Next Article in Journal
The Association between Vision Impairment and Depression: A Systematic Review of Population-Based Studies
Previous Article in Journal
A Disseminated Mycobacterium Abscessus Infection in a Patient Affected by Pulmonary Graft versus Host Disease: Case Report with a Revision of Literature
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 11
Issue 9
10.3390/jcm11092411
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Fatigue Is a Major Symptom at COVID-19 Hospitalization Follow-Up

by
Søren Sperling
1,2,*,
Andreas Fløe
1,
Steffen Leth
2,3,4,
Charlotte Hyldgaard
5,
Tina Gissel
6,
Ayfer Topcu
7,
Lars Kristensen
8,
Lene Dahl Sønderskov
9,
Johannes Martin Schmid
1,2,
Søren Jensen-Fangel
2,4 and
Elisabeth Bendstrup
1,2
1
Department of Respiratory Diseases and Allergy, Aarhus University Hospital, 8200 Aarhus, Denmark
2
Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
3
Department of Infectious Diseases, Regional Hospital West Jutland, 7400 Goedstrup, Denmark
4
Department of Infectious Diseases, Aarhus University Hospital, 8200 Aarhus, Denmark
5
Diagnostic Centre, Silkeborg Regional Hospital, 8600 Silkeborg, Denmark
6
Department of Respiratory Diseases, Viborg Regional Hospital, 8800 Viborg, Denmark
7
Department of Respiratory Diseases, Horsens Regional Hospital, 8700 Horsens, Denmark
8
Department of Respiratory Diseases, Regional Hospital West Jutland, 7400 Goedstrup, Denmark
9
Department of Respiratory Diseases, Randers Regional Hospital, 8900 Randers, Denmark
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2022, 11(9), 2411; https://doi.org/10.3390/jcm11092411
Submission received: 21 March 2022 / Revised: 23 April 2022 / Accepted: 24 April 2022 / Published: 25 April 2022
(This article belongs to the Topic Fighting against COVID-19: Latest Advances, Challenges and Methodologies)
Browse Figures
Review Reports Versions Notes

Abstract

:
Persistent symptoms after hospitalization with COVID-19 are common, but the frequency and severity of these symptoms are insufficiently understood. We aimed to describe symptoms and pulmonary function after hospitalization with COVID-19. Patients hospitalized with COVID-19 in Central Denmark Region were invited for follow-up 3 months after discharge. Clinical characteristics, patient reported outcomes (Fatigue Assessment Scale (FAS), anxiety and depression (HADS)), symptoms, pulmonary function test and 6-min walk test were collected. We included 218 patients (mean age 59.9 (95% CI: 58.2, 61.7), 59% males). Fatigue, dyspnea and impaired concentration were the most prevalent symptoms at follow-up. Using FAS, 47% reported mild-to-moderate fatigue and 18% severe fatigue. Mean HADS was 7.9 (95% CI: 6.9, 8.9). FAS was correlated to HADS (β = 0.52 (95% CI: 0.44, 0.59, p < 0.001)). Mean DLCO was 80.4% (95% CI: 77.8, 83.0) and 45% had DLCO ˂ 80%. Mean DLCO was significantly reduced in patients treated in the ICU (70.46% (95% CI 65.13, 75.79)). The highest FAS and HADS were seen in patients with the shortest period of hospitalization (2.1 days (95% CI: 1.4, 2.7)) with no need for oxygen. In conclusion, fatigue is a common symptom after hospitalization for COVID-19 and ICU treatment is associated to decreased diffusion capacity.

1. Introduction

In December 2019, a new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, causing Coronavirus disease 2019 (COVID-19) [1]. At this point, more than 452 million COVID-19 cases and 6 million deaths have been confirmed worldwide. COVID-19 is a heterogeneous disease affecting the respiratory system, with fever, fatigue and cough as the most prevalent symptoms [2]. The disease course spans from asymptomatic infection to severe respiratory and multiorgan failure and subsequent death. Approximately 95% of patients experience a mild or moderate course of disease [3,4]. Elderly patients, especially those with one or more comorbidities, and non-vaccinated individuals are at risk of severe disease and fatal outcome [5,6,7].
At the beginning of the first pandemic wave, reports suggested an increase in persistent multiorgan symptoms months after acute illness; this was later defined as long Covid if symptoms persisted for more than three months [8]. The most prevalent symptoms of long Covid are fatigue (approx. 70%) and dyspnea (approx. 50%) reported in patients months after discharge [9,10,11]. Furthermore, several studies have found radiological abnormalities [12], mildly reduced diffusion capacity for carbon monoxide (DLCO) [13] and relatively preserved dynamic lung volumes, which contrast patients’ experience of debilitating dyspnea months after admission [14].
Recent evidence on long Covid suggests that females and patients with a medical history of mental disease (anxiety or depression) are at increased risk of prolonged fatigue [15]. One study [16] found that females were at increased risk of mental disease at follow-up, including sleep disorder, anxiety and depression. Studies found that patients with severe disease [17], and multiple symptoms in the acute phase of COVID-19 [18] were at higher risk of developing prolonged fatigue and long Covid. However, Shang et al. [16] found no association between disease severity and risk of long-term fatigue. So far, the pathophysiological background for long Covid remains largely unknown.
The aim of the present study was to systematically describe the frequency and form of ongoing long-term respiratory symptoms reported after hospitalization for COVID-19 and relate these findings to physiological measures and patient reported outcome measures (PROMs).

2. Materials and Methods

2.1. Study Participants

Patients at 18 years or older hospitalized for COVID-19 with a confirmed SARS-CoV-2 infection by positive polymerase chain reaction (PCR) testing were referred to a clinical follow-up visit three months after hospitalization at six hospitals in the Central Denmark Region with a total population of approx. 1.3 million. At the clinical follow-up visit, patients were invited to participate in the study.
Patients were included after giving written informed consent. The study was approved by The Central Denmark Region Committee on Health Research Ethics (file number 1-10-72-130-20) and The Danish Data Protection Agency (1-16-02-203-20). The trial is registered in clinicaltrials.gov (ID NCT04401163).

2.2. Clinical Data

Data were obtained from patient records on demographics, time from onset of symptoms to admission, length of hospitalization and treatment including oxygen therapy, nasal high flow oxygen (NHF), ICU stay and/or, ventilator treatment, pharmacological treatment as well as comorbidity and smoking status. Administration of Remdesivir and Dexamethasone (RaD) was registered. Treatment with RaD was implemented and changed during the inclusion period for the included subjects, and administration pattern for these drugs thus reflects changing treatment recommendations.
At follow-up, a structured interview guide was used to register information on respiratory symptoms and duration together with physiological tests and PROMs.

