Abstract
Objectives
This study aimed to evaluate the recovery of functional fitness, lung function, and immune function in healthcare workers (HCWs) with nonsevere and severe COVID-19 at 13 months after discharge from the hospital.
Methods
The participants of “Rehabilitation Care Project for Medical Staff Infected with COVID-19” underwent a functional fitness test (muscle strength, flexibility, and agility/dynamic balance), lung function test, and immune function test (including cytokines and lymphocyte subsets) at 13 months after discharge.
Results
The project included 779 HCWs (316 nonsevere COVID-19 and 463 severe COVID-19). This study found that 29.1% (130/446) of the HCWs have not yet recovered their functional fitness. The most affected lung function indicator was lung perfusion capacity (34% with diffusion capacity for carbon monoxide-single breath <80%). The increase of interleukin-6 (64/534, 12.0%) and natural killer cells (44/534, 8.2%) and the decrease of CD3+ T cells (58/534, 10.9%) and CD4+ T cells (26/534, 4.9%) still existed at 13 months after discharge. No significant difference was found in the HCWs with nonsevere and severe COVID-19 regarding recovery of functional fitness, lung function, and immune function at 13 months after discharge.
Conclusion
The majority of Chinese HCWs with COVID-19 had recovered their functional fitness, lung function, and immune function, and the recovery status in HCWs with severe COVID-19 is no worse than that in HCWs with nonsevere COVID-19 at 13 months after discharge from the hospital.
Keywords: Novel coronavirus, COVID-19, Functional fitness, Cytokine, Lymphocyte subsets
Introduction
COVID-19 refers to an acute respiratory infectious disease caused by SARS-CoV-2, which can cause a series of clinical symptoms, such as fever, fatigue, dry cough, dyspnea, shortness of breath, shock, and multiorgan dysfunction. As of June 17, 2022, the World Health Organization reports 535,863,950 confirmed cases of COVID-19 and 6,314,972 deaths (WHO, 2022). Between December 2019 and February 2020, 3019 healthcare workers (HCWs) (1716 confirmed cases) in China were found to be affected by SARS-CoV-2 (Epidemiology Working Group for NCIP Epidemic Response and Chinese Center for Disease Control and Prevention, 2020). Wuhan (17.7%) and Hubei Province (10.4%), where the patients were first diagnosed, had the highest proportion of patients with severe COVID-19 in the whole country (Epidemiology Working Group for NCIP Epidemic Response and Chinese Center for Disease Control and Prevention, 2020).
At present, few studies focused on the health consequences, including symptoms (Havervall et al., 2021), SARS-CoV-2 seroprevalence (Moncunill et al., 2021), and antibodies (Egbert et al., 2021) in HCWs with COVID-19 after they were discharged from the hospital. A study in China followed up HCWs with COVID-19 for 3 months after discharge; it suggested that 69 (91%) of the HCWs with COVID-19 had returned to their original work, 82% of the HCWs’ lung high-resolution computed tomography returned to normal, and 42% of the HCWs had mild pulmonary function abnormalities (Liang et al., 2020). Our previous study reported dynamic changes in functional fitness and immunologic indicators within 1 year after discharge in HCWs with severe COVID-19 (Xiong et al., 2021). There were also other studies revealing recovery of functional fitness (Paz et al., 2021), lung function (Huang et al., 2021), and immune function (Qin et al., 2020; Wan et al., 2020) in patients with COVID-19. However, most of these studies were not carried out on HCWs with COVID-19, and few of them had compared the recovery status in patients with nonsevere and severe COVID-19 after discharge. In the fight against COVID-19, HCWs with COVID-19 had made huge sacrifices. It is of great public health significance to pay attention to their health status after discharge from the hospital and implement individualized interventions to help the recovery of the target population. So far, the health consequences of HCWs with COVID-19 at 13 months after discharge from the hospital remain unclear.
Therefore, this study aimed to evaluate the recovery of functional fitness, lung function, and immune function in HCWs with COVID-19 at 13 months after hospital discharge and compare the recovery status of nonsevere and severe groups.
Methods
Study design and participants
The participants were from the “Rehabilitation Care Project for Medical Staff Infected with COVID-19” in China, which the Chinese Academy of Engineering and Tencent Charity Foundation launched (Xiong et al., 2021). The participants were HCWs with COVID-19 in Hubei Province (including the provincial capital city, Wuhan, and its surrounding cities). The HCWs with COVID-19 agreed to participate in the project through the information platform of “Rehabilitation Care Project for Medical Staff Infected with COVID-19” and were followed up on the health consequences after discharge from the hospital. The health consequences that the project mainly focused on included psychologic evaluation, a survey of persistent symptoms, lung function evaluation, and physical examinations. From June 2020 to March 2021, the project included a total of 779 HCWs (316 nonsevere and 463 severe COVID-19). All HCWs were contacted through the platform and/or by telephone to participate in follow-up visits (5, 8, 11, and 13 months after discharge) in Union Hospital (Tongji Medical College, Huazhong University of Science and Technology). Currently, the longest follow-up period for the HCWs is 13 months after discharge.
