Abstract
Background
Post‐acute sequelae of COVID‐19 (PASC or ‘long COVID’) reflect ongoing symptoms, but these are non‐specific and common in the wider community. Few reports of PASC have been compared with a control group.
Aims
To compare symptoms and objective impairment of functional capacity in patients with previous COVID‐19 infection with uninfected community controls.
Methods
In this community‐based, cross‐sectional study of functional capacity, 562 patients from Western Melbourne who had recovered from COVID‐19 infections in 2021 and 2022 were compared with controls from the same community and tested for functional capacity pre‐COVID‐19. Functional impairment (<85% of the predicted response) was assessed using the Duke Activity Status Index (DASI) and 6‐min walk distance (6MWD) test. A subgroup underwent cardiopulmonary exercise testing before and after exercise training.
Results
Of 562 respondents (age 54 ± 12 years, 69% women), 389 were symptomatic. Functional impairment (<85% predicted metabolic equivalent of tasks) was documented by DASI in 149 participants (27%), and abnormal 6MWD (<85% predicted) was observed in 14% of the symptomatic participants. Despite fewer risk factors and younger age, patients with COVID‐19 had lower functional capacity by 6MWD (P < 0.001) and more depression (P < 0.001) than controls. In a pilot group of seven participants (age 58 ± 12 years, two women, VO2 18.9 ± 5.7 mL/kg/min), repeat testing after exercise training showed a 20% increase in peak workload.
Conclusions
Although most participants (69%) had symptoms consistent with long COVID, significant subjective functional impairment was documented in 27% and objective functional impairment in 14%. An exercise training programme might be beneficial for appropriately selected patients.
Keywords: long COVID, exercise capacity, echocardiography, cardiorespiratory fitness, exercise training
Introduction
The coronavirus disease 2019 (COVID‐19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has brought an unprecedented crisis to public health globally and is still impacting millions of people. According to World Health Organization (WHO) data in March 2023, there have been approximately 758 million confirmed COVID‐19 cases and 6.8 million deaths worldwide, with over 11 million confirmed cases and approximately 20 000 deaths in Australia. 1 There is increasing evidence that many patients with COVID‐19 could experience a wide range of post‐acute sequelae, including significant cardiovascular complications. 2 , 3
Post‐viral symptoms are common (>70%) in the first month after COVID‐19 infection. 4 Fewer patients describe continuing symptoms for 3 months – the arbitrary cut‐point chosen by the WHO for the definition of post‐acute sequelae of COVID‐19 (PASC, or ‘long COVID’). 4 Although the incidence of this problem ranges from 8% to 12%, infection of ~758 million people with COVID‐19 1 means that there is a very large cohort of patients with this condition. Female sex, middle age, the presence of ≥2 comorbidities and the intensity of the original infection are associated with the risk of developing long COVID, 5 but community‐based patients with milder COVID‐19 are far from exempt, 6 although the frequency and intensity of long‐term symptoms seem to be attenuated in vaccinated individuals. 6 , 7 Long COVID is a heterogeneous condition, 8 with clusters caused by autonomic dysfunction, 9 immune activation, endotheliopathy 10 and neuropsychiatric symptoms. The constellation of symptoms – of which debilitating fatigue is a central component 11 , 12 – includes exercise intolerance and functional impairment. It seems likely that the association of reduced functional capacity with depression reflects a common response to ongoing illness, although fatigue may be a symptom of depression. Myocardial injury after COVID‐19 infection – evidenced by biomarkers (e.g. cardiac troponin (Tn)) 13 and imaging evidence of inflammation and overt dysfunction by cardiac magnetic resonance imaging 14 – may be important. Many of these patients have been unwell for months, so there may also be an element of deconditioning. Understanding the long‐COVID phenotypes may better identify patients likely to be responsive to interventions, including exercise training. 15
This study sought to better understand the association of long‐COVID symptoms and functional impairment in a community‐dwelling population who have recovered from the initial illness. It was hypothesised that long‐COVID participants would show heterogeneity of functional capacity, but this would be less than community controls. Accordingly, this study used a cohort of COVID‐19 survivors with and without symptoms to establish the prevalence of reduced functional capacity and the potential responsiveness to rehabilitation.
Methods
Participants
In response to advertising on social media, 562 respondents from Western Melbourne who had COVID‐19 infection in 2021–2022 were recruited into the PERCEIVE study and compared with community‐based subjects who underwent the same tests before the pandemic (2019 and before). For controls, this study included 979 participants (aged 70 ± 4 years) who had been recruited into two previous community‐based studies (VicELF and TasELF) 16 , 17 before the pandemic, and therefore exclude COVID‐19 with a certainty that is not achievable with current control groups. 18 In both groups, patients with known valvular stenosis or regurgitation of moderate or greater severity, history of previous heart failure, mobility impairment that would impact participants' ability to perform exercise or life expectancy <12 months were excluded. The study was approved by the Alfred Human Research Ethics Committee (72455), and all participants gave informed consent.