2.3. Pulmonary Function and Six-Minute Walk Test

At follow-up, patients completed a pulmonary function test (PFT) including flow-volume curves and body plethysmography with registration of forced expiratory volume in one second (FEV1), forced vital capacity (FVC), total lung capacity (TLC), residual volume (RV) and diffusion capacity (DLCO) for carbon monoxide (MasterScreen PFT; Jaeger, Germany). PFT was conducted according to European Respiratory Society and American Thoracic Society (ATS) guidelines and stated according to reference values [19,20,21].
At follow-up, exercise capacity was assessed by a six-minute walk test (6MWT) [22]. Reference equations were used to calculate predicted 6MWT distance (6MWTD) [23]. Patient-reported dyspnea before, during and after the 6MWT was measured using the Borg scale [24]. Peripheral arterial oxygen saturation was measured using a pulse oximeter placed on the index finger, and pre-test oxygen saturation as well as maximum desaturation was recorded.

2.4. Patient Reported Outcome Measures

The Fatigue Assessment Scale (FAS) is a self-reported 10-item questionnaire validated in patients with sarcoidosis [25]. The total score ranges from 10 to 50. A FAS score between 0–21 indicates no fatigue, 22–34 indicates mild-to-moderate fatigue and ≥35 indicates severe fatigue [26].
The MRC scale contains five statements that score the degree of disability associated with dyspnea. A score of 1 indicates no disability, and a score of 5 indicates severe incapacity [27].
The Hospital Anxiety and Depression Scale (HADS) is a 14-item scale assessing depression and anxiety with emphasis on minimizing the impact of physical illness on the total score. The items are rated on a 4-point severity scale. HADS consists of two scales, one for depression, HADS-D, and one for anxiety, HADS-A. Based on previous studies, a cut-off ≥8 was used to identify cases [28,29].

2.5. Statistics

Continuous data are presented as means with 95% confidence intervals (95% CI). Normal distribution of data was assessed using histograms and Q-Q plots. Categorical variables are reported as proportions of the total population.
The impact of clinical variables on disease severity was tested using multivariable linear regression models for continuous data yielding a regression coefficient (β) describing the differences between groups. Comparison of binary outcome variables between treatment groups were made using multivariable logistic regression yielding odds ratio (OR). A backward stepwise selection was used to select variables associated with outcomes. Variables age, sex and BMI were included in the multivariable model, all with a p-value < 0.2.
Patients who did not receive oxygen during hospitalization were the reference group in the statistical analysis. A p-value < 0.05 was considered statistically significant.
Stata (version 17.0, StataCorp, College Station, TX, USA) was used for statistical analysis.

3. Results

3.1. Baseline Data during Hospitalization

A total of 218 patients were included (mean age 59.9 (95% CI: 58.2, 61.7)), 128 (59%) males. Mean body mass index (BMI) was 29.2 (95% CI: 28.5, 29.9) and 106 (54%) had never smoked. The most frequent comorbidities were hypertension, asthma and diabetes. Table 1 presents basic demographic characteristics of participants. See Supplementary Material, Table S1, for additional details.
During admission, 57 (26%) patients received no oxygen therapy, 120 (55%) received oxygen at the ward and 41 (19%) were treated at the ICU. A total of 22 (10%) patients received ventilator treatment, and one patient was treated with extracorporeal membrane oxygenation (ECMO).
In a multivariable model, patients in the ICU were older (mean age 62.3 vs. 54.0, p = 0.057) had a higher BMI (30.4 vs. 28.2, p = 0.067), and were more often males (80% vs. 42%, p = 0.005) compared to patients who did not need oxygen therapy.
Mean time from onset of symptoms to admission was 8.4 days (95% CI: 7.4, 9.4), and did not differ between patients receiving oxygen therapy or not, or whether treatment in the ICU was needed or not. Overall, mean length of hospital stay was 9.3 days (95% CI: 7.7, 10.9); longest length of stay (26.4 days, 95% CI: 21.3, 31.4) was seen in patients treated in the ICU.

3.2. Follow-Up

Mean time from hospitalization to follow-up was 127.7 days (95% CI: 122.2, 133.1). The most prevalent symptoms at follow-up were fatigue (61%), dyspnea (55%) and impaired concentration (34%). Overall, 86% of all patients reported at least one symptom. Symptoms reported at follow-up did not differ significantly between groups (Figure 1). See Supplementary Material, Table S2, for additional symptoms at follow-up. Table 2 presents patient characteristics at follow-up.

3.3. Pulmonary Function Test

At follow-up, mean FEV1 was 2.9 l (95% CI: 2.8, 3.0) and FEV1 percent predicted (FEV1%) was 98.2% (95% CI: 95.5, 100.9). A total of 27 patients (13%) had FEV1 ˂ 80% predicted, and 11 patients (5%) FEV1 ˂ 60% predicted. Mean TLC and RV percent predicted were within the normal range. Mean DLCO was 80.4% (95% CI: 77.8, 83.0) predicted (DLCO%). DLCO% was ˂80% predicted in 96 (45%) patients and ˂60% in 35 patients (16%).
FEV1, FVC, DLCO, TLC and RV were all significantly lower in patients admitted to the ICU compared to patients not needing oxygen therapy. However, only DLCO was decreased below the lower limit of normal (Table 2).

3.4. Six-Minute Walk Test (6MWT)

Mean 6MWTD at follow-up was 486.9 m (95% CI: 471.9, 501.9). The predicted walk distance was lower in males (84.7%, 95% CI: 81.6, 87.8) compared to females (95.9%, 95% CI: 91.4, 100.6), (p < 0.001). Mean desaturation was 2.9 percentage points (95% CI: 2.4, 3.4). A decrease in oxygen saturation of more than 4 percentage points was observed in 53 (27%) patients. Patients admitted to the ICU desaturated significantly more often ≥4 percentage points and below 92% compared to patients not needing oxygen therapy (Table 2).

3.5. Patient Reported Outcome Measures

3.5.1. FAS

Most patients experienced significant fatigue; 88 patients (47%) had mild-to-moderate fatigue indicated by a FAS score of 22–34 and 34 patients (18%) had severe fatigue indicated by a FAS score ≥ 35. FAS scores were significantly higher in females compared to males (p = 0.02).
The highest FAS score was found in younger patients and patients who did not receive oxygen therapy during hospitalization (Figure 2, panel A and Table 2). Severe fatigue (FAS score ≥ 35) was more often reported in these groups (Figure 2, panel B and Table 2).

3.5.2. HADS

Mean HADS was 7.9 (95% CI: 6.9, 8.9). The HADS-A score was higher than HADS-D in all subgroups. The highest HADS-scores were found in younger patients and patients who did not receive oxygen therapy during hospitalization (Figure 3 and Table 2).

3.5.3. MRC

Overall, mean MRC score was 1.9 (95% CI: 1.8, 2.1). Patients treated in the ICU had the highest MRC score (p = 0.08) and the highest percentage (n = 12, 31%) of patients with MRC scores ≥ 3 was seen among patients treated in the ICU.
A total of 48 patients had MRC scores ≥ 3 of whom 31 (65%) had a FEV1% within the normal range and 38 (79%) had a FVC percent predicted (FVC%) within the normal range. MRC scores ≥ 3 were reported by 19 (40%) patients with DLCO% within the normal range.

