Epstein Barr Virus Reactivation during COVID-19 Hospitalization Significantly Increased Mortality/Death in SARS-CoV-2(+)/EBV(+) than SARS-CoV-2(+)/EBV(−) Patients: A Comparative Meta-Analysis
Bibliographic record
Abstract
Epstein–Barr virus (EBV) reactivation in acute-phase of COVID-19 disease was recently discovered but it is not clear in terms of degree of mortality caused, and this was the aim of the current study. Six databases and three non‐databases were thoroughly searched, independently. The articles related to non‐human study (abstract, in vitro, in vivo, in silico, case study, poster, and review articles) were excluded for main analysis. Four articles related to mortality linked to EBV reactivation were systematically identified and included in the qualitative and quantitative analyses. Based on proportional meta-analysis of 4 studies, 34.3% or 0.343 (95% CI: 0.189–0.516; I2 = 74.6) mortality related to EBV reactivation was identified. To address high heterogeneity, subgroup meta-analysis was carried out. Based on subgroup analysis, 26.6% or 0.266 (95% CI: 0.191–0.348; I2 = 0) with no heterogeneity was identified. Interestingly, in comparative meta-analysis, EBV(−)/SARS-CoV-2(+) patients had statistically lesser mortality (9.9%) than EBV(+)/SARS-CoV-2(+) patients (23.6%) where RR = 2.31 (95% CI: 1.34–3.99; <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>p</a:mi> <a:mo>=</a:mo> <a:mn>0.003</a:mn> </a:math> ; I2 = 6%). This finding is equivalent to the absolute mortality effect of 130 more per 1000 COVID-19 patients (95% CI: 34–296). Furthermore, based on statistical analysis, D-dimer was not statistically significantly different ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>p</c:mi> <c:mo>></c:mo> <c:mn>0.05</c:mn> </c:math> ) between the groups although studies have shown that D-dimer was statistically significantly different ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>p</e:mi> <e:mo><</e:mo> <e:mn>0.05</e:mn> </e:math> ) between these groups. Based on the inclusion and analysis of low risk of bias and high quality of articles graded with Newcastle–Ottawa Scale (NOS), when COVID-19 patients’ health state is gradually worsening, EBV reactivation needs to be suspected because EBV reactivation is a possible marker for COVID-19 disease severity.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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; a candidate call from one teacher head, 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".