Background: Long COVID has been increasingly linked to persistent clinical manifestations, including chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME). However, the relationship between this syndrome and pre-existing conditions such as bipolar spectrum disorders and hypothyroidism is not yet clearly established. These disorders may influence the regulation of biorhythms and immune function, suggesting a possible role in the predisposition to the development of CFS/ME in the context of long-term COVID-19. Objectives: This study investigates the prevalence of hypothyroidism and bipolar spectrum disorders in patients with CFS/ME associated with long-term COVID-19. It compares it with pre-pandemic population data to determine whether these conditions may be predisposing factors. Methods: A case–control design was used to select cases from a clinical trial on CFS/ME in long COVID, while controls were extracted from pre-COVID epidemiological databases. Comparative statistical analyses, including chi-square tests and analysis of variance (ANOVA), were performed to assess significant differences in the frequency of these conditions between both groups. Results: The clinical sample showed significantly higher prevalence rates of hypothyroidism [27.78% vs. 1.14%; odds ratio (OR) = 33.07; 95% confidence interval (CI): 7.10–153.70] and bipolar spectrum disorders (16.67% vs. 0.2%; OR = 138.4; 95% CI: 36.40–526.43) compared to control populations (p < 0.0001 for both). Similarly, individuals screening positive for depressive symptoms (PHQ9 > 9) showed markedly increased odds (55.5% vs. 4.16%; OR = 28.75; 95% CI: 6.52–126.73). Conclusion: The findings suggest that hypothyroidism and bipolar spectrum disorders may act as predisposing factors in the development of CFS/ME in long-term COVID-19. Identifying these clinical antecedents could facilitate early detection and the development of targeted intervention strategies in at-risk populations.
Bipolar spectrum, hypothyroidism, and their association with chronic fatigue/myalgic encephalomyelitis-like syndrome in long COVID: could they be identified as early determinants?
Tusconi, Massimo;Aviles Gonzalez, Cesar Ivan;Barrui, Vanessa;Fornaro, Michele;Carta, Mauro Giovanni;Cossu, Giulia
2025-01-01
Abstract
Background: Long COVID has been increasingly linked to persistent clinical manifestations, including chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME). However, the relationship between this syndrome and pre-existing conditions such as bipolar spectrum disorders and hypothyroidism is not yet clearly established. These disorders may influence the regulation of biorhythms and immune function, suggesting a possible role in the predisposition to the development of CFS/ME in the context of long-term COVID-19. Objectives: This study investigates the prevalence of hypothyroidism and bipolar spectrum disorders in patients with CFS/ME associated with long-term COVID-19. It compares it with pre-pandemic population data to determine whether these conditions may be predisposing factors. Methods: A case–control design was used to select cases from a clinical trial on CFS/ME in long COVID, while controls were extracted from pre-COVID epidemiological databases. Comparative statistical analyses, including chi-square tests and analysis of variance (ANOVA), were performed to assess significant differences in the frequency of these conditions between both groups. Results: The clinical sample showed significantly higher prevalence rates of hypothyroidism [27.78% vs. 1.14%; odds ratio (OR) = 33.07; 95% confidence interval (CI): 7.10–153.70] and bipolar spectrum disorders (16.67% vs. 0.2%; OR = 138.4; 95% CI: 36.40–526.43) compared to control populations (p < 0.0001 for both). Similarly, individuals screening positive for depressive symptoms (PHQ9 > 9) showed markedly increased odds (55.5% vs. 4.16%; OR = 28.75; 95% CI: 6.52–126.73). Conclusion: The findings suggest that hypothyroidism and bipolar spectrum disorders may act as predisposing factors in the development of CFS/ME in long-term COVID-19. Identifying these clinical antecedents could facilitate early detection and the development of targeted intervention strategies in at-risk populations.| File | Dimensione | Formato | |
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