Study design
Because of lockdowns during the pandemic, the screening process was designed to be initiated online. Patients with a Duke Activity Status Index (DASI) score less than normal for their age or those with a high‐sensitivity Tn >15 ng/L were invited to attend a clinic to assess 6‐min walk distance (6MWD). Cardiopulmonary exercise tests (CPETs) were performed in participants with reduced functional capacity or an abnormal Tn.
Clinical characteristics
Baseline data were collected through validated methods, including self‐administered questionnaires, semi‐structured interviews and clinical assessment. The demographic profile included age, sex, marital status, social support, income, education, ethnicity and language. The clinical profile included the presence of cardiovascular risk factors, comorbid disease and medical therapy, and past/concurrent cardiac and non‐cardiac disease states, including history of cardiovascular risk factors, known coronary artery disease, valvular heart disease and functional class. Validated questionnaires were used to assess sociodemographic, clinical status, depression (PHQ‐9) 19 and overall health and well‐being (AQoL‐8D). 20 Routine biochemistry (Cobase 601, Roche Diagnostics, North Ryde, NSW) included assessment of high‐sensitivity Tn, identified as abnormal (>15 ng/L) and borderline (5–15 ng/L).
Functional capacity
6MWD 21 and DASI 22 were obtained to assess functional capacity in both post‐COVID‐19 patients and controls. Both have been previously validated against peak oxygen uptake and associated with outcome. 23 , 24 DASI was performed as a self‐administered questionnaire; an abnormal test was defined if predicted metabolic equivalent of tasks (METS) were <85% of age‐ and sex‐defined normative values. 25 A 6MWD was performed in line with the American Thoracic Society guidelines. 21 Because age is a significant determinant of 6MWD, a percentage of the expected normal findings was used in this study 26 (<85% of predicted was considered abnormal).
Peak V̇o 2 was determined from breath‐by‐breath gas analysis (Vyntus or MedGraphics CPX/D) following a standardised protocol. 27 Heart rate (HR) and blood pressure were measured at baseline, throughout exercise and in recovery.
Exercise training
Post‐COVID‐19 participants with reduced exercise capacity were offered the opportunity to participate in an exercise training programme. The aim of this exercise intervention was to help participants manage their condition while assisting them in restoring their optimal physical function. This was achieved by engaging in a structured exercise training programme prescribed by an exercise physiologist (EP) and delivered through different modalities depending on the participant's preference.
Participants completed two supervised sessions/week (either in person or online). Continuous exercise sessions were completed on a treadmill, cycle ergometer or as an outdoor walk at moderate intensity of rated perceived exertion (RPE) of 11–13/20 and HR 55–70% of maximum (informed from the participants' baseline CPET). Similarly, interval‐based aerobic activity was performed at high intensity (RPE >16/20, HR max >90%). Generally, this led to most participants performing 30 (or more) min of continuous aerobic activity by the end of the programme. The strength component involved six to eight exercises (a combination of bodyweight, free‐weight or resistance‐bands) with the goal of two sets of 15 repetitions by the end of the programme.
Statistical analysis
This study initially sought to recruit 300 post‐COVID‐19 participants, with the expectation that reduced functional capacity would be present in 50% of patients. 28 However, as the frequency of reduced functional capacity was lower than expected (27%), it required 562 participants to identify the number of initially planned participants with reduced functional capacity (n = 149). This sample size provided greater than sufficient power to detect a significant difference in functional capacity between the post‐COVID‐19 and control cohorts. There were no missing data for the primary endpoint; all participants proceeding to other tests are described.
Categorical variables were reported as numbers and percentages and continuous variables as either mean with standard deviation or median with interquartile range. One‐way analysis of variance was used to determine statistical differences among groups of participants. Logistic regression was used to estimate the associations of variables with binary outcomes. C‐statistics and areas under the curve (AUCs) were used to compare discriminatory power among predictive models. Statistics were performed using standard software STATA 17 (StataCorp, College Station, TX, USA). A P value <0.05 was used to define statistical significance in this study.
Post‐COVID‐19 participants were matched to those in the control cohort using a previously published propensity‐matching method. 29 Because of the age differences between the two samples, two propensity scores were calculated, one based on sex and cardiovascular risk factors and the other based on age and sex. When matching based on sex and risk factors, the majority of post‐COVID‐19 participants (542/562, 96%) were matched 1:1 to their controls. When matching based on age and sex, only 21% (120/562) of the COVID‐19 participants could be matched. Findings from both of these two propensity‐matching scores are shown for comparison.
