A Seroprevalence Study of West Nile Virus Infection in Solid Organ Transplant Recipients
Bibliographic record
Abstract
West Nile virus (WNV) causes severe neurological disease in less than 1% of infections. However, meningoencephalitis may be more common in immunosuppressed transplant patients. In 2002, a WNV outbreak occurred in our region. To determine the spectrum of disease of community acquired WNV infection and assess public health behavior patterns in transplant recipients, we carried out a seroprevalence study. Patients were enrolled from outpatient transplant clinics in October 2002 and sera were screened for WNV. Questionnaires about WNV were provided to patients. Eight hundred sixteen organ transplant patients were enrolled. The seroprevalence of WNV IgM was 2/816 (0.25%; 95% CI 0.03-0.88%). By extrapolation to our entire transplant population of 2360 patients, and using data from hospital-based surveillance, the risk of meningoencephalitis in a transplant patient infected with WNV is estimated to be 40% (95% CI 16-80%). With regards to knowledge and behavior, 56% patients knew of and 47% used at least one protective measure against WNV. Only 33% used insect repellent. The risk of meningoencephalitis in transplant recipients is much higher than in the general population. There is incomplete knowledge and poor rates of compliance amongst patients with regards to WNV prevention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".