Regarding follow-up visits at 13 months after discharge, all HCWs participating in this project were asked to take physical examinations (any time between March 11, 2021 and March 19, 2021) and complete the functional fitness, lung function, and immune function tests at Union Hospital (Tongji Medical College, Huazhong University of Science and Technology). For HCWs with abnormal results of physical examinations, experts will be arranged to develop personalized rehabilitation plans to speed recovery.
In this study, HCWs of “Rehabilitation Care Project for Medical Staff Infected with COVID-19” who completed any follow-up visits (including functional fitness test, lung function test, and immune function test) between March 11, 2021, and March 19, 2021, were included in the analyses.
The disease severity and the standards of discharge were evaluated according to the recommendations by the National Health Commission (China National Health Commission, 2020). The severity of the disease was divided into four types, including mild (with mild clinical symptoms but without pneumonia manifestations in imaging examination), moderate (with fever, respiratory symptoms, etc., and with pneumonia manifestations in imaging examination), severe (meeting at least one of the following criteria: shortness of breath, RR ≥30 beats/min; the oxygen saturation ≤93%; PaO2/FiO2 ≤300 mmHg in the resting state), and critical (meeting at least one of the following criteria: respiratory failure requiring mechanical ventilation, shock, combined with other organ failure requiring intensive care unit [ICU] monitoring and treatment). In this study, the HCWs with severe or critical COVID-19 were assigned to the severe group, and the HCWs with mild or moderate COVID-19 were assigned to the nonsevere group. The standards of discharge included (i) no fever for three consecutive days, (ii) improved respiratory symptoms, (iii) obvious resolution and recovery of an acute lesion in lung computed tomography scanning, and (iv) two negative results of SARS-CoV-2 tests 24 hours apart.
According to the principles of the Declaration of Helsinki, this research was approved by the ethics committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. All HCWs signed written informed consents at enrollment.
Data collection
Information on demographic and clinical characteristics of the participants was obtained at enrollment through the information platform of “Rehabilitation Care Project for Medical Staff Infected with COVID-19”.
The functional fitness test was performed by doctors in the Department of Rehabilitation of Union Hospital (Tongji Medical College, Huazhong University of Science and Technology). The Senior Fitness Test (SFT) could comprehensively reflect the physical recovery status of the participants in the aspects of muscle strength, flexibility, and agility/dynamic balance. Previous literature showed that SFT could also be applied to other age groups beyond the elderly (Boshnjaku et al., 2021); therefore, this study used SFT to assess the functional fitness status. In this study, the SFT included evaluation of muscle strength (grip strength test, 30-second elbow flexion test, 30-second chair stand, and 2-minute step test), flexibility (back scratch test and chair sit-and-reach test), and agility/dynamic balance (functional reach test and the Y balance test) (Rikli and Jones, 1999). According to literature and policy documents, there are normal ranges for evaluation of muscle strength and agility/dynamic balance (Nogueira et al., 2021; State Sport General Administration, 2003). Therefore, if a HCW's score in any muscle strength and agility/dynamic balance test is out of the normal ranges, it was recorded that they had not recovered their functional fitness by the doctors.
The lung function test was performed by doctors at the NHC Key Laboratory of Pulmonary Diseases of Union Hospital (Tongji Medical College, Huazhong University of Science and Technology). The tests were performed with the Masterscreen pneumotachograph system (CareFusion, Hoechberg, Germany), and the diagnoses were based on the recommendations by the American Thoracic Society (Graham et al., 2019).
The immunologic indicators of the HCWs were measured at the Department of Clinical Laboratory of Union Hospital (Tongji Medical College, Huazhong University of Science and Technology). The levels of cytokine profile, including interferon-γ, interleukin (IL)-10, IL-2, IL-4, IL-6, and tumor necrosis factor-α were quantified by BD cytometric bead array analysis, using the BD™ Cytometric Bead Array Human Th1/Th2 cytokine kit. The relative numbers of lymphocyte subsets, including B cells, CD3+ T cells, CD4+ T cells, CD8+ T cells, natural killer (NK) cells and CD4+/CD8+ cell ratio were detected with flow cytometry (BD FACSCanto™, BD Biosciences), and data of lymphocyte subsets were analyzed with FCAP software (version 3.0).
Statistical analysis
Median and interquartile range and number (%) were used to describe continuous and categoric covariates, respectively. The Mann-Whitney U test, Wilcoxon signed-rank test, t-test, χ2, and Fisher's exact test were applied where appropriate. Multivariate linear regression models were used to analyze disease severity associations with functional fitness. Multivariable adjusted logistic regression models were applied to investigate disease severity and lung function relationships. The covariates of age, sex, education, roles in work, body mass index (BMI), smoking habit, and comorbidities were adjusted in the models. The analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA). A two-sided P-value lower than 0.05 was considered statistically significant.
Results
Characteristics of the HCWs
From June 2020 to March 2021, the cohort recruited a total of 779 HCWs in Hubei Province. All the follow-up visits were completed between March 11, 2021, and March 19, 2021. The median number of hospital discharge days was 387.4 (376.3, 396.3) (approximately 13 months). Among the 779 HCWs, 222 HCWs missed follow-up visits at 13 months after discharge. Among the remaining 557 HCWs, 111 HCWs declined functional fitness test, 254 HCWs declined lung function test, and 23 HCWs declined immune function test. The final sample sizes of participants who underwent functional fitness, lung function, and immune function tests (including cytokines and lymphocyte subsets) were 446, 303, and 534, respectively (Figure 1 ).
