The Relationship Between Respiratory Viral Loads and Diagnosis in Children Presenting to a Pediatric Hospital Emergency Department
Bibliographic record
Abstract
BACKGROUND: respiratory viral infections account for a considerable proportion of pediatric emergency room visits. Illnesses range in severity from mild upper respiratory tract infections to serious lower respiratory tract infections (LRTI). The relationship between viral load and specific viruses to clinical diagnosis made by physicians in this setting is poorly understood. METHODS: we applied a real-time, quantitative polymerase chain reaction (qPCR) panel for 13 common respiratory viruses to 195 frozen, archival nasopharyngeal aspirate specimens obtained from symptomatic children ≤ 4 months of age presenting to the emergency room. Mean total viral load and number of viruses per archival nasopharyngeal aspirate specimen were compared between LRTI (n = 70) and non-LRTI (1 or more of upper respiratory tract infection, fever, or cough) (n = 125), as were yield and concordance of qPCR results to viral culture/direct fluorescence assay (DFA). RESULTS: children with LRTI had significantly increased total viral load and harbored more viruses than the non-LRTI group. Respiratory syncytial virus-A and -B were significantly associated with LRTI, and parainfluenza virus-1 with non-LRTI. Individual loads of parainfluenza virus-2 and human rhinovirus were increased in LRTI versus non-LRTI. Quantitative PCR yielded more viruses (including coinfections, where a "dominant virus" was typically identified) than viral culture/DFA and documented nucleic acid from pathogens not tested by culture/DFA including human rhinovirus; coronaviruses -OC43, -229E, and -NL63; and metapneumovirus. CONCLUSIONS: in symptomatic children presenting to the emergency room, total viral load is related to clinical diagnosis; specific viruses are associated with particular clinical diagnoses, and qPCR has a higher yield than other viral diagnostic methods.
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".