Direct molecular detection of a broad range of bacterial and viral organisms and Streptococcus pneumoniae vaccine serotypes in children with otitis media with effusion
Bibliographic record
Abstract
BACKGROUND: Otitis media with effusion (OME) causes significant morbidity in children, but the causes of OME and methods for prevention are unclear. To look for potential infectious etiologies, we performed a pilot study using multiple-target real-time polymerase chain reaction (qPCR) for 27 infectious agents, including nine bacterial organisms and 18 respiratory viruses in middle ear fluids (MEFs) from children with OME. QPCR was also performed for the 13 Streptococcus pneumoniae serotypes contained in the current vaccine. RESULTS: Forty-eight MEF samples were obtained and qPCR detected bacterial nucleic acid (NA) in 39/48 (81%) and viral NA in 7/48 (15%). Alloiococcus otitidis and S. pneumoniae were both detected in 15/48 (31%) MEFs, followed by M. catarrhalis in 14/48 (29%), H. influenzae in 5/48 (10%) and M. pneumoniae in 4/48 (8%). Rhinoviruses were most common virus type detected, found in 4/48 (8%) MEFs. Serotypes included in the current 13-serotype vaccine were detected in only 3/15 (20%) S. pneumoniae qPCR-positive MEFs. CONCLUSIONS: Bacteria may play an important role in OME, since over 80% of MEFs contained bacterial NA. Further research into the role of A. otitidis in OME will be helpful. Serotypes of S. pneumoniae not included in the current 13-serotype vaccine may be involved in OME. Larger studies of OME S. pneumoniae serotypes are needed to help determine which additional serotypes should be included in future vaccine formulations in order to try to prevent OME.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".