Figure 1.
Flow chart of this study.
HCWs: healthcare workers
The demographic and clinical characteristics of 779 HCWs according to disease severity are presented in Table 1 . The HCWs’ median age was 35.0 (30.0-43.0) years, median BMI was 22.8 (20.8-25.2) kg/m2; 77% of the HCWs were female (601/779), and 59% (445/755) of the HCWs were nurses. The HCWs with severe COVID-19 were older, had higher BMI, lower education status, less likely to be nurses, more likely to have respiratory support, a history of ICU admission, comorbidities, and symptoms at admission than HCWs with nonsevere COVID-19.
Table 1.
Characteristics of HCWs according to disease severity of COVID-19.
| Characteristics | All (N = 779) | nonsevere (N = 316) | Severe (N = 463) | P |
|---|---|---|---|---|
| Demographic characteristics | ||||
| Age (years) | 35.0 (30.0-43.0) | 34.0 (28.0-40.0) | 36.0 (31.0-45.0) | <0.001 |
| BMI (kg/m2) | 22.8 (20.8-25.2) | 22.0 (20.0-23.8) | 23.4 (21.2-25.7) | <0.001 |
| Sex (female) | 601 (77%) | 249 (79%) | 352 (76%) | 0.386 |
| Education (college and higher) | 586/732 (80%) | 234/288 (81%) | 352/444 (79%) | 0.019 |
| Location of the hospital work for | 0.378 | |||
| Hankou, Wuhan | 452 (58%) | 188 (59%) | 264 (57%) | |
| Wuchang, Wuhan | 196 (25%) | 79 (25%) | 117 (25%) | |
| Hanyang, Wuhan | 40 (5%) | 11 (4%) | 29 (6%) | |
| Outside Wuhan in Hubei | 91 (12%) | 38 (12%) | 53 (12%) | |
| Roles in work | 0.003 | |||
| Doctors | 184/755 (24%) | 72/298 (24%) | 112/457 (24%) | |
| Nurses | 445/755 (59%) | 182/298 (61%) | 263/457 (58%) | |
| Other | 126/755 (17%) | 44/298 (15%) | 82/457 (18%) | |
| Smoking habit (yes) | 24/756 (3%) | 9/300 (3%) | 15/456 (3%) | 0.016 |
| Time from discharge to follow-up (days)* | 387.4 (379.3-393.4) | 386.4 (382.3-396.1) | 387.4 (379.1-393.3) | 0.271 |
| Clinical characteristics | ||||
| The highest respiratory support in hospital | <0.001 | |||
| No supplemental oxygen | 278/740 (38%) | 159/295 (54%) | 119/445 (27%) | |
| Supplemental oxygen by nasal cannula or mask | 443/743 (60%) | 136/295 (46) | 307/445 (69%) | |
| Noninvasive or invasive mechanical ventilation | 19/740 (2%) | 0(0%) | 19/445 (4%) | |
| ICU admission (yes) | 20/753 (3%) | 1/299 (0.3%) | 19/454 (4%) | <0.001 |
| Comorbidities (yes) | 167/747 (22%) | 28/298 (9%) | 139/449 (31%) | <0.001 |
| Symptoms at admission | ||||
| Fatigue | 412 (53%) | 127 (60%) | 285 (62%) | <0.001 |
| Fever | 404 (52%) | 119 (38%) | 285 (62%) | <0.001 |
| Muscle soreness | 252 (32%) | 58 (18%) | 194 (42%) | <0.001 |
| Dry cough | 238 (31%) | 79 (25%) | 159 (34%) | 0.006 |
| Cough | 232 (30%) | 72 (23%) | 160 (35%) | <0.001 |
| Chest distress | 212 (27%) | 49 (16%) | 163 (35%) | <0.001 |
| Diarrhea | 175 (23%) | 56 (18%) | 119 (26%) | 0.009 |
| Shortness of breath | 169 (22%) | 29 (9%) | 140 (30%) | <0.001 |
| Headache | 147 (19%) | 33 (10%) | 114 (24%) | <0.001 |
| Dyspnea | 99 (13%) | 7 (2%) | 92 (20%) | <0.001 |
| Vomiting | 43 (6%) | 8 (3%) | 35 (8%) | 0.002 |
Data are presented as n (%), n/N (%), or median (IQR).
Abbreviations: BMI, body mass index; HCWs, healthcare workers; ICU, intensive care unit; IQR, interquartile range
The sample sizes for a group of “all,” “nonsevere,” and “severe” were 557, 205, and 352.
Functional fitness in HCWs with nonsevere and severe COVID-19
In this study, 446 HCWs (162 nonsevere and 284 severe COVID-19) took part in the functional fitness test; it found that 29.1% (130/446) of the HCWs have not yet recovered their functional fitness. There was no significant variance in the proportion of unrecovered HCWs between the nonsevere (30.2%, 49/162) and severe groups (28.5%, 81/284). The results of functional fitness test in HCWs according to disease severity are presented in Table 2 . In the three aspects of functional fitness recovery (muscle strength, flexibility, and agility/dynamic balance), no significant difference was found in the nonsevere and severe groups (all P-values >0.05). The characteristics of the HCWs included and excluded from the analyses of functional fitness were similar (Table S1).