3.5.4. Relationship between FAS and Other Parameters

A positive correlation between FAS and HADS total score was found (β = 0.52 (95% CI: 0.44, 0.59, p < 0.001)) indicating an increase in FAS of 1 was associated to an increase in HADS score of 0.52. In addition, a negative correlation was found between FAS and 6MWTD (−1.92 (−3.62, −0.22), p = 0.03) indicating patients with fatigue had a shorter walking distance. FAS was not related to DLCO, anticoagulant treatment or smoking status.

3.6. Remdesivir and Dexamethasone Subgroup Analysis

Patients receiving RaD were younger (p = 0.01) and had more comorbidities (1.8 (95% CI: 1.6, 2.0)) compared to patients not receiving RaD (1.1 (95% CI: 0.8, 1.4), p < 0.001). Length of hospital stay was non-significantly shorter in the group receiving RaD with a mean of 9.2 days (95%CI: 7.1, 11.4) compared to a mean of 12.3 days (95% CI: 8.8, 15.7) in the group not receiving RaD (p = 0.07).
Patients receiving RaD reported a higher HADS score (8.8 vs. 5.7, p = 0.008) and higher scores in both depression and anxiety subscales. However, a higher number of cases with a score ≥ 8 was not found in patients treated with RaD.
Pulmonary function test, 6MWTD, FAS and MRC were similar in the two groups. Patients treated with RaD had an increased risk of desaturation during 6MWT at follow-up (β 1.77, p = 0.02) and reported a higher change in Borg Scale score (β 1.16, p = 0.04). Table 3 shows patient characteristics stratified for treatment with RaD. See Supplementary Material, Table S3, for additional details.

4. Discussion

Fatigue was a major symptom following hospitalization for PCR-proven COVID-19 infection at six hospitals in Central Denmark Region and the incidence at follow-up was in line with several previous studies reporting fatigue in 52–63% of participants [8,15,30]. Other common symptoms at follow-up were dyspnea (55%), impaired concentration (34%) and muscle pain (30%). The FAS score was increased in the majority of patients and the highest fatigue scores were found in younger patients, females and patients who had not received oxygen therapy. Mean DLCO and lung volumes were normal, although in 45% of patients the DLCO% was ˂80%. Patients treated in the ICU had the lowest DLCO and desaturated most often ≥4 percentage points during the 6MWT.
Dennis et al. and Goërtz et al. reported an incidence of fatigue of more than 95%. However, they used patient self-reported fatigue and did not report fatigue measured by standardized PROMs such as the FAS score [30,31]. Moreover, the study populations in these two studies included younger patients (median age 44 years and 47 years, respectively) and the majority were not hospitalized [32,33]. Conversely, other studies have reported a lower incidence of fatigue between 16% and 39% [34,35]. In the latter studies, patients had fewer comorbidities, which may explain the lower incidence of fatigue. Our study is the first to document a high incidence of fatigue among patients with a normal PFT.
Using validated PROMs, we found a high incidence of fatigue (65%), anxiety (23%) and depression (16%) in our cohort. Surprisingly, the highest fatigue and anxiety scores were found in younger patients hospitalized for the shortest period (2.1 days (95% CI: 1.4, 2.7)) without the need for oxygen therapy and with a correlation between fatigue and HADS. This is in keeping with a previous study reporting that fatigue was independent of disease severity and most pronounced in females [15]. Several mechanisms of the SARS-CoV-2 virus entering and affecting the central nervous system have been proposed and may explain the high incidence of neurocognitive deficits such as fatigue, concentration difficulty and dysgeusia at follow-up [36,37]. Furthermore, it may be speculated that external factors during a pandemic, e.g., physical inactivity during lockdown and emotional stress and concern could be a significant contributor to fatigue and reduced exercise capacity in long Covid [38,39].
In our cohort, dyspnea was reported by more than 50% of participants, and surprisingly, dyspnea was also a common symptom in the subgroup of patients with a normal FEV1 (52%) and DLCO (47%). Substantial dyspnea indicated by an MRC score ≥ 3 was frequent in patients with a normal FEV1% (65%), FVC% (79%) and DLCO% (40%) indicating that extrapulmonary factors most likely contribute to a high MRC score. We did not find any association between fatigue and dyspnea. Dysfunctional breathing has been suggested as a possible explanation for chronic dyspnea and exercise intolerance among some patients with long covid [31,40].
The 6MWTD was significantly shorter in patients who had received oxygen therapy or had been admitted to the ICU during hospitalization for COVID-19, and a shorter 6MWTD was related to an increased FAS, probably reflecting physical inactivity as discussed above. In addition, patients admitted to the ICU more often desaturated ≥4 percentage points and below 92%. These findings are in contrast to previous reports by Huang et al. and Van Den Borst et al., who both reported an equal walk distance across patients with mild, severe and critical disease [30,41]. Our findings correlate with the reduced DLCO in patients treated in ICU but did not correlate with fatigue. This may reflect that the lung parenchyma or ventilator-induced lung injury may have affected patients with severe respiratory failure during COVID-19 for several months after recovery, or it may represent pre-existing lung affection in patients who developed respiratory failure. It also indicates that post-covid dyspnea may have different physiological correlates in patients with mild and severe COVID-19, as self-reported dyspnea and high MRC scores were also highly prevalent in patients with mild disease and normal gas transfer. This finding underlines that dyspnea is a complex symptom that may involve several other mechanisms than those of the respiratory system.
Treatment with RaD was introduced in May 2020, which was during the inclusion period of this study. A non-significant reduction in length of admission and number of ICU admissions were found in patients receiving RaD, supporting the non-significant findings on Remdesivir by the WHO Solidarity Trial [42]. The use of RaD did not impact on long Covid concerning the burden of fatigue and other symptoms, although higher HADS and HADS-D scores were found. There was no increase in the number of cases with a score ≥ 8. The incidence of ICU admission was significantly reduced in patients receiving RaD (p = 0.02). One explanation to this finding could be that patients receiving RaD were significantly younger (p = 0.01). Only one study by Boglione et al. has previously investigated long Covid among patients treated with RaD. In contrast to our findings, Boglione et al. demonstrated reduced functional impairment at follow-up among patients treated with RaD using The Post-COVID-19 Functional Status scale [43,44]. Boglione et al. in their cohort found fatigue in 47.9%, myalgias/arthralgias in 40% and dyspnea in 50.8% at follow-up, which was similar to results in patients treated in the ICU. The study by Boglione et al. as well as the present study are observational and were not designed to evaluate the impact of RaD on long Covid; the results should thus be interpreted with caution. Other factors may impact on the results, as RaD was introduced concomitantly with changes of non-pharmacologic treatment and admission criteria to hospitals and to the ICU. Further studies are thus needed to clarify if RaD had a direct impact on long Covid.
Our study has some limitations. First, this observational study holds a risk of sampling bias, as lack of referral of patients with milder symptoms, or a higher willingness to participate in the study among patients experiencing debilitating symptoms, may have affected our results; also, we did not have access to information of the patients who did not participate. Second, the lack of pre-hospitalization baseline data makes it difficult to estimate the direct impact of COVID-19. However, we found that especially fatigue was overrepresented in younger persons with mild disease, making it less likely that this is a result of pre-existing conditions. Third, we cannot conclude if the results presented here are specific to COVID-19 or if they reflect a general tendency after a respiratory viral infection. Further studies including control groups representing healthy individuals and patients recovering from other infectious disease, e.g., influenza, pneumonia and common colds, would significantly increase our knowledge in this field.
However, our study also has several strengths. One of the strengths is the multicenter prospective design with patients included systematically during the first two waves of the pandemic. The study includes patients with different disease courses during hospitalization and highlights important PROMs and objective measures.

