Abstract
Purpose
During the COVID-19 pandemic, widespread public health measures were implemented to control community transmission. The association between these measures and health-related quality of life (HRQOL) among patients following percutaneous coronary intervention has not been studied.
Methods
We included consecutive patients undergoing percutaneous coronary intervention (PCI) in the state-wide Victorian Cardiac Outcomes Registry between 1/3/2020 and 30/9/2020 (COVID-19 period; n = 5024), with a historical control group from the identical period one year prior (control period; n = 5041). HRQOL assessment was performed via telephone follow-up 30 days following PCI using the 3-level EQ-5D questionnaire and Australian-specific index values.
Results
Baseline characteristics were similar between groups, but during the COVID-19 period indication for PCI was more common for acute coronary syndromes. No patients undergoing PCI were infected with COVID-19 at the time of their procedure. EQ-5D visual analogue score (VAS), index score, and individual components were higher at 30 days following PCI during the COVID-19 period (all P < 0.01). In multivariable analysis, the COVID-19 period was independently associated with higher VAS and index scores. No differences were observed between regions or stage of restrictions in categorical analysis. Similarly, in subgroup analysis, no significant interactions were observed.
Conclusion
Measures of HRQOL following PCI were higher during the COVID-19 pandemic compared to the previous year. These data suggest that challenging community circumstances may not always be associated with poor patient quality of life.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11136-021-03056-0.
Keywords: COVID-19, Cardiovascular disease, Percutaneous coronary intervention, Health-related quality of life, Public health
Introduction
The COVID-19 pandemic has led to significant obstacles in delivering health care for non-COVID-19 conditions. For patients with cardiovascular disease, several countries identified markedly lower rates of PCI for STEMI and delays in treatment during periods of uncontrolled community COVID-19 transmission [1–5]. Similarly, concerns have been raised regarding appropriate follow up for patients following cardiac conditions with a transition to telehealth-based services. Concerningly, increases in deaths due to ischemic heart disease and cardiac arrest during COVID-19 have been observed in some regions [6, 7].
In Australia, the first two waves of sustained community transmission of COVID-19 during 2020, both occurred in the south-eastern state of Victoria, with a population of 6.4 million people. To address these waves, the Victorian government instituted a variety of strict public health measures, including one of the longest periods of mandatory home-confinement during the pandemic (112 days) [8, 9]. Somewhat uniquely to Victoria, overall case numbers of COVID-19 remained relatively low during the strict lockdown, and full medical services remained available for patients that required admission to hospital. These control measures were undoubtedly successful in eliminating community transmission. However, the impact of these public health measures on health-related quality of life (HRQOL) and care delivery for other health conditions, including cardiovascular conditions, is unclear. Furthermore, there are scant data regarding the impact of the COVID-19 period and public health measures on HRQOL internationally with all studies to date limited to small cohorts and many limited by the lack of a control group [10–26].
This study sought to assess the association between COVID-19 and measures of HRQOL in a large, state-based PCI cohort in Victoria, Australia with comparison to an identical time period 1 year prior. Further, we aimed to determine subgroups that may be more affected by COVID-19 public health measures, including comparing patients from regional areas, where public health measures were less restrictive.
Methods
This was an observational cohort study of consecutive adult patients undergoing PCI procedures prospectively enrolled in the state-wide Victorian Cardiac Outcomes Registry (VCOR) in Victoria, Australia. Patients were included in the study if they were entered into VCOR during the defined COVID-19 period (PCI between 1/3/2020 and 30/9/2020; 30-day HRQOL assessment between 30/3/2020 and 29/10/2020), or during the identical period one year prior (PCI between 1/3/2019 and 30/9/2019; 30-day HRQOL assessment between 30/3/2019 and 29/10/2019).