Results
Clinical status of post‐COVID‐19 patients
Out of 562 post‐COVID‐19 patients who responded to invitations to participate, 55 (10%) were hospitalised for their initial infection. At the time of testing (>1 month after COVID), 173 (31%) were asymptomatic, 65 (11%) were symptomatic for <90 days after infection and 324 (58%) had symptoms for >90 days.
Details of viral variants were not available. However, as Omicron became the dominant COVID‐19 variant in Australia in December 2021, this date was used to separate those with expected Omicron and those with earlier variants. The group with expected Omicron was generally less symptomatic than the remainder (Table 1), especially dyspnoea, but were more likely to have cough/sneeze/running nose. Overall, 80% (447/562) of the study group were vaccinated at the time of their COVID‐19 infection, with 77% (433/562) having at least two doses. None of the participants received antiviral therapy.
Table 1.
Differences in long‐COVID symptoms according to expected COVID‐19 variant
| COVID‐19 variant | ||||
|---|---|---|---|---|
| N (%) | Not Omicron (n = 322) | Likely Omicron (n = 240) | P value | |
| Fever | 5 (1%) | 3 (0.9%) | 2 (0.8%) | 0.90 |
| Shortness of breath/dyspnoea | 170 (30%) | 112 (34.8%) | 58 (24.2%) | 0.006 |
| Fatigue | 278 (49%) | 159 (49.4%) | 119 (49.5%) | 0.96 |
| Chest pain | 82 (14%) | 54 (16.8%) | 28 (11.7%) | 0.09 |
| Cough/sneeze/running nose | 109 (19%) | 46 (14.3%) | 63 (26.2%) | <0.001 |
| Flu‐like symptoms | 59 (10%) | 36 (11.1%) | 23 (9.6%) | 0.54 |
| Palpitation | 74 (13%) | 49 (15.2%) | 25 (10.4%) | 0.09 |
| Diarrhoea | 15 (3%) | 12 (3.7%) | 3 (1.2%) | 0.07 |
| Loss of smell | 44 (8%) | 31 (9.6%) | 13 (5.4%) | 0.066 |
| Loss of taste | 43 (8%) | 25 (7.8%) | 18 (7.5%) | 0.91 |
| Loss of appetite | 19 (3%) | 10 (3.1%) | 9 (3.7%) | 0.67 |
| Abdominal pain | 17 (3%) | 13 (4.0%) | 4 (1.7%) | 0.11 |
| Insomnia | 61 (11%) | 34 (10.5%) | 27 (11.2%) | 0.79 |
| Skin rash or other skin condition | 19 (3%) | 15 (4.6%) | 4 (1.7%) | 0.05 |
| Other symptoms | 88 (16%) | 61 (18.9%) | 27 (11.2%) | 0.013 |
| Any long‐COVID symptoms | 389 (69.2%) | 220 (68.3%) | 169 (70.4%) | 0.59 |
Ongoing symptoms were significantly associated with depressive symptoms, with a relatively large difference in PHQ‐9 scores between patients with and without long‐COVID symptoms. Most patients with ongoing sleep disturbance, flu‐like symptoms, palpitations and chest pain had scores associated with moderate or severe depression (Appendix Table 1). Moderate or severe depression was associated with 14.43‐fold (95% confidence interval (CI): 8.50–24.50) greater odds of having DASI‐METS <85% predicted and 5.05‐fold (95% CI: 1.98–12.84) greater odds of having <85% predicted 6MWD. In a logistic model (AUC: 0.87), moderate to severe depression was associated with sleep disturbance (OR: 4.77 (95% CI: 2.29–9.91)), fatigue (OR: 8.67 (95% CI: 3.48–21.58)), dyspnoea (OR: 4.77 (95% CI: 2.29–9.91)), chest pain (OR: 2.95 (95% CI: 1.49–5.87)) and rash (OR: 2.98 (95% CI: 1.43–6.19)).
Functional impairment
Based on the DASI, 149 (27%) had an estimated exercise capacity <85% predicted METS. Functional impairment was significantly associated with the presence of almost all symptoms, with the exception of fever and disturbed sense of smell (Appendix Table 2). Dyspnoea, fatigue and flu‐like symptoms were among the strongest associations of subjective functional impairment (Table 2).
Table 2.
