Predictors and characteristics of post-acute COVID-19 syndrome in healthcare workers

Abstract

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.

Keywords:

• COVID-19
• post-acute COVID-19 syndrome
• symptom
• predictor
• C-reactive protein
• blood count
• immunoglobulin

Acknowledgements

The authors would like to thank all workers whose dedicated activity enabled this study.

Author contributions

L.Š. (Ladislav Štěpánek): Conceptualisation, methodology, writing—original draft. M.N.: Conceptualisation, supervision. M.J.: Formal analysis, data curation. L.Š. (Lubomír Štěpánek): Methodology, formal analysis. A.B.: Data curation, writing – review & editing. K.K.: Data curation, project administration.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The study was supported by the Palacký University Fund under grant IGA_LF_UP_2022_005.