How post-infection status could lead to the increasing risks of chronic fatigue syndrome and the potential mechanisms: A 17-year population based Cohort study

Abstract:

Background: Serological studies have suggested that viruses and atypical pathogens are associated with CFS, but no study has focused on typical and common pathogens. This study aims to assess the association of infections with a variety of common pathogens with the risk of CFS and provide evidence for the hypothesis that infection triggers CFS.

Methods: The nested case-control study identified 2,000,000 adult patients from a nationwide population-based health insurance claims database from January 1, 2000, to December 31, 2017. Each case with a diagnosis of infection by pathogens was matched with one control using a propensity score. Patients with more than one potential pathogen, younger than 20 years old, or with a history of CFS or infection with certain pathogens before the index date were excluded. Univariate and multivariate Cox proportional hazard models were applied to estimate the HR, aHR, and corresponding 95% CI. The multivariate analysis had adjustments for age, sex, comorbidities, and medication confounders.

Results: A total of 395,811 cases with 1: 1 matched controls were included (58.2% female; mean age [standard deviation], 44.15 [17.02]). Among these, the aHR of the pathogen cohort was 1.5 (95% CI, 1.47 to 1.54). Pathogens were positively correlated with CFS, including influenza, candida and others.

Conclusion: The findings of this study demonstrate the association between CFS and infection with common pathogens, including bacteria, virus and fungi.

Source: Hsun Chang; Chien-Feng Kuo; Teng-Shun Yu; Liang-Yin Ke; Chung-Lieh Hung; Shin-Yi Tsai. How post-infection status could lead to the increasing risks of chronic fatigue syndrome and the potential mechanisms: A 17-year population based Cohort study. Research Square, August 30, 2023. https://assets.researchsquare.com/files/rs-3289981/v1/55890598-6f0d-4f73-a9f4-5349e07baac0.pdf (Full text)

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.