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. 2022 Aug 26;19(17):10644.
doi: 10.3390/ijerph191710644.

The Coronavirus Footprint on Dual-Task Performance in Post-Acute Patients after Severe COVID-19: A Future Challenge for Rehabilitation

Affiliations

The Coronavirus Footprint on Dual-Task Performance in Post-Acute Patients after Severe COVID-19: A Future Challenge for Rehabilitation

Marica Giardini et al. Int J Environ Res Public Health. .

Abstract

Recent studies suggest that also the non-critical form of COVID-19 infection may be associated with executive function impairments. However, it is not clear if they result from cognitive impairments or by COVID-19 infection per se. We aimed to investigate if patients in the post-acute stage of severe COVID-19 (PwCOVID), without manifest cognitive deficits, reveal impairments in performing dual-task (DT) activities compared to healthy controls (HS). We assessed balance in 31 PwCOVID vs. 30 age-matched HS by stabilometry and the Timed Up and Go (TUG) test with/without a cognitive DT. The DT cost (DTC), TUG test time and sway oscillations were recorded; correct cognitive responses (CCR) were calculated to evaluate cognitive performance. Results show a significant difference in overall DT performance between PwCOVID and HS in both stabilometry (p < 0.01) and the TUG test (p < 0.0005), although with similar DTCs. The main difference in the DTs between groups emerged in the CCR (effect size > 0.8). Substantially, PwCOVID gave priority to the motor task, leaving out the cognitive one, while HS performed both tasks simultaneously. Our findings suggest that PwCOVID, even without a manifest cognitive impairment, may present a deficit in executive function during DTs. These results encourage the use of DTs and CCR in PwCOVID.

Keywords: COVID-19; TUG test; balance assessment; dual-task; falls risk; healthy subjects; prevention; rehabilitation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Sway path and sway area in EO and EC conditions, for PwCOVID and HS, with the ST vs. DT. PwCOVID and HS differed, as did the ST versus the DT, considering both groups together (not shown in the figure), except for the sway area with EC. Statistical analysis was performed with ANOVA, applying Bonferroni’s correction. *, p < 0.01; ***, p < 0.0005. Abbreviations: ST, single-task; DT, dual-task; PwCOVID, people with COVID-19; HS, healthy subjects; EO, eyes open; EC, eyes closed; SE, standard error.
Figure 2
Figure 2
Relationship between CCR EO and CCR EC in PwCOVID and HS in stabilometric assessment. Subjects were instructed to count backwards in threes; number of total subtractions and errors were recorded to calculate each CCR, separately for each visual condition. Orange dots represent PwCOVID and blue dots HS. The relationship between CCR in the different visual conditions shows a linear correlation and the slopes of the fit line across each group are similar (orange and blue line for PwCOVID and HS, respectively). Abbreviations: PwCOVID, people with COVID-19; HS, healthy subjects; CCR, correct cognitive response; EO, eyes open; EC, eyes closed.
Figure 3
Figure 3
Mean time employed to perform the TUG test in ST and DT conditions. ANOVA showed a significant difference between the overall performance of PwCOVID and HS. ***, p < 0.0005. Abbreviations: PwCOVID, people with COVID-19; HS, healthy subjects; ST, single-task; DT, dual-task; TUG, Timed Up and Go; SE, standard error.

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