Cytomegalovirus infection post‐pancreas–kidney transplantation – results of antiviral prophylaxis in high‐risk patients
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is a major pathogen affecting solid organ transplant (SOT) recipients. Prophylactic strategies have decreased the rate of CMV infection/disease among SOT. However, data on the effect of current prophylactic strategies for simultaneous pancreas-kidney (SPK) or pancreas after kidney (PAK) transplant remain limited. We report our experience of CMV prophylaxis in SPK/PAK recipients. METHODS: A total of 130 post-SPK/PAK patients were analyzed retrospectively for the rate of CMV and the risk factors associated with the acquisition of CMV. All patients received antiviral prophylaxis. The follow-up period was one yr post-transplant or until death. RESULTS: The rate of CMV post-SPK/PAK transplant was 24%, 44%, and 8.2% among the whole cohort, the D+/R- and the R+ groups, respectively. Median time of prophylaxis was 49 (0-254) d. In the whole cohort, risk factors for CMV infection/diseases were D+/R- CMV status (odds ratio [OR] = 16.075), preceding non-CMV (infection caused by bacteria or fungi and other viruses) infection (OR = 6.362) and the duration of prophylaxis (OR = 0.984). Among the CMV D+/R- group, non-CMV infection was the only risk factor for CMV disease (OR = 10.7). CONCLUSIONS: Forty-four per cent (25/57) of the D+/R- recipients developed CMV infection/disease despite CMV prophylaxis. Current CMV prophylaxis failed to prevent CMV infection/disease in this group of patients.
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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".