Association of impaired functional capacity (reduced DASI score) with persistent COVID symptoms
| OR (95% CI) | AUC (95% CI) | |
|---|---|---|
| Fever | 9.58 (1.06–86.41) | 0.51 (0.50–0.52) |
| Shortness of breath/dyspnoea | 4.35 (2.95–6.42) | 0.66 (0.62–0.70) |
| Fatigue | 5.69 (3.75–8.61) | 0.70 (0.66–0.74) |
| Chest pain | 4.50 (2.77–7.33) | 0.60 (0.57–0.64) |
| Cough/sneeze/running nose | 2.40 (1.56–3.70) | 0.57 (0.53–0.61) |
| Flu‐like symptoms | 8.96 (4.82–16.67) | 0.61 (0.58–0.65) |
| Palpitation | 4.30 (2.59–7.15) | 0.59 (0.56–0.63) |
| Diarrhoea | 10.02 (1.79–36.01) | 0.53 (0.51–0.55) |
| Loss of smell | 1.70 (0.90–3.19) | 0.52 (0.49–0.55) |
| Loss of taste | 3.29 (1.75–6.19) | 0.55 (0.52–0.57) |
| Loss of appetite | 22.07 (5.04–96.66) | 0.55 (0.52–0.57) |
| Abdominal pain | 8.18 (2.62–25.47) | 0.53 (0.51–0.55) |
| Insomnia | 4.02 (2.33–6.96) | 0.57 (0.54–0.61) |
| Skin rash/other conditions | 3.38 (1.33–8.56) | 0.52 (0.50–0.54) |
| Other symptoms | 2.13 (1.33–3.39) | 0.55 (0.52–0.59) |
| Any long‐COVID symptoms | 4.70 (2.82–7.81) | 0.63 (0.60–0.67) |
AUC, area under the curve; DASI, Duke Activity Status Index; OR, odds ratio.
Out of 114 with symptoms of significantly impaired functional capacity and who attended for functional assessment, 31 (27%) had a reduction of the 6MWD to <85% age‐predicted. In contrast, only three (2%) of 158 with preserved functional capacity had a below‐predicted 6MWD (Fig. 1). Conversely, 6MWD was >85% predicted in about 80% of people with reduced functional capacity based on DASI. Dyspnoea and fatigue were correlates of symptoms with 6MWD (Appendix Table 3), but although flu‐like symptoms (OR: 3.44 (95% CI: 1.44–8.24)), palpitations (OR: 3.70 (95% CI: 1.63–8.39)) and insomnia (OR: 2.78 (95% CI: 1.14–6.76)) were associated with objective evidence of reduced functional capacity, the prediction was modest (AUC: 0.72, Appendix Table 4).
Figure 1.

Subjective and objective impairment of functional capacity after COVID.
Of 27 symptomatic patients with evidence of functional impairment by 6MWD who underwent CPET, the average peak VO2 was 20 ± 5 mL/min/kg (75 ± 16% of predicted). The 6MWD results were not a good indicator of peakVO2 (r = 0.34); 13 patients with 6MWD ≤85% predicted had average peak VO2 of 20 ± 3 mL/min/kg, compared with 19 ± 6 mL/min/kg in those with a normal 6MWD (P = 0.80). These values represent 71 ± 20% and 78 ± 8% of predicted peak VO2 respectively.
Troponin levels
Tn‐T was elevated (>15 ng/L) in 12 out of 263 participants (5%) and borderline (5–15 ng/L) in 147 (56%). Levels of Tn‐T were not associated with symptoms. There were no differences in those with normal and impaired 6MWD (6.6 ± 4.5 vs 6.0 ± 4.2 ng/L, P = 0.44) or normal and impaired peak VO2 (12.8 ± 5.1 vs 12.2 ± 11.1 ng/L, P = 0.88). Elevated Tn levels were not associated with long‐COVID symptoms or reduced functional capacity.
Clinical features and functional capacity with and without COVID‐19
The same functional features were obtained in the non‐COVID controls (Table 3). The PHQ‐9 score and prevalence of moderate and severe depression were significantly worse in the COVID‐19 group, irrespective of how patients were matched (Table 3).
Table 3.
