Burden of cytomegalovirus DNAemia among pediatric renal transplant patients on antiviral prophylaxis: A hospital‐based analysis
Bibliographic record
Abstract
INTRODUCTION: We examined the burden of CMV DNAemia and time to such events among renal transplant patients receiving CMV prophylaxis. We targeted the first year after transplantation, with the primary focus being on the first 3 months. METHODS: We conducted a retrospective review of renal transplant patients (<18 years) who were transplanted and followed at our center between January 2007, and December 2017. Clinical and laboratory data were obtained from the medical records and laboratory databases. RESULTS: Among 141 patients, the median age at transplant was 12.7 years (range 0.87-17.83 years). CMV DNAemia was detected in 33 of 77 patients eligible for prophylaxis (42.9%; 95% CI 31.6-54.6) during the first post-transplant year. Proportionately more D+R- patients were present among patients with DNAemia compared with those without DNAemia (15/38, 39.5% vs 16/103, 15.5%, P = .005). Median time to first positivity was 134 days (range 0-304 days). Eight patients had a positive PCR during the first 3 months (5.7% of all patients). Among those eligible for prophylaxis, 6.5% had DNAemia during the first 3 months while on prophylaxis. Among patients whose first positive PCR was after 3 months post-transplant, the median time to positivity was 52 days (range 13-214 days) after the end of prophylaxis. CONCLUSIONS: Breakthrough CMV DNAemia was documented among children receiving antiviral prophylaxis. While routine monitoring while on prophylaxis might not be warranted for the majority of patients, studies are needed to determine the optimal indications for CMV PCR testing while on prophylaxis.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".