Screening for West Nile Virus in Organ Transplantation: A Medical Decision Analysis
Bibliographic record
Abstract
The Organ Procurement and Transplant Network (OPTN) has recently announced that screening for West Nile Virus (WNV) in deceased organ donors is not recommended at this time. The purpose of this report was to examine the impact of this recommendation by using medical decision analysis. Without screening the rate of disease transmission was assumed to be the same as in donated blood with a case fatality rate of 25%. With screening we assumed the baseline screening test specificity and sensitivity to be 99.5% and 95%, respectively. The analysis was confined to heart, liver and kidney recipients. Survival probabilities and transplant rates were taken from UNOS. Annual screening could result in the loss of potentially 452.4 life years (113.8 for heart, 272.6 for liver and 66.0 for kidney). Most positive test results would be false-positive. Screening would be preferable for kidney donors in areas of high disease prevalence and high test specificity. However, for heart and liver most scenarios were associated with a net loss of life with screening, except if patients were stable on the wait list with particularly high case fatality rates from WNV. Current recommendations by OPTN that screening is not mandatory seem appropriate until further data are available.
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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 | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".