Autoantibodies in COVID-19 survivors with post-COVID symptoms: a systematic review
Bibliographic record
Abstract
Objective: The long-lasting persistence of autoantibodies stands as one of the hypotheses explaining the multisystemic manifestations seen in individuals with post-COVID-19 condition. The current review offers restricted insights into the persistence of autoantibodies in plasma/serum in people with post-COVID symptoms. Methods: , 2024. Papers investigating the presence of autoantibodies in plasma/serum samples in people with post-COVID symptoms were included. The Newcastle-Ottawa Scale (NOS) was used to assess methodological quality. Results: From 162 identified records, five articles met all inclusion criteria; four studies included infected controls with no post-COVID symptoms whereas all five studies included non-infected controls (410 COVID-19 survivors with post-COVID symptoms, 223 COVID-19 survivors with no post-COVID symptoms as controls and 266 non-infected healthy controls). Four studies concluded that the presence of autoantibodies had a potential (but small) role in post-COVID-19 condition whereas one study concluded that autoantibodies were not associated. Quality assessment showed all studies had high methodological quality. Conclusion: Although evidence suggests that persistent autoantibodies can be associated with post-COVID symptoms, the clinical relevance of their presence seems modest at this stage. Current results highlight further research to clarify the role of autoantibodies in the development of post-COVID symptoms, guiding the development of tailored diagnostic and treatment approaches to enhance patient outcomes. Systematic review registration: https://osf.io/vqz28.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".