5. Conclusions

This study demonstrates that significant fatigue is common after hospitalization for Covid19 and is associated with younger age, shorter hospital stay and preserved pulmonary function. Contrary, desaturation during 6MWT and diffusion impairment mainly affected patients who had been treated in the ICU.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/jcm11092411/s1, Table S1: Additional basic demographic characteristics during hospitalization. Table S2: Additional characteristics for patients hospitalized for PCR-proven COVID-19 at follow-up. Table S3: Additional demographics and outcomes at follow-up stratified for treatment with RaD.

Author Contributions

Conceptualization, S.S., A.F., S.L., L.K., J.M.S., S.J.-F. and E.B.; methodology, S.S., A.F., S.L. and E.B.; software, S.S.; validation, S.S., A.F., S.L. and E.B.; formal analysis, S.S.; investigation, S.S., A.F., T.G., A.T., L.K., C.H., L.D.S., J.M.S. and E.B.; data curation, S.S.; writing—original draft preparation, S.S., A.F., S.L. and E.B.; writing—review and editing S.S., A.F., S.L., C.H., J.M.S., S.J.-F. and E.B.; project administration, S.S., A.F., S.L. and E.B.; funding acquisition, S.S. and E.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Novo Nordisk Foundation, grant number NNF21OC0066984.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by The Central Denmark Region Committee on Health Research Ethics (file number 1-10-72-130-20).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

All data used during the study are available on reasonable request.

Acknowledgments

Study Group; Multidisciplinary Systematic Investigation and Experimental Treatment of Long-Term COVID-19 Illness.

Conflicts of Interest

E.B. has received honoraria for lectures and presentations from Boehringer; Ingelheim, Roche, AstraZeneca and Galapagos; support for attending meetings and/or travel from; Boehringer Ingelheim and Roche; and participation on a safety monitoring board or advisory board for Boehringer Ingelheim and Roche. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. S.S., A.F., S.L., C.H., T.G., A.T., L.K., L.D.S., S.J.-F. and J.M.S. declare no conflict of interest.