Data sources and setting
VCOR is an Australian, state-wide clinical quality registry, established in 2012, which collects patient-level data on all patients undergoing PCI in the state of Victoria, Australia (including 14 public and 18 private hospitals). The state of Victoria has a population of approximately 6.4 million people and covers an area of 237,000 km2 in the south-eastern part of Australia. Demographic, clinical, procedural and in-hospital outcome data are recorded on electronic case report forms using standardized definitions for each field. Post-discharge data are obtained via a standardized process involving medical record review and 30-day telephone follow up, and 30-day outcomes collected include major adverse cardiac events (MACE), myocardial infarction (MI), major bleeding, mortality, readmissions, revascularization procedures, and health-related quality of life (HRQOL). Periodic independent audits assess data quality at each participating site. The cumulative result of audits between 2013 and 2019 demonstrate a 98.6% agreement between VCOR data and hospital medical records [27, 28]. Overarching VCOR ethics approval was gained from the Alfred Hospital Ethics Committee (approval 47/12). Approval was gained from each individual hospital’s ethics committee prior to participation in the registry. An “opt-out” consent approach is used by participating hospitals, resulting in almost all patients undergoing PCI in the state being enrolled in the registry. A Participant Information Statement is provided detailing the registry processes, rationale and ethics approvals, and registry contact information is provided for patients to withdraw their participation if preferred. Ethics approval for this specific analysis was also gained from the Alfred Hospital Ethics Committee (approval 727/20).
Health-related quality of life
HRQOL was determined using the EuroQol 5-Dimensional 3-level (EQ-5D-3L) questionnaire completed during telephone follow up at 30 days following PCI. The EQ-5D-3L is a generic measure of HRQOL comprising five dimensions—mobility, self-care, usual activities, pain/discomfort, and anxiety/depression; each of these were assessed on a 3-point ordinal scale [no problems (1 point), some problems (2 points), severe problems (3 points)]. Each dimension is combined to form one score profile out of 243 (35) possible health states ranging from 11111 (perfect health) to 33333 (worst health). This score profile may then be converted into an index score via population specific scoring algorithms using the time trade-off method. The Australian scoring algorithm was used to calculate index scores, with potential values ranging from − 0.217 to 1, whereby negative index score values indicate health states perceived to be worse than death [29]. The EQ-5D-3L also includes a single global rating of self-perceived health using a visual analogue scale (VAS) ranging from 0, indicating worst possible health state, to 100, indicating best possible health state.
Data definitions
Indication for PCI was classified as ST-elevation myocardial infarction (STEMI), non-ST-elevation acute coronary syndrome (NSTEACS), and stable ischemic heart disease (SIHD) presentations according to standard definitions [30, 31]. Geographic remoteness was determined through each patient’s residential area postcode using The Accessibility and Remoteness Index of Australia (ARIA)—a geographic accessibility index available through the Australian Bureau of Statistics that divides Australia into five classes of remoteness to reflect relative access to services in non-metropolitan Australia by determining road distance to the nearest urban center [32]. In this system, the five classes of remoteness include ‘Major City’, ‘Inner Regional’, ‘Outer Regional’, ‘Remote’, and ‘Very Remote’. Due to low numbers of ‘Remote’ and ‘Very Remote’ patients, these two categories were combined with ‘Outer Regional’ for the purposes of this study. Socio-economic status (SES) was determined using Socio-Economic indexes for Areas (SEIFA) score, a well-validated system developed by the Australian Bureau of Statistics from data collected in the national Census in 2011 [33]. To determine the SEIFA score, each residential area postcode in the state of Victoria is ranked and placed in deciles based on a combination of factors including household income, unemployment rate, home and motor vehicle ownership, educational level, and non-English speaking background. For this study, the SEIFA score was divided into quintiles, with the 1st quintile including patients living in the lowest 2 SEIFA score deciles (most disadvantaged) and the 5th quintile including patients living in the highest 2 SEIFA score deciles (least disadvantaged). In the subgroup analysis, ‘lower SES’ was defined as patients within SEIFA deciles 1–5. Procedural success was defined as the successful treatment of all lesions and the absence of any major in-hospital complications.