Table 2.
Functional fitness in HCWs with nonsevere and severe COVID-19.
| Categories | All (N = 446) | Median (IQR) | β (95% CI) | |||
|---|---|---|---|---|---|---|
| Nonsevere (N = 162) | Severe (N = 189) | Nonsevere (N = 114) | Severe (N = 189) | P | ||
| Muscle strength test | ||||||
| Grip strength test, N | 25.5 (21.2, 30.5) | 25.9 (21.4, 29.9) | 25.3 (21.3, 30.7) | 0 | 0.21 (-0.98, 1.41) | 0.726 |
| 30-second elbow flexion test, n | 19.0 (15.0, 20.5) | 18.0 (15.0, 24.0) | 19.0 (15.0, 23.0) | 0 | 0.21 (-0.83, 1.24) | 0.693 |
| 30-second chair stand, n | 17.0 (15.0, 20.5) | 18.0 (15.0, 21.0) | 17.0 (15.0, 20.0) | 0 | -0.50 (-1.50, 0.50) | 0.328 |
| 2-minute step test, n | 93.0 (80.0, 107.0) | 95.0 (83.0, 108.0) | 92.0 (79.0, 107.0) | 0 | -1.62 (-5.60, 2.36) | 0.423 |
| Flexibility test | ||||||
| Back scratch test (left) | -1.0 (-8.0, 3.0) | 0.0 (-5.9, 3.4) | -2.8 (-10.1, 2.6) | 0 | -0.76 (-2.51, 0.99) | 0.392 |
| Back scratch test (right) | 2.0 (-2.1, 5.0) | 2.5 (0.0, 5.2) | 1.7 (-4.3, 4.4) | 0 | -1.01 (-2.39, 0.36) | 0.147 |
| Chair sit-and-reach test, cm | 1.5 (-2.0, 6.5) | 2.3 (0.0, 7.0) | 1.0 (-3.5, 6.5) | 0 | 0.05 (-2.38, 2.48) | 0.969 |
| Agility/dynamic balance | ||||||
| Functional reach test, cm | 27.0 (22.2, 31.0) | 27.0 (22.0, 30.0) | 27.0 (23.0, 31.0) | 0 | 0.51 (-0.97, 1.99) | 0.500 |
| YBT | ||||||
| Anterior-La | 73.1 (69.0, 80.0) | 73.0 (69.4, 79.0) | 73.5 (68.0, 80.0) | 0 | 0.56 (-1.13, 2.26) | 0.512 |
| Posterolateral-L | 76.0 (70.2, 81.0) | 75.9 (71.0, 81.0) | 77.0 (70.0, 81.0) | 0 | 0.52 (-1.40, 2.45) | 0.595 |
| Posteromedial-L | 64.0 (54.9, 71.8) | 64.0 (56.0, 71.0) | 77.0 (70.0, 81.0) | 0 | 1.01 (-1.67, 3.71) | 0.460 |
| Anterior-Rb | 75.0 (69.5, 80.0) | 75.0 (70.5, 80.0) | 75.0 (69.0, 80.0) | 0 | -0.27 (-1.85, 1.31) | 0.731 |
| Posterolateral-R | 78.0 (71.5, 83.0) | 78.0 (73.0, 83.0) | 78.0 (71.0, 84.0) | 0 | 0.00 (-1.87, 1.87 | 0.999 |
| Posteromedial-R | 62.0 (54.0, 70.0) | 61.0 (54.0, 81.0) | 63.0 (54.0, 71.0) | 0 | 1.29 (-1.42, 3.99) | 0.351 |
| Leg length | 79.0 (76.8, 81.5) | 79.0 (76.8, 81.0) | 79.0 (76.8, 81.6) | 0 | 0.25 (-0.28, 0.77) | 0.358 |
| Composite score-L | 211.8 (196.6, 227.0) | 211.0 (197.9, 228.4) | 212.0 (196.5, 227.9) | 0 | 2.10 (-2.80, 7.00) | 0.400 |
| Composite score-R | 214.0 (197.0, 229.6) | 214.0 (197.9, 228.4) | 214.0 (196.0, 230.0) | 0 | 1.01 (-4.01, 6.03) | 0.692 |
| Ratio of composite score to leg length-L | 0.9 (0.8, 0.9) | 0.9 (0.8, 0.9) | 0.9 (0.8, 0.9) | 0 | 0.01 (-0.01, 0.02) | 0.533 |
| Ratio of composite score to leg length-R | 0.9 (0.8, 1.0) | 0.9 (0.8, 1.0) | 0.9 (0.8, 1.0) | 0 | 0.00 (-0.02, 0.02) | 0.931 |
Abbreviations: HCWs, healthcare workers; IQR, interquartile range
L-reach distance by left leg. bR-reach distance by right leg.
The models adjusted for age, sex, education, roles in work, body mass index (BMI), smoking habit, and comorbidities.