References

  1. Zhu, N.; Zhang, D.; Wang, W.; Li, X.; Yang, B.; Song, J.; Zhao, X.; Huang, B.; Shi, W.; Lu, R.; et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 2020, 382, 727–733. [Google Scholar] [CrossRef] [PubMed]
  2. Grant, M.C.; Geoghegan, L.; Arbyn, M.; Mohammed, Z.; McGuinness, L.; Clarke, E.L.; Wade, R.G. The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries. PLoS ONE 2020, 15, e0234765. [Google Scholar] [CrossRef] [PubMed]
  3. Gattinoni, L.; Gattarello, S.; Steinberg, I.; Busana, M.; Palermo, P.; Lazzari, S.; Romitti, F.; Quintel, M.; Meissner, K.; Marini, J.J.; et al. COVID-19 pneumonia: Pathophysiology and management. Eur. Respir. Rev. 2021, 30, 210138. [Google Scholar] [CrossRef] [PubMed]
  4. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. China CDC Wkly. 2020, 41, 145–151.
  5. Zhou, F.; Yu, T.; Du, R.; Fan, G.; Liu, Y.; Liu, Z.; Xiang, J.; Wang, Y.; Song, B.; Gu, X.; et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020, 395, 1054–1062. [Google Scholar] [CrossRef]
  6. Wang, Y.; Lu, X.; Li, Y.; Chen, H.; Chen, T.; Su, N.; Huang, F.; Zhou, J.; Zhang, B.; Yan, F.; et al. Clinical course and outcomes of 344 intensive care patients with COVID-19. Am. J. Respir. Crit. Care Med. 2020, 201, 1430–1434. [Google Scholar] [CrossRef] [PubMed]
  7. Vilches, T.N.; Moghadas, S.M.; Sah, P.; Fitzpatrick, M.C.; Shoukat, A.; Pandey, A.; Galvani, A.P. Estimating COVID-19 Infections, Hospitalizations, and Deaths Following the US Vaccination Campaigns during the Pandemic. JAMA Netw. Open 2022, 797, 2020–2023. [Google Scholar] [CrossRef] [PubMed]
  8. Carfi, A. Persistent Symptoms in Patietns after Acute COVID-19. JAMA-J. Am. Med. Assoc. 2020, 324, 603–605. [Google Scholar] [CrossRef]
  9. Leth, S.; Gunst, J.D.; Agergaard, J. Persistent symptoms in hospitalized patients recovering from COVID-19 in Denmark. Infect. Dis. Soc. Am. 2021, 8, ofab042. [Google Scholar]
  10. Bulut, O.; Kilic, G.; Netea, M.G.; Netea, M.G. Disparities in case frequency and mortality of coronavirus disease 2019 (COVID-19) among various states in the United States. Ann. Med. 2020, 53, 151–159. [Google Scholar] [CrossRef]
  11. Vejen, M.; Hansen, E.F.; Al-Jarah, B.N.I.; Jensen, C.; Thaning, P.; Jeschke, K.N.; Ulrik, C.S. Hospital admission for COVID-19 pneumonitis–long-term impairment in quality of life and lung function. Eur. Clin. Respir. J. 2022, 9, 2024735. [Google Scholar] [CrossRef]
  12. Liu, C.; Ye, L.; Xia, R.; Zheng, X.; Yuan, C.; Wang, Z.; Lin, R.; Shi, D.; Gao, Y.; Yao, J.; et al. Chest CT and Clinical Follow-up of Discharged Patients with COVID-19 in Wenzhou City, Zhejiang, China. Ann. Am. Thorac. Soc. 2020, 17, 1231–1237. [Google Scholar] [CrossRef] [PubMed]
  13. You, J.; Zhang, L.; Zhang, J.; Hu, F.; Chen, L.; Dong, Y.; Yang, K.; Zhang, B.; Zhang, S. Anormal pulmonary function and residual CT abnormalities in rehabilitating COVID-19 patients after discharge. J. Infect. 2020, 81, e150–e152. [Google Scholar] [CrossRef] [PubMed]
  14. Huang, L. 1-year outcomes in hospital survivors with COVID-19: A longitudinal cohort study. Lancet 2021, 398, 747–758. [Google Scholar] [CrossRef]
  15. Townsend, L.; Dyer, A.H.; Jones, K.; Dunne, J.; Mooney, A.; Gaffney, F.; O’Connor, L.; Leavy, D.; O’Brien, K.; Dowds, J.; et al. Persistent fatigue following SARS-CoV-2 infection is common and independent of severity of initial infection. PLoS ONE 2020, 15, e0240784. [Google Scholar] [CrossRef] [PubMed]
  16. Shang, Y.F.; Liu, T.; Yu, J.N.; Xu, X.R.; Zahid, K.R.; Wei, Y.C.; Wang, X.H.; Zhou, F.L. Half-year follow-up of patients recovering from severe COVID-19: Analysis of symptoms and their risk factors. J. Intern. Med. 2021, 290, 444–450. [Google Scholar] [CrossRef] [PubMed]
  17. Blomberg, B.; Mohn, K.G.I.; Brokstad, K.A.; Zhou, F.; Linchausen, D.W.; Hansen, B.A.; Lartey, S.; Onyango, T.B.; Kuwelker, K.; Sævik, M.; et al. Long COVID in a prospective cohort of home-isolated patients. Nat. Med. 2021, 27, 1607–1613. [Google Scholar] [CrossRef]
  18. Sudre, C.H.; Murray, B.; Varsavsky, T.; Graham, M.S.; Penfold, R.S.; Bowyer, R.C.; Pujol, J.C.; Klaser, K.; Antonelli, M.; Canas, L.S.; et al. Attributes and predictors of long COVID. Nat. Med. 2021, 27, 626–631. Available online: http://www.nature.com/articles/s41591-021-01292-y (accessed on 22 April 2022). [CrossRef]
  19. Wanger, J.; Clausen, J.L.; Coates, A.; Pedersen, O.F.; Brusasco, V.; Burgos, F.; Casaburi, R.; Crapo, R.; Enright, P.; van der Grinten, C.P.M.; et al. Standardisation of the measurement of lung volumes. Eur. Respir. J. 2005, 26, 511–522. [Google Scholar] [CrossRef]
  20. Graham, B.L.; Brusasco, V.; Burgos, F.; Cooper, B.G.; Jensen, R.; Kendrick, A.; Macintyre, N.R.; Thompson, B.R.; Wanger, J. 2017 ERS/ATS standards for single-breath carbon monoxide uptake in the lung. Eur. Respir. J. 2017, 49, 1600016. [Google Scholar] [CrossRef] [Green Version]
  21. Miller, M.R.; Hankinson, J.; Brusasco, V.; Burgos, F.; Casaburi, R.; Coates, A.; Crapo, R.; Enright, P.; van der Grinten, C.P.M.; Gustafsson, P.; et al. Standardisation of spirometry. Eur. Respir. J. 2005, 26, 319–338. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Holland, A.E.; Spruit, M.A.; Troosters, T.; Puhan, M.A.; Pepin, V.; Saey, D.; McCormack, M.C.; Carlin, B.W.; Sciurba, F.C.; Pitta, F.; et al. An official European respiratory society/American thoracic society technical standard: Field walking tests in chronic respiratory disease. Eur. Respir. J. 2014, 44, 1428–1446. [Google Scholar] [CrossRef] [PubMed]