Selection of time periods and COVID-19 variables
The first Australian case of COVID-19 was identified on the 25th January 2020, with the World Health Organization declaring COVID-19 a ‘Public Health Event of International Concern’ on the 30th January and a pandemic on the 11th March. In Victoria, Australia, home confinement was first introduced on 30th March 2020 in the setting of the first wave of community transmission, which occurred from early March until late May (peak new daily cases 111 people on 28th March 2020). The second wave in Victoria lasted from mid-June until mid-October (peak new daily cases 725 people on 5th August 2020). For this study, we selected 1st March 2020 as the start date for the COVID-19 period until 30th September 2020. HRQOL data was collected 30 days after PCI, therefore representing a period from 30th March 2020 (the first date of home confinement in Victoria) until 29th October 2020 (at the completion of the second Victorian wave). For most of the pandemic, a four tier system of public health measures was instituted by the Victoria government ranging from Stage 1 (no or minimal restrictions) to Stage 4 (home confinement); see Fig. 1 and Supplemental Table S1. COVID-19 variables included in the study were determined from Victorian Department of Health and Human Services press releases and included number of new daily COVID-19 cases within Victoria and public health restriction stage. For each patient, restriction stage was determined at the time of HRQOL assessment (i.e. 30 days following PCI) and were specific to whether they lived in a metropolitan or regional area (restrictions were frequently different between metropolitan and regional areas).
Fig. 1.
Timeline of health-related quality of life and PCI during the COVID-19 period and control period in Victoria, Australia. Number of state-wide PCI performed per week (top) and weekly mean EQ5D index score 30 days after PCI (second from top) in relation to new daily COVID-19 cases (middle) and public health measures (shaded background) during the COVID-19 pandemic in Victoria, Australia (2020). The red lines indicate during the COVID-19 period (2020) while the blue lines show data from the identical period 12 months earlier (2019). Regional restrictions outside metropolitan Melbourne were different for the latter half of the period studied and are shown at the bottom. Compulsory mask mandates and curfew public health measures are shown by the black dots (second to bottom). Further details regarding public health measures at each stage of restrictions in Victoria are presented in the supplemental material
Statistical analysis
Continuous data are expressed as mean ± SD or median (IQR), as appropriate, and are compared using the Student’s t test or Mann–Whitney U test. Categorical variables are presented as number (percentage) and are compared using the Pearson’s Chi-square test. Multivariable analysis was performed to determine whether the COVID-19 period was independently associated with EQ-5D-3L visual analogue scale or index scores at 30 days after PCI. In addition to time period, 15 other clinically relevant variables were screened for inclusion in the model, and variables with a P value of < 0.25 in univariable analysis were entered into a linear regression using complete case analysis. For the EQ-5D-3L VAS model, variables included were time period, age, sex, body mass index, ACS, ejection fraction ≤ 40%, diabetes, peripheral vascular disease, prior stroke, prior CABG, prior PCI, eGFR, SES, and regional/remote status. For the EQ-5D-3L index score model, variables included were time period, age, sex, ACS, cardiogenic shock, out-of-hospital cardiac arrest (OHCA), ejection fraction ≤ 40%, diabetes, peripheral vascular disease, prior stroke, prior CABG, eGFR, SES, and regional/remote status. Subgroup analysis was performed using multivariable linear regression adjusted for the same variables to determine whether there were any significant interactions among specific subgroups for the observed associations between time period and 30-day HRQOL. To support clinical interpretation of these data, we also defined four ordinal categories in line with previous studies that have correlated EQ5D VAS and index scores with severity of ischemic heart disease symptoms [34]. The following cut-offs were used representing HRQOL being high (VAS 90–100, index 1.0), moderate (VAS 75–89, index 0.75–0.99), low (VAS 60–74, index 0.6–0.74), or very low (VAS < 60, index < 0.6). Statistical analysis was conducted using Stata version 14.2 for Windows (College Station, Texas, USA) and R version 3.6.2 (R Foundation for Statistical Computing, Vienna, Austria) with figures created using the ggplot2 visualization package. All calculated P values were 2 sided, and a P value < 0.05 was considered statistically significant.
