BACKGROUND: Post-acute COVID-19 syndrome (PCS) is a multisystem disorder degrading the quality of life. The study determined characteristics and predictors of PCS in unvaccinated healthcare workers (HCWs) suffering from PCS based on a comparison with their fully recovered counterparts. METHODS: 305 HCWs were examined at least 12 weeks post COVID-19 symptom onset to obtain data about their acute phase of COVID-19 and current health status and tested for complete blood count, C-reactive protein (CRP), electrophoresis of plasma proteins and SARS-CoV-2-specific immunoglobulin (Ig) G and M. RESULTS: 181 (59.3%) HCWs reported persisting symptoms attributable to PCS during the examination and 124 (40.7%) HCWs stated no symptoms. In the entire sample, the mean CRP level slightly exceeded the normal range (6.63 mg/L, 95% confidence interval [CI] 5.96-7.3) while all other laboratory results were within the normal range. No statistically significant differences in laboratory results were revealed between both subgroups except for the mean Ig levels, which were higher in HCWs with PCS. The average number of symptoms of PCS was 1.9 (median 2). The most frequent symptoms of PCS were fatigue that interfered with daily life (47.5%), shortness of breath (38.1%), muscle or joint aches (16%), loss of smell (14.9%), headache (14.9%) and sleep disorders (11%). The only statistically significant predictors of PCS were female sex (odds ratio [OR] 1.48, 95% CI 1.059-2.067, p = .022) and increasing age (OR 1.04, 95% CI 1.01-1.07, p = .008). CONCLUSIONS: PCS appears to be a prevalent condition determined by female sex and increasing age.
- MeSH
- COVID-19 * epidemiologie MeSH
- kvalita života MeSH
- lidé MeSH
- postakutní syndrom COVID-19 MeSH
- SARS-CoV-2 MeSH
- zdravotnický personál MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: COVID-19 survivors may experience long-term health problems, including deterioration of cardiorespiratory fitness (CRF), as demonstrated by several cross-sectional studies that compared the results of cardiopulmonary exercise tests (CPET) performed only after COVID-19 with predicted values. This study aimed to analyze a change in CRF between repeated CPETs in response to suffered COVID-19. METHODS: A total of 127 healthcare workers (HCWs; mean age 55.7 years) underwent two CPETs with a mean interval of 762 days. Forty HCWs suffered from COVID-19 (mild to moderate severity) in the interim (321 days before the second CPET), and 87 HCWs formed a control group. Mixed-effects regression with multiple adjustment and interaction terms was used for two response variables - maximum oxygen uptake (VO2 max) and power output. RESULTS: Between both CPETs, mean VO2 max decreased statistically significantly in the COVID-19 subgroup (by 3.12 mL/kg/min, p = .034) and insignificantly in controls (by 0.56 mL/kg/min, p = .412). The proportion of HCWs achieving predicted VO2 max decreased from 75.9% to 59.5% (p = .161) in COVID-19 survivors, while it increased from 73.8% to 81% (p = .274) in controls. COVID-19 (β = -0.66, p = .014) and body mass index (β = -0.49, p < .001) were independent negative predictors of VO2 max change. COVID-19 was not associated with a change in power output. CONCLUSIONS: On the basis of repeated CPETs, COVID-19 significantly, albeit rather modestly, reduces CRF almost one year after infection. The reduction persists even after the acute phase with mild or moderate severity.
- Publikační typ
- abstrakt z konference MeSH
- Publikační typ
- abstrakt z konference MeSH
- Publikační typ
- abstrakt z konference MeSH
- Publikační typ
- abstrakt z konference MeSH
- Publikační typ
- abstrakt z konference MeSH
Analysing complex datasets while maintaining the interpretability and explainability of outcomes for clinicians and patients is challenging, not only in viral infections. These datasets often include a variety of heterogeneous clinical, demographic, laboratory, and personal data, and it is not a single factor but a combination of multiple factors that contribute to patient characterisation and host response. Therefore, multivariate approaches are needed to analyse these complex patient datasets, which are impossible to analyse with univariate comparisons (e.g., one immune cell subset versus one clinical factor). Using a SARS-CoV-2 infection as an example, we employed a patient similarity network (PSN) approach to assess the relationship between host immune factors and the clinical course of infection and performed visualisation and data interpretation. A PSN analysis of ~85 immunological (cellular and humoral) and ~70 clinical factors in 250 recruited patients with coronavirus disease (COVID-19) who were sampled four to eight weeks after a PCR-confirmed SARS-CoV-2 infection identified a minimal immune signature, as well as clinical and laboratory factors strongly associated with disease severity. Our study demonstrates the benefits of implementing multivariate network approaches to identify relevant factors and visualise their relationships in a SARS-CoV-2 infection, but the model is generally applicable to any complex dataset.
