by ‘moderate or severe problems’ or by the presence of a chronic disease; some of these differences exceed 10 points on the VAS scale.

Conclusions

Low SES groups seem to be faced with a double burden: first, increased levels of health impairments and, second, lower levels of valuated HRQL once health is impaired. These associations should be analysed and discussed in their own right, based on interdisciplinary co-operation. Social epidemiologists could include measures of HRQL in their studies more often, for example, and health economists could consider assessing whether recommendations based on HRQL scales might include a social bias.