Results
A total of 14,581 procedures were entered into the VCOR registry during the defined periods (7042 during the COVID-19 period and 7539 during the control period). Of these, 310 patients (146 COVID-19 period; 164 control period) died within 30 days of their PCI and were excluded. Of the remaining cohort, 4206 patients (1872 COVID-19 period; 2334 control period) did not have any measures of 30-day HRQOL recorded and were also excluded, leaving 5024 patients in the COVID-19 period and 5041 patients in the control period (Supplemental Fig. S1). Differences in patient characteristics between patients with missing QOL data undergoing PCI in the COVID-19 period compared to the control period are shown in Supplemental Table S2, and differences in patient characteristics between patients with and without available QOL data for both groups are shown in Supplemental Table S3. A timeline of public health measures during the first two COVID-19 waves in Victoria, Australia in relation to weekly PCI numbers and mean weekly 30-day EQ-5D-3L index scores is shown in Fig. 1. EQ-5D-3L index scores were on average higher among patients undergoing PCI during the COVID-19 period. There were no patients in Victoria, Australia who underwent PCI while actively infected with COVID-19 during the study period.
Patient characteristics
During the COVID-19 period, patients undergoing PCI were on average younger and rates of non-ST-elevation ACS, STEMI, and impaired left ventricular ejection fraction (≤ 40%) were higher than during the control period, Table 1. Procedural success, length of stay, and 30-day outcomes (including major adverse cardiac events and stroke) were similar between the COVID-19 and control periods. However, rehospitalization rates within 30 days were lower during the COVID-19 period.
Table 1.
Patient characteristics and outcomes
| COVID-19a n = 5024 | Controla n = 5041 | P | |
|---|---|---|---|
| Demographics | |||
| Age (years) | 68 ± 11 | 68 ± 12 | 0.002 |
| < 60 years old | 1319 (26%) | 1197 (24%) | 0.015 |
| 60–69 years old | 1473 (29%) | 1475 (29%) | |
| 70–79 years old | 1470 (29%) | 1582 (31%) | |
| ≥ 80 years old | 762 (15%) | 787 (16%) | |
| Female | 1193 (24%) | 1249 (25%) | 0.228 |
| BMI (kg/m2) | 29 ± 5 | 29 ± 5 | 0.938 |
| ARIA | 0.002 | ||
| Major City | 3667 (74%) | 3538 (71%) | |
| Inner regional | 1058 (21%) | 1212 (24%) | |
| Outer regional/remote | 246 (5%) | 253 (5%) | |
| SEIFA quintile | 0.071 | ||
| 1 (most disadvantaged) | 525 (11%) | 510 (10%) | |
| 2 | 575 (12%) | 675 (13%) | |
| 3 | 1024 (21%) | 997 (20%) | |
| 4 | 1481 (30%) | 1473 (29%) | |
| 5 (least disadvantaged) | 1366 (27%) | 1348 (27%) | |
| Diabetes | 1144 (23%) | 1204 (24%) | 0.130 |
| Prior stroke | 166 (3.3%) | 184 (3.7%) | 0.345 |
| PVD | 145 (2.9%) | 170 (3.4%) | 0.162 |
| eGFR < 60 ml/min/1.73m2 | 1029 (20%) | 956 (19%) | 0.081 |
| Prior PCI | 1780 (35%) | 1766 (35%) | 0.671 |
| Prior CABG | 293 (6%) | 369 (7%) | 0.003 |
| Presentation | |||
| Indication | |||
| Stable IHD | 2634 (52%) | 2951 (59%) | < 0.001 |
| NSTEACS | 1481 (29%) | 1344 (27%) | 0.002 |
| STEMI | 908 (18%) | 746 (15%) | < 0.001 |
| OHCA | 50 (1.0%) | 59 (1.2%) | 0.398 |
| Cardiogenic shock | 51 (1.0%) | 41 (0.8%) | 0.286 |
| EF ≤ 40% | 591 (13%) | 517 (11%) | 0.020 |
| Outcomes | |||
| Procedural success | 4752 (95%) | 4741 (94%) | 0.244 |
| Length of stay (median,IQR) | 2 (1–4) | 2 (1–4) | 0.815 |
| Rehospitalization (30 days) | 559 (11%) | 647 (13%) | 0.008 |
| MACE (30 days) | 63 (1.3%) | 84 (1.7%) | 0.085 |
| Stroke (30 days) | 13 (0.3%) | 11 (0.2%) | 0.677 |
Data are presented as number (%) or mean ± SD unless otherwise indicated
