Neurotherapies for Long COVID: Rewiring Fatigue, Mental Health, and Quality of Life Through a Systematic Review and Network Meta-Analysis

Maria Sri Crishnatalia Wirodihardjo; Ardina Lukito Sampurno; Fauzan Ahmad Arkanokahfi Indrawan; Teresa Wulan Karenina; Tiffney Tyara Setyoko

doi:10.19166/lijn.v2i2.10397

著者

Maria Sri Crishnatalia Wirodihardjo Universitas Padjadjaran https://orcid.org/0009-0004-3514-0684
Ardina Lukito Sampurno Universitas Padjadjaran https://orcid.org/0009-0005-3397-8309
Fauzan Ahmad Arkanokahfi Indrawan Universitas Padjadjaran https://orcid.org/0009-0005-8508-5238
Teresa Wulan Karenina Universitas Padjadjaran https://orcid.org/0009-0003-1496-6949
Tiffney Tyara Setyoko Universitas Pelita Harapan https://orcid.org/0009-0008-1932-9988

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https://doi.org/10.19166/lijn.v2i2.10397

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Long COVID##common.commaListSeparator## Neurorehabilitation##common.commaListSeparator## Fatigue##common.commaListSeparator## Quality of Life##common.commaListSeparator## Network Meta-Analysis##common.commaListSeparator## Non-Pharmacological Therapy

要旨

Introduction: Long COVID affects nearly 36% of post-infected individuals worldwide, many of whom experience persistent neurological symptoms such as fatigue, cognitive impairment, and mood disorders. Despite growing recognition of this condition, the most effective nonpharmacological strategies remain unclear. This study aimed to determine optimal neurotherapy to improve fatigue, mental health, and quality of life (QoL) in Long COVID patients.

Methods: A systematic review of a network meta-analysis was conducted following the PRISMA NMA guidelines. Literature searches were made using Pubmed, EBSCOhost, Wiley, and Scopus up to May 2025. Randomized controlled trials (RCT) were included with patients suffering from long COVID and treated with non-pharmacological therapy. Standard mean differences (SMD) were calculated using a frequentist approach, and treatments were ranked using the Surface under the Cumulative Ranking Curve (SUCRA). Risk of bias and certainty of evidence were assessed using the Cochrane RoB-2 and GRADE framework.

Results: Fourteen RCTs including 1,309 participants were included in the analysis. Affective and cognitive integrated therapy achieved the greatest result of decreased fatigue severity (SMD = –5.01, 95% CI –6.38 to –3.65). Multimodal therapies combining aerobic training, strength conditioning, respiratory neuroplasticity training and telerehabilitation improved QoL (SMD = 7.55, 95% CI 5.14 to 9.95). The mental health data remained insignificant due to the data being heterogeneous and publication bias.

Conclusions: Affective and Cognitive Integration and multimodal rehabilitation show potential for providing relief for fatigue and enhancing QoL in Long COVID patients. However, further standardized and longitudinal studies are needed to understand their effects on mental health.

Keywords: Long COVID, Neurorehabilitation, Fatigue, Quality of Life, Network Meta-Analysis, Non-pharmacological Therapy

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