Lung function in HCWs with nonsevere and severe COVID-19
A total of 303 HCWs (114 nonsevere and 189 severe COVID-19) underwent lung function tests at 13 months after discharge. The lung function indicators of the HCWs according to disease severity are demonstrated in Table 3 . This study found that the most affected indicator of lung function was lung perfusion capacity (34% with diffusion capacity for carbon monoxide [DLCO]-single breath [SB] <80%) in the HCWs. Obstruction (forced expiratory volume in one second/forced vital capacity <70%) was found in 8% and restriction (total lung capacity-SB <80%) in 6% of the HCWs. No significant variance in all indicators of lung function was found in HCWs of different disease severity (all P-values >0.05). The characteristics of the HCWs included and excluded from the analyses of lung function were similar (Table S1).
Table 3.
Lung function in HCWs with nonsevere and severe COVID-19.
| Categories | All (N = 303) | N (%) | β (95% CI) | |||
|---|---|---|---|---|---|---|
| Nonsevere (N = 114) | Severe (N = 189) | Nonsevere (N = 114) | Severe (N = 189) | P | ||
| FEV1 <80%, % of predicted | 24 (8%) | 13 (11%) | 11 (6%) | 1 | 0.51 (0.20, 1.31) | 0.160 |
| FVC <80%, % of predicted | 7 (2%) | 4 (4%) | 3 (2%) | 1 | 0.57 (0.08, 4.29) | 0.583 |
| FEV1/FVC <70% | 24 (8%) | 9 (8%) | 15 (8%) | 1 | 1.11 (0.43, 2.84) | 0.827 |
| RV <80%, % of predicted* | 43 (14%) | 17 (15%) | 26 (14%) | 1 | 0.75 (0.36, 1.57) | 0.449 |
| TLC <80%, % of predicted | 18 (6%) | 9 (8%) | 9 (5%) | 1 | 0.51 (0.17, 1.57) | 0.243 |
| FRC <80%, % of predicted | 57 (19%) | 17 (15%) | 40 (21%) | 1 | 1.52 (0.77, 3.00) | 0.223 |
| DLCO <80%, % of predicteda | 102 (34%) | 42 (37%) | 60 (32%) | 1 | 0.71 (0.41, 1.23) | 0.223 |
Data are presented as n (%).
Carbon monoxide diffusion capacity was not corrected for hemoglobin.
Abbreviations: DLCO, diffusion capacity for carbon monoxide; FEV1, forced expiratory volume in one second; FRC, functional residual capacity; FVC, forced vital capacity; HCWs, healthcare workers; RV, residual volume; TLC, total lung capacity.
The models adjusted for age, sex, education, roles in work, body mass index, smoking habit, and comorbidities.
Immune function in HCWs with nonsevere and severe COVID-19
In this study, 534 HCWs (198 nonsevere and 336 severe COVID-19) participated in the immune function test. No significant difference was found in the median values of cytokines (Table 4 ) and lymphocyte subsets (Table 5 ) between the nonsevere and the severe group. This study also analyzed the distribution of various cytokines and lymphocyte subsets. The results suggested that more than 95% of the study population had normal levels of interferon-γ, IL-10, IL-2, IL-4, and TNF-α, and 12.0% (64/534) of the HCWs had elevated levels of IL-6 at 13 months after discharge from the hospital (Table 4). More than 90% of the HCWs had normal relative numbers of lymphocyte subsets (B cells, CD3+ T cells, CD4+ T cells, CD4+/CD8+ cell ratio, CD8+ T cells, and NK cells) (Table 5). At 13 months after discharge from the hospital, the decrease of CD3+ T cells (58/534, 10.9%) and CD4+ T cells (26/534, 4.9%) and elevation of NK cells (44/534, 8.2%) still existed.
Table 4.
Levels of cytokines in HCWs with nonsevere and severe COVID-19.
| Categories | All (N = 534) | Nonsevere (N = 198) | Severe (N = 336) | P |
|---|---|---|---|---|
| IFN-γ (pg/ml) | 1.04 (0.96-1.16) | 1.04 (0.96-1.16) | 1.04 (0.96-1.16) | 0.881 |
| Elevated | 1 (0.2%) | 1 (0.5%) | 0 (0.0%) | 0.371 |
| Normala | 0.64-15.17 | 0.73-15.17 | 0.64-9.58 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| IL-10 (pg/ml) | 1.25 (1.09-1.45) | 1.25 (1.10-1.45) | 1.40 (1.05-1.45) | 0.952 |
| Elevated | 3 (0.6%) | 2 (1.0%) | 1 (0.3%) | 0.559 |
| Normala | 0.51-3.81 | 0.66-2.55 | 0.51-3.81 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| IL-2 (pg/ml) | 1.36 (1.23-1.52) | 1.36 (1.25-1.48) | 1.40 (1.23-1.52) | 0.271 |
| Elevated | 3 (0.6%) | 2 (1.0%) | 1 (0.3%) | 0.558 |
| Normala | 0.87-4.07 | 0.87-4.07 | 0.91-4.07 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| IL-4 (pg/ml) | 1.50 (1.39-1.61) | 1.46 (1.35-1.61) | 1.50 (1.39-1.60) | 0.598 |
| Elevated | 1 (0.2%) | 1 (0.5%) | 0 (0.0%) | 0.371 |
| Normala | 1.02-2.60 | 1.02-2.48 | 1.04-2.60 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| IL-6 (pg/ml) | 1.53 (1.20-2.55) | 1.51 (1.20-2.44) | 1.62 (1.14-2.74) | 0.589 |
| Elevated | 64 (12.0%) | 25 (12.6%) | 39 (11.6%) | 0.783 |
| Normala | 0.32-5.25 | 0.32-5.25 | 0.48-5.23 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | |
| TNF-α (pg/ml) | 2.58 (1.60-5.60) | 2.49 (1.60-6.45) | 2.58 (1.58-5.08) | 0.596 |
| Elevated | 8 (1.5%) | 3 (1.5%) | 5 (1.5%) | 0.980 |
| Normala | 0.56-21.20 | 0.56-21.20 | 0.92-20.38 | |
| Decreased | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) |
Data are presented as median (IQR).