BMI body mass index, ARIA Accessibility and Remoteness Index of Australia, SEIFA Socio-economic indexes for Areas, PVD peripheral vascular disease, OSA obstructive sleep apnea, eGFR estimated glomerular filtration rate, MI myocardial infarction, PCI percutaneous coronary intervention, CABG coronary artery bypass grafts, IHD ischemic heart disease, NSTEACS non-ST-elevation acute coronary syndrome, STEMI ST-elevation myocardial infarction, OHCA out-of-hospital cardiac arrest, EF ejection fraction, MACE major adverse cardiac events
aCOVID-19 period includes patients undergoing PCI in Victoria, Australia between 1/3/20 until 30/9/20, while the control period includes patients undergoing PCI between 1/3/19 until 30/9/19
Health-related quality of life
All measures of HRQOL were higher for patients undergoing PCI during the COVID-19 period compared to the control period, including EQ-5D-3L VAS (80.5 vs. 79.0, P < 0.001) and index score (0.93 vs. 0.91, P < 0.001), as well as for each of the five individual EQ-5D-3L components (mobility, self-care, usual activities, pain/discomfort, anxiety/depression; all P < 0.01), Table 2. The distribution of EQ-5D-3L VAS and index scores for the COVID-19 cohort and the control cohort are depicted in Fig. 2.
Table 2.
Health-related quality of life at 30 days following PCI
| COVID-19 n = 5024 | Control n = 5041 | P | |
|---|---|---|---|
| EQ-5D summary scores | |||
| Visual analogue score | 80.5 ± 14.9 | 79.0 ± 16.0 | 0.0002 |
| Index score | 0.93 ± 0.13 | 0.91 ± 0.15 | < 0.0001 |
| EQ-5D individual components | |||
| Mobility | 0.013 | ||
| No problems | 4552 (91%) | 4481 (89%) | |
| Some problems | 445 (9%) | 528 (11%) | |
| Confined to bed | 13 (0.3%) | 19 (0.4%) | |
| Self-care (wash/dress) | 0.002 | ||
| No problems | 4826 (96%) | 4772 (95%) | |
| Some problems | 168 (3.4%) | 237 (4.7%) | |
| Unable to perform | 11 (0.2%) | 13 (0.3%) | |
| Usual activities | 0.002 | ||
| No problems | 4423 (88%) | 4322 (86%) | |
| Some problems | 536 (11%) | 639 (13%) | |
| Unable to perform | 42 (0.8%) | 56 (1.1%) | |
| Pain or discomfort | < 0.0001 | ||
| None | 4467 (89%) | 4271 (86%) | |
| Moderate | 520 (10%) | 689 (14%) | |
| Extreme | 24 (0.5%) | 33 (0.7%) | |
| Anxiety/depression | < 0.0001 | ||
| None | 3888 (88%) | 3579 (85%) | |
| Moderate | 469 (11%) | 562 (13%) | |
| Extreme | 47 (1.1%) | 49 (1.2%) | |
Summary scores are presented as mean ± SD, individual components are presented as number (%)
EQ-5D-3L EuroQol 5-Dimension 3 Level, PCI Percutaneous Coronary Intervention
Fig. 2.
Distribution of health-related quality of life scores 30 days following PCI during the COVID-19 pandemic (red) and the identical period one year prior (blue). The left panel shows the distribution of EQ5D index scores 30 days following PCI demonstrating higher scores during the COVID-19 period. The dotted lines indicate the mean for each group (red indicating the COVID-19 period and blue indicating the control period). The right panel shows similar results for EQ5D visual analogue scale scores. EQ5D = EuroQol 5-Dimensional score (color figure online)
Multivariable analysis
In multivariable analysis, undergoing PCI during the COVID-19 period was independently associated with higher 30-day EQ-5D-3L VAS score (β 1.13, 95% CI 0.26–2.00, P = 0.011) and index score (β 0.017, 95% CI 0.011–0.023, P < 0.001). Other variables associated with higher HRQOL scores included higher socio-economic status, higher eGFR (VAS only), and regional/remote residence (VAS only). Variables associated with lower 30-day HRQOL scores included age (VAS only), female sex, body mass index (VAS only), acute coronary syndromes, ejection fraction ≤ 40%, diabetes, peripheral vascular disease (index only), prior stroke, prior CABG (index only), and prior PCI (VAS only) (see Table 3).
