Induced sputum as an adequate clinical specimen for the etiological diagnosis of community-acquired pneumonia (CAP) in children and adolescents
Bibliographic record
Abstract
OBJECTIVES: This study aimed to evaluate the utility of induced sputum (IS) for the diagnosis of community-acquired pneumonia (CAP) in pediatric population. METHODS: This cross-sectional study included pediatric population aged between 1 month and 17 years who were hospitalized with a diagnosis of CAP in 13 hospitals in Colombia, in whom an IS sample was obtained. Gram staining, aerobic bacterial and mycobacterial culture tests, and polymerase chain reaction (PCR) for 6 atypical bacteria and 15 respiratory viruses were performed. We evaluated the quality of IS samples. RESULTS: IS samples were collected in 516 of 525 children included in this study. The median age was 32 months, 38.6% were younger than 2 years, and 40.9% were between 2 and 5 years. Two patients had transient hypoxemia during the procedure. The quality of the IS obtained was good in 48.4% and intermediate in 24.5%. Identification of a respiratory pathogen was achieved with an IS sample (with Gram staining, culture test, and PCR) in 372 of 516 children with CAP. CONCLUSION: Our study shows that IS is an adequate sample for the diagnosis of CAP in pediatric population that required hospitalization. The procedure was safe, well tolerated, and with better diagnostic yields compared with the rest of the samples obtained.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".