Data are shown as the normal ranges of the indicators.
Abbreviations: HCWs, healthcare workers; IQR, interquartile range.
The comparison between two groups was performed with Mann-Whitney U test.
Table 5.
Levels of lymphocyte subsets in HCWs with nonsevere and severe COVID-19.
| Categories | All (N = 534) | Nonsevere (N = 198) | Severe (N = 336) | P |
|---|---|---|---|---|
| B cells (%) | 9.90 (7.79-12.30) | 9.90 (7.85-12.08) | 9.90 (7.72-12.42) | 0.963 |
| Elevated | 12 (2.2%) | 5 (2.5%) | 7(2.1%) | 0.918 |
| Normala | 4.29-18.31 | 4.29-17.60 | 4.30-18.31 | |
| Decreased | 15 (2.8%) | 6 (3.0%) | 9 (2.7%) | |
| CD3+ T cells (%) | 70.67 (64.37-75.92) | 71.17 (65.15-76.40) | 70.04 (63.92-75.55) | 0.254 |
| Elevated | 7 (1.3%) | 0 (0.0%) | 7(2.1%) | 0.068 |
| Normala | 58.21-83.83 | 58.34-82.80 | 58.21-83.83 | |
| Decreased | 58 (10.9%) | 18 (9.1%) | 40 (11.9%) | |
| CD4+ T cells (%) | 35.58 (31.01-40.36) | 36.40 (31.49-40.10) | 35.02 (30.54-40.85) | 0.280 |
| Elevated | 11 (2.0%) | 3 (1.5%) | 8 (2.4%) | 0.423 |
| Normala | 25.40-51.33 | 25.59-51.33 | 25.40-50.41 | |
| Decreased | 26 (4.9%) | 7 (3.5%) | 19 (5.7%) | |
| CD4+/CD8+ cell ratio | 1.42 (1.14-1.82) | 1.42 (1.18-1.77) | 1.42 (1.09-1.86) | 0.746 |
| Elevated | 22 (4.1%) | 8 (4.0%) | 14 (4.2%) | 0.427 |
| Normala | 0.46-2.72 | 0.61-2.72 | 0.46-2.72 | |
| Decreased | 1 (0.2%) | 1 (0.5%) | 0 (0.0%) | |
| CD8+ T cells (%) | 25.20 (20.76-29.98) | 25.17 (21.13-29.72) | 23.35 (20.63-30.39) | 0.820 |
| Elevated | 24 (4.5%) | 10 (5.1%) | 14 (4.1%) | 0.793 |
| Normal | 14.24-38.48 | 14.24-38.48 | 14.41-38.32 | |
| Decreased | 19 (3.6%) | 6 (3.0%) | 13 (3.9%) | |
| NK cells (%) | 16.89 (12.01-22.75) | 16.07 (11.98-23.09) | 17.42 (12.01-22.58) | 0.668 |
| Elevated | 44 (8.2%) | 15 (7.6%) | 29 (8.6%) | 0.852 |
| Normala | 3.51-30.44 | 4.58-29.66 | 3.51-30.44 | |
| Decreased | 2 (0.4%) | 1 (0.5%) | 1 (0.3%) |
Data are presented as median (IQR) or n (%).
Data are shown as the normal ranges of the indicators.
Abbreviations: HCWs, healthcare workers; IQR, interquartile range
The continuous covariate between two groups was compared with Mann-Whitney U test. The comparison of categoric covariates between two groups was evaluated using chi-square test and Fisher's exact test.
This study compared the levels and distributions of cytokines and lymphocyte subsets in HCWs with nonsevere and severe COVID-19 and found no statistically significant differences between the two groups (all P-values >0.05). This study also compared the levels of cytokines in 152 HCWs with severe COVID-19 at 11 months and 13 months after discharge. Results showed that levels of all cytokines except IL-2 were lower at 13 months after discharge than at 11 months. Levels of IL-2 were slightly elevated within normal ranges at 13 months after discharge compared with 11 months (Table S2). The characteristics of the HCWs included and excluded from the analyses of immune function were similar (Table S1).