Table 3.
Variables associated with health-related quality of life scores at 30 days following PCI
| Variable | EQ-5D visual analogue scale | EQ-5D index score | ||||
|---|---|---|---|---|---|---|
| β | 95% CI | P | β | 95% CI | P | |
| COVID-19 period (2020) | 1.13 | 0.26 to 2.00 | 0.011 | 0.017 | 0.011 to 0.023 | < 0.001 |
| Age | − 0.07 | − 0.12 to − 0.02 | 0.005 | 0.000 | 0.000 to 0.000 | 0.314 |
| Sex (Female) | − 2.85 | − 3.90 to − 1.81 | < 0.001 | − 0.025 | − 0.033 to − 0.018 | < 0.001 |
| Body mass index | − 0.21 | − 0.30 to − 0.11 | < 0.001 | |||
| Acute coronary syndrome | − 1.71 | − 2.61 to − 0.80 | < 0.001 | − 0.014 | − 0.021 to − 0.008 | < 0.001 |
| Cardiogenic shock | − 0.002 | − 0.035 to 0.031 | 0.921 | |||
| OHCA | − 0.029 | − 0.062 to 0.005 | 0.095 | |||
| EF ≤ 40% | − 1.82 | − 3.16 to − 0.48 | 0.008 | − 0.013 | − 0.022 to − 0.003 | 0.012 |
| Diabetes | − 2.28 | − 3.34 to − 1.23 | < 0.001 | − 0.016 | − 0.023 to − 0.008 | < 0.001 |
| PVD | 0.62 | − 2.01 to 3.24 | 0.648 | − 0.030 | − 0.049 to − 0.012 | 0.001 |
| Prior stroke | − 3.27 | − 5.76 to − 0.78 | 0.010 | − 0.032 | − 0.050 to − 0.015 | < 0.001 |
| Prior CABG | 0.42 | − 1.50 to 2.33 | 0.669 | − 0.014 | − 0.028 to − 0.001 | 0.042 |
| Prior PCI | − 0.66 | − 1.61 to 0.28 | 0.169 | |||
| eGFR | 0.02 | 0.00 to 0.04 | 0.014 | 0.000 | 0.000 to 0.000 | 0.098 |
| Socio-economic statusa | 0.35 | 0.17 to 0.54 | < 0.001 | 0.002 | 0.001 to 0.003 | 0.006 |
| Regional/remote | 3.76 | 2.74 to 4.78 | < 0.001 | − 0.005 | − 0.013 to 0.002 | 0.175 |
Relevant clinical variables with a P < 0.25 in univariable analysis were included in a multivariable linear regression demonstrating an independent association between undergoing PCI during the COVID-19 period and higher health-related quality of life scores at 30 days in comparison to the identical period 1 year prior
OHCA out-of-hospital cardiac arrest, EF ejection fraction, PVD peripheral vascular disease, CABG coronary artery bypass surgery, PCI percutaneous coronary intervention, eGFR estimated glomerular filtration rate
aSocio-economic Indexes for Areas (SEIFA) decile (i.e. each decile higher on the SEIFA index is associated with a 0.35 unit increase in EQ5D visual analogue scale score
Categorical analysis
Categorical analysis demonstrated significant differences in EQ-5D-3L VAS and index score categories at 30 days following PCI between patients during the COVID-19 period and control period (Fig. 3, blue panel). These differences persisted when separated by metropolitan or regional status despite differing public health restriction measures between the two regions. When limited to patients in the COVID-19 cohort, no differences were observed between stage of public health restrictions and categories of HRQOL, including when stratified by metropolitan and regional status (Fig. 3, red panel).
Fig. 3.
