Hemolytic Anemia Linked to Epstein–Barr Virus Infectious Mononucleosis: A Systematic Review of the Literature
Bibliographic record
Abstract
Background: In Epstein–Barr virus infectious mononucleosis, hemolytic anemia occasionally occurs. Methods: To characterize hemolytic anemia linked to Epstein–Barr virus infectious mononucleosis, we performed a systematic review (PROSPERO CRD42024597183) in the United States National Library of Medicine, Excerpta Medica, and Web of Science with no restrictions on language. Only reports published since 1970 were included. Eligible were reports describing hemolytic anemia in subjects with clinical signs and microbiological markers of Epstein–Barr virus mononucleosis. Results: In the literature, we detected 56 reports released between 1973 and 2024, documenting 60 individuals (32 females and 28 males; 27 children and 33 adults) with hemolytic anemia linked to Epstein–Barr virus infectious mononucleosis. The mechanism underlying anemia was categorized as cold-antibody-mediated (N = 31; 52%), warm-antibody-mediated (N = 18, 30%), mixed warm- and cold-antibody-mediated (N = 4; 6.7%), or paroxysmal cold hemoglobinuria (N = 2; 3.3%). The remaining 5 cases (8.3%) remained unclassified. Observation alone was the chosen approach in 23% of cases (N = 14). Steroids (67%; N = 40) and blood transfusions (38%; N = 23) were the most commonly used treatment, while plasma exchange, intravenous polyclonal immunoglobulin, rituximab, and splenectomy were used less frequently. Observation was slightly but significantly (p = 0.032) more common in cases of cold-antibody-mediated anemia compared to all other cases combined. Patients recovered a median of 28 [interquartile range 21–39] days after disease onset. Two patients with warm-antibody-mediated hemolytic anemia died. Conclusions: This literature review points out that Epstein–Barr virus, like Mycoplasma pneumoniae, cytomegalovirus, or severe acute respiratory syndrome coronavirus 2, may act as a trigger for immune-mediated hemolytic anemia.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".