Sensitivity of Rapid Influenza Diagnostic Testing for Swine-Origin 2009 A (H1N1) Influenza Virus in Children
Bibliographic record
Abstract
BACKGROUND: The rapidly evolving pandemic of novel 2009 swine-origin influenza A (H1N1) virus (S-OIV) demands that accurate and practical diagnostics be urgently evaluated for their potential clinical utility. OBJECTIVE: To determine the diagnostic accuracy of a rapid influenza diagnostic test (RIDT) and direct fluorescent antibody (DFA) assay for S-OIV by using reverse-transcription polymerase chain reaction (RT-PCR) as the reference standard. METHODS: We prospectively recruited children (aged 0-17 years) assessed in the emergency department of a pediatric referral hospital and a community pediatric clinic for influenza-like illness between May 22 and July 25, 2009. RIDT (performed on-site) and DFA were compared with RT-PCR to determine their sensitivity and specificity for S-OIV. We also compared the sensitivity of RIDT for S-OIV to that for seasonal influenza over 2 preceding seasons. RESULTS: Of 820 children enrolled, 651 were from the emergency department and 169 were from the clinic. RIDT sensitivity was 62% (95% confidence interval [CI]: 52%-70%) for S-OIV, with a specificity of 99% (95% CI: 92%-100%). DFA sensitivity was 83% (95% CI: 75%-89%) and was superior to that of RIDT (P < .001). RIDT sensitivity for S-OIV was comparable to that for seasonal influenza when using DFA supplemented with culture as the reference standard. RIDT sensitivity for influenza viruses was significantly higher in children 5 years of age or younger (P = .003) and in patients presenting < or =2 days after symptom onset (P < .001). CONCLUSIONS: The sensitivity of RIDT for detection of S-OIV is higher than recently reported in mixed adult-pediatric populations but remains suboptimal.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".