Categorical analysis of health-related quality of life following PCI. Left panel (blue) compares EQ5D index score (top) and visual analogue scale (bottom) between patients undergoing PCI during the COVID-19 period compared to the control period showing significantly higher EQ5D scores across all patients (left) and separated by metropolitan (middle) and regional/rural (right) status. Right panel (red) compares health-related quality of life scores across stages of public health restrictions in the COVID-19 cohort (n = 5024) demonstrating no differences in HRQOL between stages, including when separated by metropolitan and regional status (color figure online)
Subgroup analysis
In subgroup analysis among clinically relevant variables for the EQ-5D-3L VAS and index scores, with adjustment for variables included in the main multivariable analysis, no significant interactions were observed for age, sex, STEMI indication, socio-economic status, or region (Supplemental Fig. S2).
Discussion
In this state-wide study, we assessed HRQOL among patients following PCI during the COVID-19 pandemic in Victoria, Australia. The major findings can be summarized as follows: (1) state-wide PCI numbers were marginally lower during COVID-19, mainly relating to lower rates of PCI for stable angina syndromes, but in-hospital and 30-day outcomes remained unchanged; (2) all measures of HRQOL 30 days following PCI were higher during the COVID-19 period compared to the identical period one year prior; (3) differences in HRQOL persisted among both metropolitan and regional patients in spite of differing public health measures; and (4) within the COVID-19 cohort, HRQOL was not different when stratified by stage of public health restrictions. To our knowledge, this is the first large, population-based study with a historical control group to demonstrate higher patient-perceived health status during a period of highly challenging community circumstances.
During the first two waves of COVID-19 community transmission in Victoria, Australia, the state government instituted prolonged and wide-reaching public health measures aimed at suppressing, and if possible eliminating, community disease transmission [9]. The first period of mandated home-confinement lasted for 42 days and the second period lasted 112 days—one of the longest periods of strict home-confinement aimed at controlling COVID-19 community transmission anywhere in the world [8]. Each of these periods was successful at eliminating community transmission. During these strict measures, new daily COVID-19 case numbers remained relatively low in comparison to other countries (peak 111 during the first wave and peak 725 per day during the second wave), and in a state of 6.4 million people, individuals had a relatively low likelihood of being personally affected by COVID-19 infection. The current study therefore largely represents the impact of strict home-confinement measures on HRQOL following PCI rather than the impact of uncontrolled COVID-19 community transmission. Importantly, no patients included in the study had active COVID-19 infections at the time of their PCI procedure.
In this study, we demonstrated improved HRQOL among patients with cardiovascular disease 30 days following PCI during the COVID-19 period. This observation was sustained across all individual components of the EQ-5D score, and unaffected by geographic region or stage of public health restrictions. Several studies have assessed the impact of COVID-19 on quality of life among the general population and specific patient populations. So far, these studies have been limited by significantly smaller cohort sizes, with many also limited by a lack of a comparative control group. In the general population, COVID-19 has had a mixed or negative impact on HRQOL. Measures of anxiety and depression were worse in most studies across multiple different countries [10–14, 16]. However, in some studies measures of self-perceived health were not affected, and resilience, social networking and interconnectedness improved [15, 17–19]. In specific disease populations, one large observational cohort study (n = 1613) routinely collected HRQOL (EQ-5D) data among patients following hand surgery and compared the COVID-19 period with an identical period from 2018 to 2019 [22]. No meaningful differences in HRQOL were observed. Other studies have been limited by small cohort sizes and often no comparative group, showing neutral (inflammatory bowel disease, cancer) [20, 21, 23], mixed (Alzheimer’s) [24], or negative (common variable immuno-deficiency, Parkinson’s disease) [25, 26] impacts of COVID-19 on HRQOL among various disease populations.
