Design

The prospective observational study took place in a local community of Ribeirao Preto, in the Sao Paulo state of Brazil. The data presented in this study is the baseline evaluation from AEROBICOVID project that proposed physical training and hypoxia exposure intervention. Participants were enrolled in the following inclusion criteria: 1) age between 30 and 69 years old; 2) convalescent from COVID-19 (positive diagnosis); 3) mild to severe symptoms; 4) approximately 30 days since recovery from clinical signs or medical discharge (if they had been hospitalised). In addition, the following exclusion criteria were established: 1) to have an exposure to high-altitude places > 1,500 m in the previous three months; 2) presenting significant physical limitations to be assessed or to join the intervention; 3) presenting acute or chronic clinical illnesses without medical supervision; having anaemia; using immunosuppressive drugs; to be pregnant; hormone replacement; smokers or excessive use of alcohol or drugs.

Participants

Eighty-four participants were included and divided into four groups, based on National Institutes of Health (NIH) of United States of America criteria for COVID-19 severity (22,23): mild (n = 16), who have any symptoms of COVID-19, such as fever, cough, etc., but do not have shortness of breath or dyspnoea; moderate (n = 51), who have any symptoms of COVID-19 and have shortness of breath or dyspnoea; severe (n = 9), who have any symptoms of COVID-19 and need hospitalisation, but not intensive care; or critical (n = 8), who have any symptoms of COVID-19 and need hospitalisation and intensive care. The present study was approved by the research ethic committees of the School of Physical Education and Sport of Ribeirao Preto – University of Sao Paulo (USP) and the Faculty of Pharmaceutical Sciences of Ribeirao Preto – USP (CAAE: 33783620.6.0000.5659, and CAAE: 33783620.6.3001.5403, respectively). Activities started after signing the free and informed consent term presented by the study coordinator. All care was taken for the safety of the participants and the work team. Data were added to a confidential dataset, and an alphanumeric code was assigned to each participant.

Procedure

A standardized health assessment included questionnaires, physical measurements, collected blood samples, and multidisciplinary consultations. These data are related to the participants' baseline evaluation of the AEROBICOVID project, a more extensive project with other evaluations after an intervention of hypoxic training. The experimental protocol has been published elsewhere (24). A register of anamnesis was used to identify the symptoms and comorbidities predictive. Furthermore, the cardiorespiratory system, body composition, haematological and immunological indicators, and physical fitness were assessed to analyze the mild-term health sequelae.

Anamnesis: sociodemographic data, general and specific health status (COVID-19 symptoms) related to lifestyle and information on comorbidity were collected through questionnaires. The definition of metabolic syndrome used for this study is according to the International Diabetes Federation (IDF): central obesity (waist circumference ≥ 90 cm for men or ≥ 80 cm for women) plus two of the following factors: triglyceride levels ≥ 150 mg/dl or specific treatment for this lipid abnormality; HDL cholesterol < 40 mg/dl in men, < 50 mg/dl in women or specific treatment for this lipid abnormality; systolic blood pressure (SBP) ≥ 130 mmHg, diastolic blood pressure (DBP) ≥ 85 mmHg or treatment for arterial hypertension; and fasting plasma glucose ≥ 100 mg/dl or diagnosis of type 2 diabetes mellitus (25).

Anthropometric and body composition assessment: height and body mass were assessed following standard procedures. The body mass index (BMI) was calculated based on height and body weight. A constant tension tape with an accuracy of 0.1 cm was used to determine the waist and hip circumferences. The waist-to-hip ratio was calculated by dividing the waist circumference by the hip circumference (both in cm). Body composition variables such as visceral fat (g), muscle mass (%) and fat mass (%) were obtained using dual-energy X-ray absorptiometry (iDXA - GE Lunar – DPX-NT).

Physical fitness: lower limb strength was evaluated through sit and stand-up test (26). The agility and dynamic balance were also evaluated (27).

Haematological indicators: glucose, total cholesterol, LDL-c, HDL-c, and triglycerides were analyzed from blood samples, collected by specialized professionals, after fasting for 12 hours and storage of pre-analysis samples at -80ºC. The analyses were performed using the serum at the Clinical Analysis Laboratory of the Faculty of Pharmaceutical Sciences of Ribeirao Preto of the University of Sao Paulo (Brazil), utilising an enzymatic analysis kit (Wiener Lab, Rosario, Argentina) on an automatic device (CT 600i; Wiener Lab, Rosario, Argentina). Additionally, a complete blood cell count of red blood cells, white blood cells, lymphocytes, neutrophils, platelets and lactate dehydrogenase were measured using the protocol described above.

Immunological indicators: standardized methods were used to measure cytokines IL-6, IL-8, IL-10 and TNF-α by ELISA kits (R&D Systems, Billings, EUA). Reactions were performed on 96-well ELISA plates (Ultra-High Binding EIA Plates; Corning, Corning, NY, USA). The absorbance was read on a microplate reader (μQuant; BioTek Instruments Inc., Winooski, VT, USA) at a wavelength of 450nm. The cytokine concentration in each sample was estimated by interpolation of a standard curve by a four-parameter curve-fitting program. Sensitivities were >12.5pg/mL.