  23. Jay, S.J.; Enright, P. Reference equations for the six-minute walk in healthy adults. Am. J. Respir. Crit. Care Med. 2000, 161, 1396. [Google Scholar] [CrossRef] [PubMed]
  24. Borg, G.A. Psychophysical bases of perceived exertion. Med. Sci. Sport. Exerc. 1982, 14, 377–381. [Google Scholar] [CrossRef]
  25. De Vries, J.; Michielsen, H.; Van Heck, G.L.; Drent, M. Measuring fatigue in sarcoidosis: The Fatigue Assessment Scale (FAS). Br. J. Health Psychol. 2004, 9, 279–291. [Google Scholar] [CrossRef] [Green Version]
  26. Hendriks, C.; Drent, M.; Elfferich, M.; De Vries, J. The Fatigue Assessment Scale: Quality and availability in sarcoidosis and other diseases. Curr. Opin. Pulm. Med. 2018, 24, 495–503. [Google Scholar] [CrossRef]
  27. Stenton, C. The MRC breathlessness scale. Occup. Med. 2008, 58, 226–227. [Google Scholar] [CrossRef] [Green Version]
  28. Snaith, R.P.; Zigmond, A.S. The hospital anxiety anddepression scale. Br. Med. J. 1986, 292, 344. [Google Scholar] [CrossRef] [Green Version]
  29. Bjelland, I.; Dahl, A.A.; Haug, T.T.; Neckelmann, D. The validity of the Hospital Anxiety and Depression Scale. J. Psychosom. Res. 2002, 52, 69–77. [Google Scholar] [CrossRef]
  30. Huang, C.; Huang, L.; Wang, Y.; Li, X.; Ren, L.; Gu, X.; Kang, L.; Guo, L.; Liu, M.; Zhou, X.; et al. 6-month consequences of COVID-19 in patients discharged from hospital: A cohort study. Lancet 2021, 397, 220–232. [Google Scholar] [CrossRef]
  31. Motiejunaite, J.; Balagny, P.; Arnoult, F.; Mangin, L.; Bancal, C.; d’Ortho, M.P.; Frija-Masson, J. Hyperventilation: A Possible Explanation for Long-Lasting Exercise Intolerance in Mild COVID-19 Survivors? Front. Physiol. 2021, 11, 614590. [Google Scholar] [CrossRef] [PubMed]
  32. Dennis, A.; Wamil, M.; Alberts, J.; Oben, J.; Cuthbertson, D.J.; Wootton, D.; Crooks, M.; Gabbay, M.; Brady, M.; Hishmeh, L.; et al. Multiorgan impairment in low-risk individuals with post-COVID-19 syndrome: A prospective, community-based study. BMJ Open 2021, 11, 2–7. [Google Scholar]
  33. Goërtz, Y.M.J.; Van Herck, M.; Delbressine, J.M.; Vaes, A.W.; Meys, R.; Machado, F.V.C.; Houben-Wilke, S.; Burtin, C.; Posthuma, R.; Franssen, F.M.E.; et al. Persistent symptoms 3 months after a SARS-CoV-2 infection: The post-COVID-19 syndrome? ERJ Open Res. 2020, 6, 00542–02020. [Google Scholar] [CrossRef] [PubMed]
  34. Zhao, Y.; Shang, Y.; Song, W.; Li, Q.; Xie, H.; Xu, Q.; Jia, J.; Li, L.; Mao, H.; Zhou, X.; et al. Follow-up study of the pulmonary function and related physiological characteristics of COVID-19 survivors three months after recovery. EClinicalMedicine 2020, 25, 100463. [Google Scholar] [CrossRef]
  35. Arnold, D.T.; Hamilton, F.W.; Milne, A.; Morley, A.J.; Viner, J.; Attwood, M.; Noel, A.; Gunning, S.; Hatrick, J.; Hamilton, S.; et al. Patient outcomes after hospitalisation with COVID-19 and implications for follow-up: Results from a prospective UK cohort. Thorax 2021, 76, 399–401. [Google Scholar] [CrossRef] [PubMed]
  36. Abboud, H. COVID-19 and SARS-CoV-2 Infection: Pathophysiology and Clinical Effects on the Nervous System. World Neurusurg. 2020, 140, 49–53. [Google Scholar] [CrossRef] [PubMed]
  37. Kumar, S.; Veldhuis, A.; Malhotra, T. Neuropsychiatric and Cognitive Sequelae of COVID-19. Front. Psychol. 2021, 12, 553. [Google Scholar] [CrossRef]
  38. Brooks, S.K.; Webster, R.K.; Smith, L.E.; Woodland, L.; Wessely, S.; Greenberg, N.; Rubin, G.J. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet 2020, 395, 912–920. Available online: http://www.ncbi.nlm.nih.gov/pubmed/32112714 (accessed on 22 April 2022). [CrossRef] [Green Version]
  39. Morgul, E.; Bener, A.; Atak, M.; Akyel, S.; Aktaş, S.; Bhugra, D.; Ventriglio, A.; Jordan, T.R. COVID-19 pandemic and psychological fatigue in Turkey. Int. J. Soc. Psychiatry 2021, 67, 128–135. [Google Scholar] [CrossRef]
  40. Taverne, J.; Salvator, H.; Leboulch, C.; Barizien, N.; Ballester, M.; Imhaus, E.; Chabi-Charvillat, M.L.; Boulin, A.; Goyard, C.; Chabrol, A.; et al. High incidence of hyperventilation syndrome after COVID-19. J. Thorac. Dis. 2021, 13, 3918–3922. [Google Scholar] [CrossRef]
  41. Van Den Borst, B.; Peters, J.B.; Brink, M.; Schoon, Y.; Bleeker-Rovers, C.P.; Schers, H.; Van Hees, H.W.H.; Van Helvoort, H.; Van Den Boogaard, M.; Van Der Hoeven, H.; et al. Comprehensive Health Assessment 3 Months after Recovery from Acute Coronavirus Disease 2019 (COVID-19). Clin. Infect. Dis. 2021, 73, E1089–E1098. [Google Scholar] [CrossRef] [PubMed]
  42. Repurposed Antiviral Drugs for Covid-19—Interim WHO Solidarity Trial Results. N. Engl. J. Med. 2021, 384, 497–511. [CrossRef] [PubMed]
  43. Boglione, L.; Meli, G.; Poletti, F.; Rostagno, R.; Moglia, R.; Cantone, M.; Esposito, M.; Scianguetta, C.; Domenicale, B.; Di Pasquale, F.; et al. Risk factors and incidence of long-COVID syndrome in hospitalized patients: Does remdesivir have a protective effect? QJM An Int. J. Med. 2022, 114, 865–871. [Google Scholar] [CrossRef] [PubMed]
  44. Klok, F.A.; Boon, G.J.A.M.; Barco, S.; Endres, M.; Miranda Geelhoed, J.J.; Knauss, S.; Rezek, S.A.; Spruit, M.A.; Vehreschild, J.; Siegerink, B. The post-COVID-19 functional status scale: A tool to measure functional status over time after COVID-19. Eur. Respir. J. 2020, 56, 10–12. [Google Scholar] [CrossRef]
Jcm 11 02411 g001 550
Figure 1. Prevalence of 10 most common symptoms at follow-up. Prevalence of each symptom is illustrated in 3 groups; (1) patients not requiring supplemental oxygen (2) patients requiring supplemental oxygen (3) patients admitted at ICU (3).