Differences in clinical features and functional capacity in patients with and without COVID. These data compare participants recovered from COVID‐19 (PERCEIVE study) with patients from the same community with cardiac risk factors before the pandemic (VicELF and TasELF trials) before and after propensity matching for risk factors and demographics
| Before matching | Propensity matched for risk factors (RFs)† | Propensity match for age and sex | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Variables | Vic/TasELF, N = 979 | PERCEIVE, N = 562 | P value | Vic/TasELF, N = 542 | PERCEIVE, N = 542 | P value | Vic/TasELF, N = 120 | PERCEIVE, N = 120 | P value |
| Demographic | |||||||||
| Age | 70.9 ± 4.7 | 54.3 ± 11.8 | <0.001 | 68.8 ± 1.9 | 54.1 ± 11.8 | <0.001 | 68.9 ± 3.7 | 68.8 ± 3.7 | 0.93 |
| Male | 46% | 30% | <0.001 | 30% | 30% | 1.0 | 31% | 35% | 0.49 |
| Comorbidity | |||||||||
| T2DM | 44% | 6% | <0.001 | 6% | 6% | 1.0 | 27.5% | 8.8% | <0.001 |
| HTN | 82% | 21% | <0.001 | 20% | 20% | 1.0 | 93.3% | 41.2% | <0.001 |
| Obesity | 51% | 19% | <0.001 | 19% | 19% | 1.0 | 76.7% | 20.7% | <0.001 |
| Functional capacity | |||||||||
| DASI score | 42.7 ± 11.5 | 42.4 ± 15.4 | 0.65 | 43.7 ± 11.5 | 42.8 ± 15.1 | 0.31 | 45.4 ± 11.3 | 37.2 ± 13.9 | <0.001 |
| METS | 8.0 ± 1.4 | 7.9 ± 1.9 | 0.65 | 8.1 ± 1.4 | 8.0 ± 1.9 | 0.31 | 8.3 ± 1.4 | 7.3 ± 1.7 | <0.001 |
| <85% predicted METS | 4% | 26% | <0.001 | 9% | 26% | <0.001 | 0% | 12.5% | <0.001 |
| 6MWD‡ | 459 ± 89 | 567 ± 98 | <0.001 | 427 ± 66 | 567 ± 97 | <0.001 | 445 ± 67 | 508 ± 90 | <0.001 |
| <85% predicted 6MWD‡ | 15% | 12% | 0.32 | 38% | 13% | <0.001 | 10.8% | 4.1% | 0.10 |
| Mental health | |||||||||
| PHQ‐9 score | 2.0 ± 3.5 | 5.6 ± 5.3 | <0.001 | 1.1 ± 0.8 | 5.5 ± 5.3 | <0.001 | 1.4 ± 1.9 | 4.2 ± 4.5 | <0.001 |
| Moderate/severe depression | 5% | 21% | <0.001 | 0% | 20% | <0.001 | 0% | 11% | <0.001 |
RFs used for propensity matching included sex, type‐2 diabetes mellitus, hypertension and obesity.
Data were only available in 260 matched participants in PERCEIVE.
DASI, Duke Activity Status Index; GLS, global longitudinal strain; HTN, hypertension; LAE, left atrial enlargement; LVH, left ventricular hypertrophy; LVMI, left ventricular mass index; METS, maximum metabolic equivalent of tasks; PHQ‐9, Patient Health Questionnaire 9; T2DM, type‐2 diabetes mellitus; 6MWD, 6‐min walk distance.
Significant differences in functional capacity between the COVID‐19 participants and their controls were only revealed when the groups were matched by age and sex – in other words, the younger age of the COVID‐19 patients masked their functional compromise. Functional impairment was present in COVID‐19 participants regardless of the presence of long‐COVID symptoms. Both functional impairment and depression were more severe and prevalent in COVID‐19 participants with long COVID compared with those without long COVID (Appendix Table 5).
Exercise response
A pilot group of seven participants (age 58 ± 12 years, two women) with reduced functional capacity (estimated METS by DASI 73 ± 12% predicted, peak VO2 18.9 ± 5.7 mL/kg/min) were reassessed after training (Table 4). Participants completed on average 13.4 supervised sessions (range 5–24). At follow‐up testing, all this group showed an increased peak workload (by 20%, P = 0.008) and all but one showed an increase in peak VO2 (by 7.3%, P = 0.057).
Table 4.
Exercise training response. Haemodynamic and cardiopulmonary responses to exercise training over 31 ± 13 weeks
| Baseline | Follow‐up | Delta | P | |
|---|---|---|---|---|
| Rest HR, bpm | 74 ± 10 | 76 ± 13 | −3 ± 6 | 0.74 |
| Rest SBP, mmHg | 150 ± 19 | 130 ± 10 | −12 ± 18 | 0.036 |
| Rest DBP, mmHg | 89 ± 11 | 87 ± 6 | 0 ± 11 | 0.28 |
| Peak SBP, mmHg | 217 ± 23 | 201 ± 26 | −14 ± 19 | 0.253 |
| Peak DBP, mmHg | 110 ± 90 | 96 ± 8 | −30 ± 35 | 0.04 |
| Peak HR, bpm | 153 ± 14 | 156 ± 21 | 11 ± 18 | 0.52 |
| Peak VO2 (mL/kg/min) | 18.9 ± 5.7 | 20.3 ± 6.2 | 1.5 ± 1.7 | 0.0.057 |
| Peak VO2 (L/min) | 1.84 ± 0.62 | 1.95 ± 0.68 | 0.11 ± 0.14 | 0.072 |
| RER | 1.23 ± 0.08 | 1.27 ± 0.10 | 0.01 ± 0.06 | 0.33 |
| Peak workload (W) | 137 ± 55 | 160 ± 56 | 26 ± 13 | 0.008 |
Values are mean ± SD. DBP, diastolic blood pressure; HR, heart rate; RER, respiratory exchange ratio; SBP, systolic blood pressure.
