Cytomegalovirus DNAemia in Hospitalized Adults With SARS-CoV-2 Infection Requiring Supplemental Oxygen: Virologic and Clinical Characteristics and Association With Outcomes
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) reactivation occurs in the context of coronavirus disease 2019 (COVID-19); however, the viral kinetics, risk factors, and clinical outcomes are poorly defined. METHODS: We examined the association of CMV DNAemia with clinical outcomes among participants of a randomized trial of remdesivir with or without baricitinib (National Institute of Allergy and Infectious Diseases [NIAID], Adaptive COVID-19 Treatment Trial 2 [ACTT-2]). Plasma CMV DNAemia from CMV-seropositive participants with COVID-19 (NIAID ordinal scale [OS] 5, 6, or 7 at entry) were assessed longitudinally by quantitative polymerase chain reaction. Factors associated with CMV DNAemia, and clinical outcomes were analyzed by Cox regression and proportional odds models. RESULTS: Of 772 trial participants with available samples, 643 (83%) were CMV seropositive. Baseline CMV serostatus was not associated with COVID-19 outcomes. The cumulative incidence of CMV DNAemia among seropositive persons by day 28 was overall 11% (baseline OS 5, 6.3%; OS 6, 16.4%; OS 7, 24.7%), and was associated with older age, baseline OS, male sex, lymphopenia, and systemic corticosteroid use, while remdesivir and baricitinib did not affect risk. CMV DNAemia was associated with a lower probability of improvement by day 29 (adjusted hazard ratio, 0.3 [95% confidence interval, .17-.56]), with a more pronounced delay of recovery with higher CMV viral load. CMV DNAemia was also associated with higher severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and death. CONCLUSIONS: In hospitalized adults with COVID-19 requiring oxygen, CMV viremia occurs within well-defined clinical risks and is independently associated with delayed recovery from illness, higher SARS-CoV-2 viral load, and increased mortality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".