Statistical Analysis

Descriptive statistics were calculated for sociodemographic characteristics, symptoms and comorbidities, and physical function and health variables. Cut-off of the evaluated indicators were reported (28–32). Using Fisher's exact test, data analysis was performed to verify the statistical association between categorical variables symptoms and comorbidities with the COVID-19 gravity. Comparison of continuous variables between groups was analyzed using analysis of variance adjusted for potential confounding variables identified in descriptive analysis, such as body mass index, age and sex (33), all criteria and assumptions were checked. The plots were run from R (version 4.0) using the ggplot2 package. The significance level was 5%, and the program used was SAS version 9.2, using the PROC GLM, PROC MEANS and PROC TABLE (SAS/STAT® User’s Guide. Version 9.0, 2002).

Symptoms and comorbidities

Association between COVID-19 gravity and common symptoms are presented in Figures 1 and 2. Fisher’s exact test showed an association between fever (p = 0.007), cough (p = 0.003), loss of smell (p = 0.024), sore throat (p = 0.016), headache (p = 0.023), body pain (p = 0.003), fatigue (p = 0.002) and dyspnoea (p < 0.001). Predominately, participants with higher gravity presented fever (87.5% critical and 77.8% severe), fatigue (100% severe and critical) and dyspnoea (100% moderate, severe and critical).

Association between COVID-19 severity and comorbidities are presented in Figure 2. Diabetes (p = 0.003), hypertension (p < 0.001) and metabolic syndrome (p = 0.010) were the comorbidities significantly associated for severe or critical symptoms compared with mild severity. Asthma was not significantly associated with COVID-19 gravity.

Figure 1.Association between COVID-19 gravity and common symptoms 

Figure 2.Association between COVID-19 gravity and different diseases 

Mild-term health sequelae

Table 2 (Supl.) provides outcomes on Body Composition, Physical Functioning and Cardiorespiratory status one month after recovery from COVID-19. Although all the groups showed an increased fat mass percentage above cut-off for healthy adults, people with critical symptoms reported a significant higher waist/hip ratio compared with mild (p = 0.017) and moderate severity (p = 0.049). Moderate and especially severe and critical people, showed a level of visceral fat highly above of cut-off for Brazilian adults. All of groups presented worst performance in agility and balance compared with cut off, showing severe and critical people more time compared with mild (p = 0.015; p = < 0.001, respectively) and moderate (p = 0.014; p = < 0.001, respectively) gravity. According to haematological indicators, critical gravity reported a significant higher level of glucose compared with mild (p = 0.037) and moderate COVID-19 (p = 0.046). In addition, mild, moderate, severe and critical people showed anomalous values of HDL-cholesterol compared with cut-off for healthy adults.

Figure 3 shows haematological status one month after recovery from COVID-19. The critical group presented a higher level of reticulocytes in comparison with mild (p = 0.037) and moderate COVID-19 (p = 0.034), and over the 84 uL (recommended cut-off). Also, the critical group presented a higher level of lymphocytes in comparison with mild (p = 0.043) and moderate (p = 0.015). Both groups were within normal values (< 4000 cm³).

Figure 3.Haematological status one month after recovery from COVID19 

The biochemical status is shown in Figure 4. Glucose levels were higher in the critical group compared to the moderate (p=0.046) and mild (p=0.037) groups. GOT concentration showed a difference between critical and moderate groups (p=0.042). Moreover, GPT concentration is lower in the critical group compared with severe (p=0.007) and moderate (p= 0.047) groups and higher when mild and severe groups are compared (p = 0.009).

Figure 4.Biochemical Status one month after recovery from COVID-19 

The level of inflammatory indicators and EPO values are shown in figure 5. No significant differences were found in the inflammatory cytokines. The severe and critical groups reported above the cut-off level of erythropoietin (>18.5 uL) and significantly different compared to mild (p = 0.031; p = 0.004, respectively) and moderate gravity (p = 0.043; p = 0.004; respectively).

Figure 5.Level of inflammatory indicators and EPO values 

Symptoms and comorbidities

Consistent with previous studies, AEROBICOVID participants presented fever, fatigue and dyspnoea as common symptoms of severe COVID-19 (9,12). The prevalence of dyspnoea was found to be relatively high in the most severe patients (9), a common characteristic of patients with moderate, severe and critical COVID-19. In fact, to have shortness of breath has been proposed by NIH of the United States of America as criteria to consider a higher gravity of disease (22,23). In survival analyses, comorbidities have been associated with COVID-19 gravity (34). According to previous studies, metabolic diseases such as diabetes, hypertension, or metabolic syndrome were the most common comorbidities associated with a higher gravity of the disease (35). On this way, patients with these comorbidities may represent a high-risk population for COVID-19. This population should be prioritized and taken into account by the public health system (34), as they are more susceptible to severe infection.