Discussion
This study emphasises the presence of reduced exercise capacity in some patients with long‐COVID symptoms, with the group having a lower exercise tolerance than people from the same community, studied before the COVID‐19 pandemic. The results show that depression may be associated with persistent post‐COVID‐19 symptoms and reduced functional capacity.
Functional reserve in long COVID
The objective definition of impaired functional reserve can be challenging as it requires expensive equipment and specialist expertise to perform the testing. CPET is the reference standard for this purpose, but this is difficult to access in the community. In a meta‐analysis of nine published studies that allowed comparison of expired gas analysis (823 people, of whom 464 had symptoms of PASC), 30 Durstenfeld documented a reduction of peak VO2 of −4.9 (95% CI: −6.4 to −3.4) mL/kg/min among those with symptoms. The common causes of the reduced peak VO2 were deconditioning, abnormal oxygen extraction, dysfunctional breathing and chronotropic incompetence. In a prospective, multicentre cohort study of 180 previously hospitalised COVID‐19 patients who underwent CPET at 3 and 12 months after discharge, there was a significant (5%) increase in per cent peak VO2 between visits, to the extent that exercise capacity was normal in 77% at 12 months. 31
In this study, DASI 22 was used as the primary screening test for impaired functional capacity. Although this score is based on the patients' subjective assessment of their functional capacity, it was previously shown to correlate well with measured peak VO2. Despite the younger age of the post‐COVID‐19 population than the control group, the former had a significantly lower functional capacity than the controls, even when matched for their risk factor status. The 6MWD is an alternative approach to measuring exercise capacity in the community, 21 without the need for exercise equipment. Possibly because of a ceiling effect in younger individuals, 6MWD showed some discrepancy with DASI‐based assessment of functional capacity (and VO2) and was not associated with the expected long‐COVID symptoms. 32 These findings suggest that screening patients with DASI may be sufficient to select those who would be most likely to have abnormal findings at formal exercise testing.
Limitations
The experience of COVID‐19 has been different in Australia than elsewhere in the world (mainly Omicron infections in a mainly vaccinated population), so it is possible that these findings may not be valid in another environment. A historical control cohort was selected in order to ensure that control patients were unexposed to COVID‐19, but there were differences between the current and control groups. Although the propensity matching could remove most of the potential confounding related to differences in age, sex and cardiovascular risk factors between the two cohorts, the historical controls did not experience the intense lockdowns experienced during the study period. This residual difference between the two groups might have impacted our findings. However, findings from this study show significant differences in functional capacity and mental health between the COVID‐19 participants and their controls and more severe functional impairment and depression among COVID‐19 survivors with long COVID compared with COVID‐19 survivors without long COVID. These findings suggest that functional impairment and depression observed in our study were likely a consequence of COVID‐19 and long COVID rather than the lockdown effects. The performance of exercise training in only seven participants was obtained to understand the feasibility, and we would not use this to provide a recommendation for this intervention in people with long COVID. We are currently performing a randomised controlled trial to determine the benefits of exercise training in people with long COVID.
Conclusion
The results of this study show impairment of both objective and subjective functional capacity in a proportion of people infected with COVID‐19 which appeared to be exacerbated in those with long COVID, suggesting that physical deconditioning – presumably because of weeks or months of inactivity – may be causative in some. The high prevalence of depression that was associated with COVID‐19 and long COVID was a concern that might need public health intervention. Future longitudinal studies are required to determine the causal relationship between long COVID and these adverse outcomes.
Clinical implications
The standard approach to long‐COVID symptoms has been the provision of supportive care. 8 , 33 Although limited preliminary data support the notion that exercise training may improve functional capacity 34 and reduce symptoms, there is no consensus as to the benefits of this in this setting. 35 Caution needs to be applied to patient selection, as there is an overlap between long COVID and chronic fatigue syndrome, 36 and exercise may be detrimental in the latter. 37 Nonetheless, a randomised trial to test the efficacy of exercise in appropriately selected patients seems warranted.
Supporting information
Data S1. Supplementary tables.
Acknowledgements
This study was supported in part by the National Heart Foundation, Canberra (105282), and the National Health and Medical Research Council, Canberra (2005874), Australia. Open access publishing facilitated by The University of Melbourne, as part of the Wiley ‐ The University of Melbourne agreement via the Council of Australian University Librarians.