- MeSH
- COVID-19 * MeSH
- lidé MeSH
- protilátky virové MeSH
- SARS-CoV-2 * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Background and Objectives: Given the limited knowledge of antibody responses to COVID-19 and their determinants, we analyzed the relationship between the occurrence of acute-phase symptoms and infection-induced immunoglobulin (Ig) G seropositivity up to 8 months post-symptom onset. Materials and Methods: In this cross-sectional study, 661 middle-aged unvaccinated healthcare workers (HCWs) were interviewed about the presence of symptoms during the acute phase of their previously confirmed COVID-19 and were tested for specific IgG, targeting the spike protein (S1 and S2). The dependence of seropositivity on the symptom occurrence was explored through multiple logistic regression, adjusted for the interval between symptom onset and serology testing, and through classification and regression trees. Results: A total of 551 (83.4%) HCWs showed seropositivity and, inversely, 110 (16.6%) HCWs were seronegative. The chance of IgG seropositivity was increased by dyspnea (odds ratio (OR) 1.48, p < 0.001) and anosmia (OR 1.52, p = 0.021). Fever in HCWs with dyspnea resulted in the highest detected seropositivity rate, and anosmia in HCWs without dyspnea significantly increased the proportion of seropositivity. Conclusion: Clinical manifestation of the acute phase of COVID-19 predisposes to the development of infection-induced antibody responses. The findings can be applied for assessing the long-term protection by IgG, and thus, for creating effective surveillance strategies.
- MeSH
- anosmie MeSH
- COVID-19 * komplikace MeSH
- dyspnoe MeSH
- imunoglobulin G MeSH
- lidé středního věku MeSH
- lidé MeSH
- protilátky virové MeSH
- průřezové studie MeSH
- zdravotnický personál MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
The presence of neutralizing SARS-CoV-2-specific antibodies indicates protection against (re)infection, however, the knowledge of their long-term kinetics is limited. This study analyzed the presence of COVID-19-induced antibodies in unvaccinated healthcare workers (HCWs) over the period of 1-8 months post symptom onset (SO) and explored the determinants of persisting immunoglobulin (Ig) seropositivity. Six hundred sixty-two HCWs were interviewed for anamnestic data and tested for IgG targeting the spike protein (S1 and S2) and IgM targeting the receptor-binding domain. A Cox regression model was used to explore potential predictors of seropositivity with respect to the time lapse between SO and serology testing. 82.9% and 44.7% of HCWs demonstrated IgG and IgM seropositivity, respectively, with a mean interval of 83 days between SARS-CoV-2 detection and serology testing. On average, HCWs reported seven symptoms in the acute phase lasting 20 days. IgG seropositivity rates among HCWs decreased gradually to 80%, 50%, and 35% at 3, 6, and 8 months after SO, while IgM seropositivity fell rapidly to 60%, 15%, and 0% over the same time intervals. The number of symptoms was the only predictor of persisting IgG seropositivity (odds ratio [OR] 1.096, 95% confidence interval [CI] 1.003-1.199, p = 0.043) and symptom duration a predictor of IgM seropositivity (OR 1.011, 95% CI 1.004-1.017, p = 0.002). Infection-induced anti-SARS-CoV-2 IgG rates drop to a third in seropositive participants over the course of 8 months. Symptom count and duration in the acute phase of COVID-19 are both relevant to the subsequent kinetics of antibody responses.
- MeSH
- COVID-19 * diagnóza MeSH
- imunoglobulin G MeSH
- imunoglobulin M MeSH
- kinetika MeSH
- lidé MeSH
- protilátky virové MeSH
- průřezové studie MeSH
- SARS-CoV-2 MeSH
- zdravotnický personál MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Česká republika MeSH