Figure 1. Prevalence of 10 most common symptoms at follow-up. Prevalence of each symptom is illustrated in 3 groups; (1) patients not requiring supplemental oxygen (2) patients requiring supplemental oxygen (3) patients admitted at ICU (3).
Jcm 11 02411 g001
Jcm 11 02411 g002 550
Figure 2. (Panel A) Graph bar showing the mean values of Fatigue Assessment Scale (FAS) by age groups. (Panel B) Graph bar showing the percent of patients with “Severe fatigue” (FAS score ≥ 35), “Mild-to-moderate fatigue (FAS score 22–34) and “No fatigue” (FAS score ≤ 21), by age groups.
Figure 2. (Panel A) Graph bar showing the mean values of Fatigue Assessment Scale (FAS) by age groups. (Panel B) Graph bar showing the percent of patients with “Severe fatigue” (FAS score ≥ 35), “Mild-to-moderate fatigue (FAS score 22–34) and “No fatigue” (FAS score ≤ 21), by age groups.
Jcm 11 02411 g002
Jcm 11 02411 g003 550
Figure 3. Mean scores from subscales on anxiety (HADS-A) and depression (HADS-D) in Hospital Anxiety and Depression Scale (HADS), by age groups. A score ≥ 8 identifies cases.
Figure 3. Mean scores from subscales on anxiety (HADS-A) and depression (HADS-D) in Hospital Anxiety and Depression Scale (HADS), by age groups. A score ≥ 8 identifies cases.
Jcm 11 02411 g003
Table
Table 1. Basic demographic characteristics during hospitalization.
Table 1. Basic demographic characteristics during hospitalization.
Overall. n = 218Patients Not Requiring Supplemental Oxygen (Group 1)
(n = 57)		Patients Requiring Supplemental Oxygen (Group 2)
(n = 120)		Patients Admitted to ICU (Group 3)
(n = 41)
Age (years)59.94 (58.15, 61.73)54.04 (50.36, 57.71)62.3 (59.94, 64.66)61.24 (57.58, 64.90)
Sex
Male128 (59%)24 (42%)71 (59%)33 (80%)
Female90 (41%)33 (58%)49 (41%)8 (20%)
Body Mass Index29.24 (28.51, 29.98)28.21 (26.71, 29.71)29.34 (28.31, 30.36)30.37 (28.90, 31.84)
<18.51 (0%)1 (2%)0 (0%)0 (0%)
18.5–24.944 (21%)13 (24%)25 (21%)6 (15%)
25.0–29.990 (42%)25 (45%)50 (43%)15 (37%)
≥3078 (37%)16 (29%)42 (36%)20 (49%)
Smoking status
Ever92 (46%)23 (43%)46 (43%)23 (61%)
Never106 (54%)31(57%)60 (57%)15 (39%)
Comorbidities *
Hypertension71 (33%)11 (19%)41 (34%)19 (46%)
Asthma36 (17%)8 (14%)21 (18%)7 (17%)
Diabetes28 (13%)4 (7%)17 (14%)7 (17%)
Malignancy20 (9%)7 (12%)10 (8%)3 (7%)
Chronic obstructive pulmonary disease (COPD)18 (8%)2 (4%)11 (9%)5 (12%)
Number of patients with more than 3 comorbidities41 (19)9 (16)20 (17)12 (29)
Time from symptom onset to admission (days)8.37 (7.36, 9.37)8.14 (6.20, 10.08)8.42 (6.88, 9.95)8.53 (7.24, 9.81)
Length of hospital stay (days)9.29 (7.74, 10.86)2.05 (1.37, 2.74)6.85 (5.93, 7.77)26.37 (21.30, 31.43)
Treatment during hospitalization
Remdesivir92 (42%)6 (11%)69 (58%)17 (43%)
Systemic corticosteroids119 (55%)11 (19%)81 (68%)27 (68%)
Anticoagulation153 (71%)19 (33%)96 (80%)38 (97%)
Intravenous immunoglobin2 (1%)1 (2%)1 (1%)0 (0%)
Data are n (%), mean (95% CI) * Five most frequent comorbidities.
Table
Table 2. Characteristics for patients hospitalized for PCR-proven COVID-19 at follow-up.
Table 2. Characteristics for patients hospitalized for PCR-proven COVID-19 at follow-up.
All Patients
(n = 218)		Patients Not Requiring Supplemental Oxygen (Group 1)
(n = 57)		Patients Requiring Supplemental Oxygen ** (Group 2)
(n = 120)		Patients Admitted at ICU (Group 3)
(n = 41)		Group 2 vs. Group 1
Multivariable Model		Group 3 vs. Group 1
Multivariable Model
Time from discharge to follow-up (days)127.65 (122.19, 133.11)133.68 (124.11, 143.26)123.26 (115.49, 131.03)132.12 (119.46, 144.78)β (95% CI)
−11.53 (−24.40, 1.35)		β (95% CI)
−7.59 (−24.41, 9.23)
Pulmonary function β (95% CI) β (95% CI)
FEV1, L/min2.91 (2.79, 3.02)3.05 (2.87, 3.23)2.85 (2.68, 3.02)2.90 (2.68, 3.12)−0.13 (−0.34, 0.09)−0.26 (−0.54, 0.02)
FEV1, %98.17 (95.49, 100.85)103.58 (99.45, 107.71)97.71 (93.87, 101.56)91.83 (85.37, 98.28)−5.36 (−11.89, 1.18)−10.78 (−19.23, −2.33) *
FVC, L/min3.77 (3.63, 3.91)3.99 (3.74, 4.25)3.67 (3.47, 3.86)3.74 (3.46, 4.03)−0.31 (−0.59, −0.02)−0.46 (−0.86, −0.06) *
FVC, %103.28 (100.42, 106.15)111.54 (106.59, 116.49)102.37 (98.68, 106.06)94.23 (86.51, 101.94)−8.44 (−15.44, −1.43) *−13.73 (−24.05, −3.40) *
DLCO, %80.43 (77.83, 83.04)88.98 (84.77, 93.19)79.68 (76.04, 83.32)70.46 (65.13, 75.79)−9.71 (−15.49, −3.92) *−23.08 (−30.28, −15.89) *
TLC, %94.05 (91.18, 96.91)99.2 (94.14, 104.26)94.31 (90.48, 98.14)84.38 (77.27, 91.50)−5.10 (−12.55, 2.34)−14.19 (−24.40, −3.98) *
RV, %98.37 (93.83, 102.91)101.73 (93.31, 110.15)99.99 (93.20, 106.77)87.96 (80.00, 95.92)−3.96 (−15.56, 7.64)−15.01 (−29.17, −0.85) *
OR (95% CI)OR (95% CI)
DLCO < 80%96 (45%)15 (27%)54 (45%)27 (69%)2.94 (1.32, 6.51) *13.02 (0.88, 43.65) *
DLCO < 60%35 (16%)2 (4%)22 (18%)11 (28%)4.93 (1.04, 23.31) *24.47 (3.05, 196.24) *
β (95% CI) β (95% CI)
MRC score1.95 (1.82–2.08)1.75 (1.54–1.95)1.96 (1.79–2.14)2.18 (1.80–2.56)0.21 (−0.08, 0.50)0.38 (−0.05, 0.81)
OR (95% CI)OR (95% CI)
MRC score (3–5)48 (24%)8 (15%)28 (26%)12 (31%)1.89 (0.73, 4.95)2.54 (0.71, 9.03)
6MWT β (95% CI) β (95% CI)
6MWTD (m)486.90 (471.87, 501.94)515.33 (489.37, 541.29)479.65 (457.79, 501.51)464.65 (431.40, 497.89)−15.78 (−45.75, 14.20)−31.59 (−73.19, 10.01)
Percent predicted, male84.65 (81.55, 87.75)88.98 (83.74, 94.21)85.38 (81.07, 89.69)79.73 (72.69, 86.77)−3.86 (−10.44, 2.72)−9.82 (−18.30, −1.33) *
Percent predicted, female95.97 (91.35, 100.59)93.09 (85.42, 100.76)95.00 (88.71, 101.29)111.58 (94.94, 128.21)−3.92 (−14.75, 6.91)5.83 (−8.83, 20.48)