Conflict of interest: None.
References
- 1. WHO Coronavirus (COVID‐19) Dashboard. Available from URL: https://covid19.who.int
- 2. Al‐Aly Z, Xie Y, Bowe B. High‐dimensional characterization of post‐acute sequelae of COVID‐19. Nature 2021; 594: 259–264. [DOI] [PubMed] [Google Scholar]
- 3. Ayoubkhani D, Khunti K, Nafilyan V, Maddox T, Humberstone B, Diamond I et al. Post‐covid syndrome in individuals admitted to hospital with covid‐19: retrospective cohort study. BMJ 2021; 372: n693. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Nasserie T, Hittle M, Goodman SN. Assessment of the frequency and variety of persistent symptoms among patients with COVID‐19: a systematic review. JAMA Netw Open 2021; 4: e2111417. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Evans RA, McAuley H, Harrison EM, Shikotra A, Singapuri A, Sereno M et al. Physical, cognitive, and mental health impacts of COVID‐19 after hospitalisation (PHOSP‐COVID): a UK multicentre, prospective cohort study. Lancet Respir Med 2021; 9: 1275–1287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Brannock MD, Chew RF, Preiss AJ, Hadley EC, McMurry JA, Leese PJ et al. Long COVID risk and pre‐COVID vaccination: an EHR‐based cohort study from the RECOVER program. medRxiv 2022. doi: 10.1101/2022.10.06.22280795 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Notarte KI, Catahay JA, Velasco JV, Pastrana A, Ver AT, Pangilinan FC et al. Impact of COVID‐19 vaccination on the risk of developing long‐COVID and on existing long‐COVID symptoms: a systematic review. EClinicalMedicine 2022; 53: 101624. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Shah W, Hillman T, Playford ED, Hishmeh L. Managing the long term effects of covid‐19: summary of NICE, SIGN, and RCGP rapid guideline. BMJ 2021; 372: n136. [DOI] [PubMed] [Google Scholar]
- 9. DePace NL, Colombo J. Long‐COVID syndrome and the cardiovascular system: a review of neurocardiologic effects on multiple systems. Curr Cardiol Rep 2022; 24: 1711–1726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Ahamed J, Laurence J. Long COVID endotheliopathy: hypothesized mechanisms and potential therapeutic approaches. J Clin Invest 2022; 132: e161167. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Battistella LR, Imamura M, De Pretto LR, Van Cauwenbergh S, Delgado Ramos V, Saemy Tome Uchiyama S et al. Long‐term functioning status of COVID‐19 survivors: a prospective observational evaluation of a cohort of patients surviving hospitalisation. BMJ Open 2022; 12: e057246. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Carfì A, Bernabei R, Landi F. Persistent symptoms in patients after acute COVID‐19. JAMA 2020; 324: 603–605. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Sandoval Y, Januzzi JL Jr, Jaffe AS. Cardiac troponin for assessment of myocardial injury in COVID‐19: JACC review topic of the week. J Am Coll Cardiol 2020; 76: 1244–1258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Puntmann VO, Carerj ML, Wieters I, Fahim M, Arendt C, Hoffmann J et al. Outcomes of cardiovascular magnetic resonance imaging in patients recently recovered from coronavirus disease 2019 (COVID‐19). JAMA Cardiol 2020; 5: 1265. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. NSW Health . Long COVID. Available from URL: https://www.nsw.gov.au/covid-19/testing-managing/long-covid
- 16. Yang H, Negishi K, Wang Y, Nolan M, Marwick TH. Imaging‐guided cardioprotective treatment in a community elderly population of stage B heart failure. JACC Cardiovasc Imaging 2017; 10: 217–226. [DOI] [PubMed] [Google Scholar]
- 17. Potter E, Stephenson G, Harris J, Wright L, Marwick TH. Screening‐guided spironolactone treatment of subclinical left ventricular dysfunction for heart failure prevention in at‐risk patients. Eur J Heart Fail 2022; 24: 620–630. [DOI] [PubMed] [Google Scholar]
- 18. Jarrom D, Elston L, Washington J, Prettyjohns M, Cann K, Myles S et al. Effectiveness of tests to detect the presence of SARS‐CoV‐2 virus, and antibodies to SARS‐CoV‐2, to inform COVID‐19 diagnosis: a rapid systematic review. BMJ Evid Based Med 2022; 27: 33–45. [DOI] [PubMed] [Google Scholar]
