ME/CFS, case definition, and serological response to Epstein-Barr virus. A systematic literature review
Bibliographic record
Abstract
Background: The levels of antibodies to Epstein–Barr virus (EBV) in patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) have been compared to healthy controls in many studies. However, the results are inconsistent.Purpose: The objective of this systematic literature review was to determine whether differences in EBV serology between ME/CFS patients and controls vary with the case definition that is used.Methods: MEDLINE, EMBASE, and earlier reviews were searched for studies in which the serum levels of antibodies to EBV-antigens in ME/CFS patients were compared with those in persons without ME/CFS.Results: 27 studies were identified. The levels of antibodies to EBV in ME/CFS patients differed from those in controls in 14 studies. The differences in EBV serology that were revealed, were almost exclusively signs that may indicate higher EBV activity in the patient group. The serological differences between patients and controls were seen in the 2 studies in which ME/CFS was defined using the Canadian criteria, in 5 of the 9 studies using the Holmes criteria, in 1 of the 2 studies using modified Holmes criteria, in 2 of the 6 studies using the Fukuda criteria, and in 4 of the 7 studies using less known criteria. The single study using the Oxford criteria, showed no difference between cases and controls.Conclusions: There seems to be increased EBV activity in subset(s) of ME/CFS patients. The data do not allow firm conclusions about EBV antibody levels varying with the illness case definition used.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".