Human Parechovirus Central Nervous System Infections in Southern California Children
Bibliographic record
Abstract
BACKGROUND: Human parechoviruses (hPeV) are increasingly recognized as significant etiological agents for meningoencephalitis especially in young children, but testing of cerebrospinal fluid (CSF) for hPeV by PCR is not routinely performed. METHODS: We used real-time reverse transcriptase PCR for detection of serotypes 1-6 in CSF samples of 440 children who underwent a lumbar puncture to exclude an infectious etiology of their clinical presentation. We then compared the prevalence and clinical presentation of children with hPeV-positive CSF with that of children with enterovirus (EV)-positive CSF. RESULTS: HPeV was detected in 2.7% and EV in 10.7% of CSF samples. Many hPeV-positive patients were <3 months of age and usually had CSF parameters within the age-adjusted normal range. However, children with hPeV-positive CSF presented with neurologic symptoms more frequently than those with EV-positive CSF. CONCLUSIONS: HPeV infections of the central nervous system occurred mainly in young infants and were more commonly associated with neurologic symptoms at presentation, despite the fact that CSF findings were within the normal range in the vast majority of these cases. HPeV should be included in the differential diagnosis of young children with central nervous system symptoms and sepsis-like illness, even in the presence of normal CSF parameters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".