Transfusion-Transmitted Dengue and Associated Clinical Symptoms During the 2012 Epidemic in Brazil
Bibliographic record
Abstract
BACKGROUND: A linked donor-recipient study was conducted during epidemics in 2 cities in Brazil to investigate transfusion-transmitted (TT) dengue virus (DENV) by DENV RNA-positive donations. METHODS: During February-June 2012, samples were collected from donors and recipients and retrospectively tested for DENV RNA by transcription-mediated amplification. Recipient chart review, using a case (DENV positive)-control (DENV negative and not known to be exposed) design, was conducted to assess symptoms. RESULTS: Of 39 134 recruited blood donors, DENV-4 viremia was confirmed in 0.51% of donations from subjects in Rio de Janeiro and 0.80% of subjects in Recife. Overall, 42 DENV RNA-positive units were transfused into 35 recipients. Of these, 16 RNA-positive units transfused into 16 susceptible recipients were identified as informative: 5 cases were considered probable TT cases, 1 possible TT case, and 10 nontransmissions. The TT rate was 37.5% (95% confidence interval [CI], 15.2%-64.6%), significantly higher than the viremia rate of 0.93% (95% CI, .11%-3.34%) in nonexposed recipients (P < .0001). Chart review did not find significant differences between cases and controls in symptoms or mortality. CONCLUSIONS: During a large epidemic of DENV-4 infection in Brazil, >0.5% of donations were RNA positive, and approximately one third of components resulted in TT. However, no significant clinical differences were evident between RNA-positive and RNA-negative recipients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 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".