Early during the COVID-19 pandemic, concerns were raised regarding maintaining adequate delivery of cardiac care [2]. Several countries noted marked decreases in rates of PCI for STEMI and heart failure admissions during periods of uncontrolled community transmission [2–5, 35]. Similarly, rates of diagnostic testing for cardiac disease were reduced, and access to rehabilitation, family supports and prompt clinic review following a cardiovascular admission have been impacted [36, 37]. Our study represents a unique set of circumstances, whereby despite strict prolonged home-confinement measures, there were low rates of COVID-19 infection in the community, and full cardiac services were available to patients that ended up in hospital. It is worth noting that there were higher rates of STEMI and NSTEACS, possibly representing a tendency for patients with stable angina to delay presentation until ACS during the pandemic. At the peak of the 2nd wave in Victoria, there was a preference to defer non-urgent PCI procedures and patients were required to undergo COVID-19 screening prior to non-emergent procedures. However, overall, PCI numbers were only marginally reduced compared to 1 year prior, early outcomes were unchanged, and all individual components of HRQOL were higher. This apparent higher QOL is likely multifactorial, but may be related to a period of forced home respite rather than feeling pressured to quickly return to their usual responsibilities (although this point is speculative). Moreover, although in-person clinics and rehabilitation services were disrupted, several studies have shown high patient satisfaction and higher attendance rates among patients following up with telehealth services [38, 39]. At the commencement of this study, we hypothesized (as others may have) that HRQOL was likely to be adversely impacted by COVID-19. Therefore, the results of this study were surprising to us, but overall should be reassuring to patients, clinicians, and public health officials.
Limitations
This study has several limitations. First, the study may not be generalisable to other jurisdictions that enforced public health measures during COVID-19. Our data reflect HRQOL outcomes in a specific state-wide region of Australia. These data are influenced by specific public health measures, daily COVID-19 case numbers, government services, financial supports for hardship related to the pandemic, and local practices of cardiac care. Substantial financial supports were available for Australians that were unemployed during the pandemic, which may have led to less financial stress than in other countries. Furthermore, these results might be vulnerable to collider bias, for example, a person’s decision to present to hospital for a PCI procedure might have been influenced by their quality of life as well as the COVID-19 period. Second, approximately one quarter of the cohort did not have any measure of HRQOL and were therefore excluded—nonetheless, among patients with missing data, baseline characteristics were similar between the COVID-19 and control groups (Supplemental Tables S2 and S3). The EQ-5D-3L tool is well validated, but is only a measure of HRQOL rather than being a disease specific measure, and is known to have a significant ceiling effect and therefore a difference in HRQOL between periods among patients with higher HRQOL scores may not have been elicited from this study.
Conclusions
In this large, state-wide, observational cohort study, HRQOL among cardiac patients undergoing PCI was higher during the COVID-19 period compared to 1 year prior. Overall, the study highlights the resilience of PCI populations during the pandemic despite strict public health measures aimed at controlling community transmission of COVID-19. These data suggest that difficult circumstances may not always be associated with poor patient quality of life.
Supplementary Information
Below is the link to the electronic supplementary material.
Abbreviations
- HRQOL
Health-related quality of life
- EQ-5D-3L
EuroQol 5-dimensional 3-level questionnaire
- PCI
Percutaneous coronary intervention
- VCOR
Victorian cardiac outcomes registry
- STEMI
ST-elevation myocardial infarction
- NSTEMI
Non-ST-elevation myocardial infarction
- ACS
Acute coronary syndrome
- MACE
Major adverse cardiovascular events
- MI
Myocardial infarction
- CABG
Coronary artery bypass grafts
- BMI
Body mass index
- HR
Hazard ratio
- OR
Odds ratio
- CI
Confidence interval
Funding
Dr Dawson’s work is supported by National Heart Foundation and National Health and Medical Research Council of Australia (NHMRC) postgraduate scholarships. Professor Duffy’s work is supported by a NHMRC Grant (Grant No. 1111170). Professor Reid is supported by a NHMRC Principal Research Fellowship (Grant No. 1136972). A/Prof Stub is supported by National Heart Foundation grants.
Data availability
The data underlying this article may be shared on reasonable request to the VCOR data custodian (Professor Chris Reid) in accordance with Monash University policies.
Declarations
Conflict of interest
All authors declare that they have no conflict of interest to disclose.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data underlying this article may be shared on reasonable request to the VCOR data custodian (Professor Chris Reid) in accordance with Monash University policies.