- 19. Kroenke K, Spitzer RL, Williams JB. The PHQ‐9: validity of a brief depression severity measure. J Gen Intern Med 2001; 16: 606–613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Richardson J, Iezzi A, Khan MA, Maxwell A. Validity and reliability of the Assessment of Quality of Life (AQoL)‐8D multi‐attribute utility instrument. Patient 2014; 7: 85–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories . ATS statement: guidelines for the six‐minute walk test. Am J Respir Crit Care Med 2002; 166: 111–117. [DOI] [PubMed] [Google Scholar]
- 22. Hlatky MA, Boineau RE, Higginbotham MB, Lee KL, Mark DB, Califf RM et al. A brief self‐administered questionnaire to determine functional capacity (The Duke Activity Status Index). Am J Cardiol 1989; 64: 651–654. [DOI] [PubMed] [Google Scholar]
- 23. Bittner V, Weiner DH, Yusuf S, Rogers WJ, McIntyre KM, Bangdiwala SI et al. Prediction of mortality and morbidity with a 6‐minute walk test in patients with left ventricular dysfunction. SOLVD Investigators. JAMA 1993; 270: 1702–1707. [PubMed] [Google Scholar]
- 24. Shaw LJ, Olson MB, Kip K, Kelsey SF, Johnson BD, Mark DB et al. The value of estimated functional capacity in estimating outcome: results from the NHBLI‐Sponsored Women's Ischemia Syndrome Evaluation (WISE) Study. J Am Coll Cardiol 2006; 47: S36–S43. [DOI] [PubMed] [Google Scholar]
- 25. Gulati M, Black HR, Shaw LJ, Arnsdorf MF, Merz CN, Lauer MS et al. The prognostic value of a nomogram for exercise capacity in women. N Engl J Med 2005; 353: 468–475. [DOI] [PubMed] [Google Scholar]
- 26. Casanova C, Celli BR, Barria P, Casas A, Cote C, de Torres JP et al. The 6‐min walk distance in healthy subjects: reference standards from seven countries. Eur Respir J 2011; 37: 150–156. [DOI] [PubMed] [Google Scholar]
- 27. Dillon HT, Saner NJ, Ilsley T, Kliman D, Spencer A, Avery S et al. Preventing the adverse cardiovascular consequences of allogeneic stem cell transplantation with a multi‐faceted exercise intervention: the ALLO‐Active trial protocol. BMC Cancer 2022; 22: 898. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Belli S, Balbi B, Prince I, Cattaneo D, Masocco F, Zaccaria S et al. Low physical functioning and impaired performance of activities of daily life in COVID‐19 patients who survived hospitalisation. Eur Respir J 2020; 56: 2002096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Leuven E, Sianesi B. PSMATCH2: Stata Module to Perform Full Mahalanobis and Propensity Score Matching, Common Support Graphing, and Covariate Imbalance Testing. Statistical Software Components S432001, Boston College Department of Economics, revised 01 Feb 2018; 2003.
- 30. Durstenfeld MS, Sun K, Tahir P, Peluso MJ, Deeks SG, Aras MA et al. Use of cardiopulmonary exercise testing to evaluate long COVID‐19 symptoms in adults: a systematic review and meta‐analysis. JAMA Netw Open 2022; 5: e2236057. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Ingul CB, Edvardsen A, Follestad T, Trebinjac D, Ankerstjerne OAW, Bronstad E et al. Changes in cardiopulmonary exercise capacity and limitations 3‐12 months after COVID‐19. Eur Respir J 2023; 61: 2200745. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Frost AE, Langleben D, Oudiz R, Hill N, Horn E, McLaughlin V et al. The 6‐min walk test (6MW) as an efficacy endpoint in pulmonary arterial hypertension clinical trials: demonstration of a ceiling effect. Vascul Pharmacol 2005; 43: 36–39. [DOI] [PubMed] [Google Scholar]
- 33. Nalbandian A, Sehgal K, Gupta A, Madhavan MV, McGroder C, Stevens JS et al. Post‐acute COVID‐19 syndrome. Nat Med 2021; 27: 601–615. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Rudofker EW, Parker H, Cornwell WK 3rd. An exercise prescription as a novel management strategy for treatment of Long COVID. JACC Case Rep 2022; 4: 1344–1347. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Wright J, Astill SL, Sivan M. The relationship between physical activity and Long COVID: a cross‐sectional study. Int J Environ Res Public Health 2022; 19: 5093. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Davis HE, McCorkell L, Vogel JM, Topol EJ. Long COVID: major findings, mechanisms and recommendations. Nat Rev Microbiol 2023; 21: 133–146. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Myalgic Encephalomyelitis (or Encephalopathy)/Chronic Fatigue Syndrome: Diagnosis and Management. NICE Guideline [NG206]. 2021; 2023.
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1. Supplementary tables.