Discussion
To the best of our knowledge, this is the first study that focuses on the health consequences of patients with COVID-19 with the longest follow-up time (13 months after discharge), and the study population consisted of HCWs. This study found that at 13 months after discharge from the hospital, there was no statistically significant difference between the HCWs in nonsevere and severe groups regarding recovery of functional fitness, lung function, and immune function. The results of this study found that at 13 months after discharge, a small proportion of HCWs had not recovered their functional fitness (about 30%), had poor lung perfusion (34%), increased IL-6 and NK cells, and decreased relative numbers of CD3+ T cells and CD4 + T cells. Interventions should be implemented timely to help speed recovery in these target populations in the future.
In this study, approximately 30% of the HCWs had not recovered their functional fitness at 13 months after discharge from the hospital. The results were consistent with the findings of an Italian study, which demonstrated that 32% of the patients were still showing impaired functional fitness up to approximately 3-6 months after infection with SARS-CoV-2 (Baricich et al., 2021). The decline in functional fitness was also found in patients with SARS approximately 1-2 years after discharge from the hospital (Rooney et al., 2020). Studies speculated that the causes of the decline in functional fitness might be related to the prolonged time of immobility (Herridge et al., 2016), the impairment in lung function (Mo et al., 2020), the presence of neurologic symptoms (e.g., as skeletal muscle injury) (Cagnazzo et al., 2021), and the inflammatory changes due to cardiac involvement (Rodriguez et al., 2020). To date, it is not clear how COVID-19 affects the functional fitness of the patients and for how long the impaired functional fitness will last. Therefore, research regarding mechanisms and a longer follow-up time should be carried out in the future. In addition, rehabilitation guidance should be provided to help their recovery.
Our study found that up to 34% of the HCWs with COVID-19 had diffusion impairment at 13 months after discharge. Similar to the previous findings, the lung is the organ most affected by infection of SARS-COV-2. Former studies also found abnormal lung function in patients with COVID-19 after discharge or symptom onset (Huang et al., 2021; Milanese et al., 2021; Shah et al., 2021). The study in Jin Yin-tan Hospital in China reported that approximately 22-56% of patients with various severity scales of COVID-19 had pulmonary diffusion abnormality (DLCO <80%, % of predicted) at 6 months after symptom onset (Huang et al., 2021). A study in Italy also found that 40% of the patients with COVID-19 had DLCO impairment at 6 months after hospital discharge (Milanese et al., 2021). Another prospective cohort in Canada suggested that more than 50% of the patients with COVID-19 had lung function impairment at 12 weeks after symptom onset (Shah et al., 2021). In published studies, patients with SARS (Xie et al., 2005) and H1N1 (Bai et al., 2011) were also found to have varying degrees of decline in lung diffusing capacity after discharge. The impairment would persist for months or years after discharge. Therefore, it is of significant importance to monitor lung function in patients with COVID-19 after discharge from the hospital for a longer period of time. In addition, effective intervention measures, such as cardiopulmonary exercise (Gao et al., 2021), should be practiced to help patients regain their regular lung function. Some studies speculate that the mechanisms of the decreased diffusing capacity caused by SARS-COV-2 may be related to angiotensin-converting enzyme 2, lung and multiorgan damage, and functional failure caused by cytokine storm (Iwasaki et al., 2021; Mustafa et al., 2020), and related mechanism research should also be further carried out.
Patients infected with the SARS-COV-2 (Qin et al., 2020; Wan et al., 2020), SARS-COV (Huang et al., 2005), H7N9 (Zhou et al., 2013), and H5N1 (Henter et al., 2006) were found to have increased levels of cytokines (especially IL-6), which indicated an uncontrolled systemic inflammatory reaction process and might lead to severe immune pathologic damage. Similar to the current study, a study in China demonstrated that 2 weeks after recovery, patients with COVID-19 had elevated levels of IL-6 (20.59%), IL-4 (19.12%), TNF-α (10.29%), IL-17 (2.94%), and IL-10 (1.47%); whereas levels of cytokine in healthy controls were all in normal ranges (Hasichaolu et al., 2020). Another study in China compared the levels of cytokines in hospitalized and discharged patients with noncritical COVID-19; it reported that the levels of IL-6, TNF-α, interferon-γ, IL-2, IL-4, and IL-10 were all upregulated in the hospitalized patients (Lin et al., 2020). Our previous research explored the cytokine levels in HCWs with severe COVID-19 before discharge, at 5 months, 8 months, and 11 months after discharge. The results suggested that the majority of the HCWs’ cytokine levels gradually returned to normal (showing a trend of decline) (Xiong et al., 2021). The cytokine levels still showed a trend of decline from 11 months to 13 months in HCWs with severe COVID-19. At 11 months after discharge, about one-third of HCWs with severe COVID-19 had elevated cytokine levels (Xiong et al., 2021). This study found that at 13 months after discharge, only 12% of the HCWs (including nonsevere and severe COVID-19) had increased cytokine levels (only IL-6 increased), indicating that the cytokines recovered well in the majority of the participants regardless of disease severity. This study found, for the first time, that the recovery of cytokine levels in HCWs with nonsevere and severe COVID-19 at 13 months after discharge from the hospital was similar, indicating that the immune function of HCWs with severe COVID-19 could also be recovered as well as those with nonsevere COVID-19. However, the specific mechanism is still unclear, and research should be carried out to explore the recovery process further.
