Cytomegalovirus (CMV) Prevention in Pediatric Solid Organ Transplant Recipients.
Bibliographic record
Abstract
Purpose: We determined the incidence of CMV DNAemia (CMVv) and CMV disease (CMVd) in pediatric solid organ transplant (SOT) recipients according to risk status and type of prevention therapy. Methods: 218 SOT transplants in 190 pediatric patients performed between 2004-2010 were reviewed. Standardized protocols directed CMV prevention using either universal prophylaxis, pre-emptive therapy or clinical follow up alone based on CMV risk stratification (classified by donor(D)-recipient(R) pre-transplant CMV serology, organ type and anti-lymphocyte antibody use). The incidence of CMVv and CMVd in CMV risk groups (high D+R- (HR), medium D+R+/D-R+(MR), low D-R-(LR)), was determined. Kaplan-Meier analysis was used to determine time to CMVv. Results: Number of SOTs and median days of follow-up were: heart (81; 1317), multivisceral (3; 582), liver (102; 1273), kidney (28; 1678), and lung (4; 1058). Age ranged from 0-17yrs with median age for each organ type respectively 1.5, 1, 1.6, 11 and 9.2 years. Twelve transplants lasting ≤14 days were excluded. Of the remaining 206, 71 were HR, 65 were MR and 70 were LR. 137 received prophylaxis, 48 preemptive therapy and 21 had clinical follow up. 37/137 in the prophylactic group, 12/48 in the preemptive group and 0/21 in the clinical follow up group developed CMVv. Incidence of CMVv based on risk status is outlined in the following figure. CMVd occurred in 8 patients, details in the following table.Figure: No Caption available.Table: No Caption available.Conclusions: The CMV prevention strategies used in our population resulted in a high incidence of CMVv (24%) but rates of CMVd (3.8%) remained low. This study lays the groundwork for further analysis of the causes of breakthrough disease and the development of improved strategies to mitigate these prevention failures.
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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 | 0.000 | 0.001 |
| 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".