The effect of late‐onset CMV infection on the outcome of renal allograft considering initial graft function
Bibliographic record
Abstract
BACKGROUND: Delayed graft function (DGF) increases the renal allograft failure risk. Late-onset Cytomegalovirus (CMV) infection's effect on the association between DGF and allograft failure has not been determined. METHODS: In this retrospective cohort, we included all renal allograft recipients at London Health Sciences Centre from January 1, 2014 to December 30, 2017, and continued clinical follow-up until February 28, 2020. We determined whether late-onset CMV infection affects the association between DGF and allograft failure in stratified and Cox proportional hazard analyses. RESULTS: Of 384 patients (median age [interquartile range]: 55 [43.3-63]; 38.7% female), 57 recipients (14.8%) were diagnosed with DGF. Patients with DGF were at a greater risk of CMV infection than patients without DGF (22.8% vs. 11.3%, p = .017). Late-onset CMV infection (odds ratio [OR]: 4.7, 95% CI: 2.07-10.68) and rejection (OR: 9.59, 95% CI: 4.15-22.16) significantly increased the risk of allograft failure in recipients with DGF. Patients with DGF had a significantly greater risk of graft failure than those without DGF (17.5% vs. 6.1%, p = .007). In the adjusted Cox hazard model, CMV infection significantly increased the risk of allograft failure (aHR: 3.19, 95% CI: 1.49-6.84). CONCLUSION: Late-onset CMV infection considerably increased the risk of graft failure in patients with DGF. A hybrid preventive model including prophylaxis followed by CMV-specific cell-mediated immunity monitoring may decrease the risk of allograft failure in recipients with DGF.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".