This study found that at 13 months after discharge, the relative numbers of CD3+ T cells, CD4+ T cells, and CD8+ T cells decreased and NK cells increased in HCWs regardless of disease severity. This is similar to our previous results in follow-up visits within 1 year (Xiong et al., 2021). However, the lymphocyte subsets at 13 months after discharge recovered better than within 1 year in HCWs. In addition to our previous study, other research indicates that the immune system gradually recovered after COVID-19 infection. A study in China found decreased levels of CD8+ T cells, CD19+ B cells, total lymphocytes, CD3+ T cells, CD4+ T cells, and CD56+ NK cells in patients with COVID-19 2 weeks after recovery (Hasichaolu et al., 2020). Another study in China suggested that the levels of neutrophils, monocytes, NK cells, and CD4+ T cells increased. Levels of total lymphocytes and CD8+ T cells significantly decreased in discharged noncritical patients with COVID-19 than in those who were hospitalized (Lin et al., 2020). Published studies showed that levels of lymphocyte subsets were significantly decreased in patients with severe COVID-19 (Huang et al., 2020; Wang et al., 2020). Lymphocytes play key roles in viral clearance in patients with COVID-19. The observed decrease of lymphocyte subsets may destroy many immune cells, inhibiting the patients’ cellular immunity. The decreases in lymphocyte subsets after recovery were evidenced to be independent predictors of disease severity and rehabilitation efficacy (Akbari et al., 2020; Deng et al., 2020; Wan et al., 2020; Wang et al., 2020). Similar T cell depletion was also observed in SAR-CoV and MERS patients (Fung et al., 2020). However, the mechanisms remain unclear; although there were studies speculating that cytokine storm (Zhang et al., 2020), lung impairment, and virus (Merad and Martin, 2020) might be involved in the T cell depletion. Future mechanism studies are warranted. Studies with a longer follow-up time are also needed to investigate the impacts of COVID-19 on immune function.
This research has several limitations. First, this study evaluated the HCWs’ functional fitness recovery from three aspects: muscle strength, flexibility, and agility/dynamic balance. Follow-up studies should also use other evaluation methods, such as the 6-minute walking test, to evaluate the HCWs’ functional fitness recovery. Second, the HCWs did not have a lung function test before infection. Therefore, it was impossible to compare with the results after infection. The number of HCWs with chronic respiratory disease was limited. However, self-reported prevalence of chronic respiratory disease might lead to underestimation. This study speculates that the majority of the HCWs’ lung function at baseline is normal. The interpretation of current results remains valid. Third, this study did not analyze the associations between computed tomography findings and lung function parameters; future studies should focus on these aspects. Fourth, due to laboratory testing methods, only the relative numbers of lymphocyte subsets were available in this study. Follow-up studies should also focus on the differences in the absolute numbers of lymphocyte subsets. Fifth, this study lacked a control group and could not assess the health status of HCWs who were not infected with COVID-19. Future studies should be conducted to compare the health status of HCWs infected and uninfected with COVID-19. Lastly, this study found no statistically significant difference in some aspects of health recovery in HCWs with nonsevere and severe COVID-19. The response rate of follow-up visits may introduce biases to the study findings. However, the characteristics of the HCWs included and excluded from the study were similar. In addition, the low proportion of ICU admission (4%) in HCWs with severe COVID-19 and the high proportion (approximately 40%) of HCWs without supplemental oxygen may also limit generalizability of the study findings to other populations. Therefore, the results achieved in the current study need to be confirmed in larger cohort studies in the future.
At 13 months after discharge from the hospital, the health consequences of the majority of the HCWs with COVID-19 had returned to normal. The recovery of HCWs with severe COVID-19 is no worse than those with nonsevere COVID-19 in terms of functional fitness, lung function, and immune function. However, it is still necessary to implement timely interventions in helping HCWs to recover fully after discharge from the hospital.
Acknowledgments
Funding
The study was supported by the Rehabilitation Care Project for Medical Staff Infected with COVID-19 in China launched by the Chinese Academy of Engineering and Tencent Foundation. The study's funder had no role in the study design, data collection, analysis, interpretation, or report writing. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Declarations of competing interest
The authors have no competing interests to declare.
Ethical approval
According to the principles of the Declaration of Helsinki, this research was approved by the ethics committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. All HCWs signed written informed consents at enrollment.
Availability of data and materials
All data generated or analyzed during this study are included in this published article (and its supplementary information files). Because the cohort is still going on, we may not make the data available to others.
Author contributions
Hu Y, Xia J, Xiong LJ, Li Q, Cao XJ, Xiong HG, Huang M, and Yang FW designed this study. Hu Y, Xiong LJ, and Li Q were responsible for the integrity of the data and the accuracy of the data analysis. All authors had full access to all of the data in the study. Hu Y, Xia J, and Xiong LJ managed the project and provided guidance. Xiong LJ, Cao XJ, Xiong HG, Meng DQ, Zhou M, Zhang YZ, and Fan YZ collected the data. Xiong LJ, Li Q, Xiong HG, and Tang L analyzed the data. Xiong LJ and Li Q drafted the manuscript. All authors revised the manuscript and gave final approval for the version to be published.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ijid.2022.06.052.
Appendix. Supplementary materials
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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
All data generated or analyzed during this study are included in this published article (and its supplementary information files). Because the cohort is still going on, we may not make the data available to others.