Mild-term health sequelae

Critical and severe infection have been linked to an overstated inflammatory process denominated “cytokine storm” (36) a coordinated innate immune response that acts on the first line of defence against COVID-19 (37). A great deal of evidence suggests that an acute inflammatory response is likely associated with COVID-19 severity and clinical outcomes (38–40). Increased cytokine levels have been found in COVID-19 participants during the acute infection phase (16,41), and are associated with a greater gravity of the disease (42). Among the long list of cytokines, IL-6 and TNF- $\alpha$ have been recognized to play a key role in the inflammation process induced by SARS-CoV-2 (18). Surprisingly, in the present study, critical participants showed a lower level of some biomarkers in the blood (as cytokines, GOT or GPT) even above the cut-off for healthy people. In this sense, the current anti-inflammatory drugs administered to fight against the virus could play a critical role in the progression of COVID-19 after the disease (43).

Besides leading risk factor, previous reports observed hyperglycemia at the time of presentation and following months after COVID-19 infection in participants without a prior diagnosis of diabetes (44–46). In the present study, glucose levels were maintained higher in the most severe participants compared with mild and moderate participants. Although this study did not examine physiology, previous studies that assessed the pathophysiological mechanism of hyperglycemia in acute and severe COVID-19 suggested that the severe systemic inflammation during the acute phase of infection, may damage the pancreatic beta cells (47) and produce adipose dysfunction (48), causing insulin resistance and insulin secretion dysregulated (49), even post-COVID-19.

Thus, as ACE2 insulin receptors are expressed in the liver, adipose tissue and skeletal muscle, different damages could occur in the body systems post-COVID-19 after overcoming the disease (15). Functional decline and reduced physical capacity were evident as agility-balance results compared with cut-off values in healthy adults (< 12 seconds) were found. Besides the above-mentioned mechanisms, the reduced work participation and regular daily routines (50), as declines in physical activity levels were reported in previous studies with patients recovered from acute respiratory distress syndrome (51), could be another important factor. In line with this argument, muscle weakness has been observed among individuals infected with SARS-CoV-2 (19,20) and is associated with poor functional capacity and long-term disability (21). Furthermore, in acute respiratory distress syndrome survivors, an expansion in the fat compartment (51,52), is often characterized by a greater rate of fat mass vs. lean mass (53). In the present study, patients who had experienced severe or critical SARS-CoV-2 infection showed an increased located fat in the trunk and visceral fat mass (54). Especially, in hospitalised patients (severe and critical), sedentary behaviours (as a consequence of larger recovery in hospital, quarantine and isolation period) may be a source of inactivity, causing a disproportioning accumulation in fat mass (15), that might further worsen body composition, functional status and cardiometabolic risk.

Altered haematological status has been shown even two months after the acute phase of infection (55). Considering that the red blood cells life average is estimated at 120 days (56) changes in blood cells could be detected even several months after SARS-CoV-2 infection (57). In addition, in terms of immunological analysis in recovery participants (follow-up of 4 weeks after discharge), anormal values of leukocytes, lymphocytes, erythrocytes and C-reactive protein have been found in participants with severe COVID-19 compared with non-severe (43). Among them, lymphocytes have been assigned a key role in regulating immune response to the virus that causes COVID-19 (43), and lymphopenia has been strongly associated with the issue gravity (41). Although all the groups presented normal values compared with the cut-off of lymphocytes, 4 weeks after discharge, high lymphocyte levels were observed in critical participants. These results are in line with previous findings where lymphocytes returned to normal values in convalescent patients (58).

Limitations should be considered when interpreting these findings. Firstly, the study was designed retrospectively, and baseline prior to infection were not available in the participants to unequivocally explain changes in plasma outcomes. Secondly, the sample size is limited, especially for severe and critical participants, and studies with larger sample sizes are strongly recommended. Therefore, the current literature includes the assessment of patients in specific regions or countries (more than 50% from China) different to Brazil, one of the most affected regions by the COVID-19 pandemic, which limits the generalizability of the findings. Despite limitations, to our knowledge, this is one of the first studies to describe mild-term health follow-up in Brazilian COVID-19 patients with different severity levels. Its strengths provide a measure of different clinical outcomes which could be used in all the fields of public health to improve the general health of COVID-19 survivors. Commonly, convalescent patients have been tested for specific antibodies or factors that could influence these antibodies. Still, as other clinical outcomes could be affected after discharge, the present study provides valuable insights into issues regarding post- COVID-19 sequelae.

Future study perspectives include analyzing the long-term sequelae in a larger sample and determining the effectivity of multidisciplinary therapies aimed at improving the parameters described above.

In conclusion, the most prevalent symptoms were fever, fatigue and dyspnoea, being diabetes, hypertension and metabolic syndrome, the comorbidities associated with higher gravity. In addition, the current descriptive study showed mild-term, altered values of body composition, physical functioning, enhanced glucose, reticulocytes and lymphocytes levels. Future studies are warranted to describe natural trajectories of COVID-19 recovery on clinical status and, thus, develop new therapies to decrease mild-term COVID-19 sequelae.