Desaturation (%-point)2.89 (2.39, 3.39)2.11 (1.45, 2.77)3.05 (2.25, 3.85)3.65 (2.56, 4.73)0.59 (−0.41, 1.59)1.39 (−0.00, 2.79)
Borg scale before test0.79 (0.58, 1.01)0.57 (0.20, 0.94)0.85 (0.56, 1.13)1.02 (0.35, 1.69)0.17 (−0.36, 0.69)0.34 (−0.44, 1.12)
Borg scale after test 3.64 (3.24, 4.04)3.41 (2.67, 4.15)3.73 (3.19, 4.28)3.73 (2.67, 4.78)0.34 (−0.60, 1.29)0.27 (−1.08, 1.63)
Change in Borg scale2.82 (2.46, 3.18)2.83 (2.15, 3.49)2.85 (2.34, 3.35)2.69 (1.86, 3.53)0.13 (−0.68, 0.95)−0.06 (−1.23, 1.11)
OR (95% CI)OR (95% CI)
Desaturation below 9237 (19%)6 (11%)19 (19%)12 (32%)1.11 (0.39, 3.19)3.94 (1.07, 14.48) *
Desaturation ≥4%-point53 (27%)12 (22%)23 (23%)18 (49%)0.82 (0.35, 1.91)3.44 (1.19, 9.91) *
β (95% CI) β (95% CI)
Fatigue assessment scale25.61 (24.29, 26.93)28.08 (25.45, 30.71)24.66 (22.81, 26.52)25.08 (22.42, 27.74)−1.32 (−4.80, 2.16)−2.05 (−6.29, 2.19)
OR (95% CI)OR (95% CI)
No fatigue67 (35%)11 (23%)42 (40%)14 (38%)1.96 (0.86, 4.45)2.57 (0.86, 7.68)
Mild-to-moderate fatigue88 (47%)25 (52%)45 (43%)18 (49%)0.82 (0.41, 1.65)1.31 (0.52, 3.32)
Severe fatigue34 (18%)12 (25%)17 (16%)5 (14%)0.87 (0.34, 2.22)0.57 (0.16, 2.03)
β (95% CI) β (95% CI)
HADS score total7.94 (6.95, 8.93)9.60 (7.54, 11.67)7.59 (6.27, 8.91)6.76 (4.52, 8.99)−1.17(−3.79, 1.45)−2.90 (−6.15, 0.34)
HADS-D score3.22 (2.71, 3.67)3.56 (2.53, 4.59)3.26 (2.59, 3.94)2.49 (1.59, 3.38)−0.05 (−1.41, 1.31)−1.29 (−2.84, 0.26)
HADS-A score4.75 (4.17, 5.34)6.04 (4.87, 7.21)4.32 (3.56, 5.08)4.27 (2.80, 5.74)−1.12 (−2.59, 0.35)−1.61 (−3.53, 0.31)
OR (95% CI)OR (95% CI)
HADS-D abnormal score (≥8)29 (16%)9 (19%)16 (16%)4 (11%)0.94 (0.35, 2.49)0.54 (0.14, 2.14)
HADS-A abnormal score (≥8)43 (23%)15 (31%)21 (21%)7 (19%)0.73 (0.32)0.69 (0.22, 2.20)
Data are n (%), mean (95% CI). Comparison of groups are presented by regression coefficients (β) (95% CI) for continuous data and as odds ratio (OR) (95% CI) for binary outcomes. * p < 0.05. Comparison was made using multivariable analysis including variables age, sex and BMI ** Patients treated at the ward.
Table
Table 3. Demographics and outcomes at follow-up stratified for treatment with RaD.
Table 3. Demographics and outcomes at follow-up stratified for treatment with RaD.
Oxygen-Dependent Patients Not Receiving Systemic Corticosteroids and Remdesivir (RaD÷) n = 52Oxygen-Dependent Patients Receiving Systemic Corticosteroids and Remdesivir (RaD+) n = 86RaD+ vs. RaD÷
Multivariable Model
β (95% CI)
Age63.54 (59.62, 67.45)61.88 (59.24, 64.53)−5.27 (−9.33, −1.22) *
Sex OR (95% CI)
  Male31 (60%)56 (65%)1.18 (0.55, 2.51)
  Female21 (40%)30 (35%)
Smoking status OR (95% CI)
  Ever23 (48%)37 (47%)1.18 (0.55, 2.51)
  Never25 (52%)41 (53%)
β (95% CI)
Number of comorbidities1.13 (0.84, 1.43)1.79 (1.55, 2.03)0.72 (0.40, 1.04) *
β (95% CI)
Length of hospital stay12.27 (8.84, 15.69)9.22 (7.08, 11.36)−4.04 (−8.38, 0.29)
OR (95% CI)
ICU admission13 (25%)17 (20%)0.19 (0.05, 0.74) *
Number of symptoms at follow-up β (95% CI)
3.27 (2.49, 4.04)3.86 (3.15, 4.57)0.13 (−0.97, 1.24)
β (95% CI)
MRC score1.89 (1.64, 2.15)2.08 (1.85, 2.30)−0.03 (−0.36, 0.29)
OR (95% CI)
MRC score 3–512 (25%)22 (28%)0.81 (0.32, 2.04)
Pulmonary function β (95% CI)
  FEV1, %101.69 (96.30, 107.07)95.0 (90.84, 99.16)−4.17 (−11.11, 2.78)
  FVC, %107.37 (101.08, 113.66)97.92 (93.89, 101.94)−6.64 (−13.86, 0.58)
  DLCO, %80.41 (74.79, 86.04)76.39 (72.21, 80.57)−2.15 (−8.89, 4.59)
6MWT β (95% CI)
6MWTD (m)471.73 (438.67, 504.79)471.55 (445.56, 497.54)20.02 (−17.25, 57.31)
Desaturation during 6MWT (%-point)2.09 (1.25, 2.93)3.79 (2.76, 4.81)1.77 (0.27, 3.27) *
Change in Borg scale score
2.28 (1.60, 2.95)3.37 (2.67, 4.07)1.16 (0.05, 2.27) *
β (95% CI)
FAS score23.73 (21.28, 26.19)25.37 (23.17, 27.57)0.61 (−2.67, 3.89)
OR (95% CI)
No fatigue22 (45%)28 (38%)0.78 (0.36, 1.67)
Mild-to-moderate fatigue23 (47%)31 (42%)0.73 (0.34, 1.54)
Severe fatigue4 (8%)14 (19%)1.65 (0.43, 6.19)
β (95% CI)
HADS score total5.69 (4.17, 7.21)8.82 (7.04, 10.60)2.52 (0.21, 4.83) *
HADS-D score2.22 (1.52, 2.91)3.89 (3.00, 4.79)1.29 (0.20, 2.38) *
HADS-A score3.47 (2.20, 4.44)4.93 (3.88, 5.97)1.23 (−0.22, 2.67)
OR (95% CI)
HADS-D abnormal score (≥8)3 (6%)15 (22%)3.17 (0.78, 12.94)
HADS-A abnormal score (≥8)5 (10%)18 (26%)2.54 (0.82, 7.84)
Data are n (%), mean (95% CI). Comparison of groups are presented by regression coefficients (β) (95% CI) for continuous data and as odds ratio (OR) (95% CI) for binary outcomes. Comparison was made using multivariable analysis including variables age and comorbidities * p < 0.05.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Sperling, S.; Fløe, A.; Leth, S.; Hyldgaard, C.; Gissel, T.; Topcu, A.; Kristensen, L.; Sønderskov, L.D.; Schmid, J.M.; Jensen-Fangel, S.; et al. Fatigue Is a Major Symptom at COVID-19 Hospitalization Follow-Up. J. Clin. Med. 2022, 11, 2411. https://doi.org/10.3390/jcm11092411

AMA Style

Sperling S, Fløe A, Leth S, Hyldgaard C, Gissel T, Topcu A, Kristensen L, Sønderskov LD, Schmid JM, Jensen-Fangel S, et al. Fatigue Is a Major Symptom at COVID-19 Hospitalization Follow-Up. Journal of Clinical Medicine. 2022; 11(9):2411. https://doi.org/10.3390/jcm11092411

Chicago/Turabian Style

Sperling, Søren, Andreas Fløe, Steffen Leth, Charlotte Hyldgaard, Tina Gissel, Ayfer Topcu, Lars Kristensen, Lene Dahl Sønderskov, Johannes Martin Schmid, Søren Jensen-Fangel, and et al. 2022. "Fatigue Is a Major Symptom at COVID-19 Hospitalization Follow-Up" Journal of Clinical Medicine 11, no. 9: 2411. https://doi.org/10.3390/jcm11092411

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop