Evaluation of the Japanese Respiratory Society guidelines for the identification of <i>Mycoplasma pneumoniae</i> pneumonia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality worldwide. Mycoplasma pneumoniae is one of the major causative pathogens of CAP. Early diagnosis of M. pneumoniae pneumonia is crucial for initiating appropriate antibiotic therapy. The aim of this study was to determine whether the Japanese Respiratory Society (JRS) guidelines on CAP are effective for diagnosing M. pneumoniae pneumonia. METHODS: Between August 2008 and July 2009, adult outpatients with CAP were consecutively enrolled. The aetiology of CAP was determined by culture and real-time polymerase chain reaction (PCR) methods to detect M. pneumoniae, urine antigen tests to detect Streptococcus pneumoniae and Legionella pneumoniae, blood and sputum culture for bacteria and real-time PCR for eight common respiratory viruses. The predictive value of the JRS guidelines for differentiating M. pneumoniae pneumonia from typical bacterial and viral pneumonias was determined. RESULTS: Data from 215 adult CAP outpatients was analyzed. An aetiological diagnosis was made for 105 patients (48.8%), including 62 patients with M. pneumoniae pneumonia, 17 patients with typical bacterial pneumonia and 23 patients with viral pneumonia. According to the JRS criteria for differential diagnosis of atypical pneumonia, 55 of 62 patients were correctly diagnosed with M. pneumoniae pneumonia (sensitivity 88.7%), and 31 of 40 patients with bacterial and viral pneumonia were correctly excluded (specificity 77.5%). CONCLUSIONS: The JRS guidelines on CAP provide a useful tool for the identification of M. pneumoniae pneumonia cases and differentiating these from cases of typical bacterial or viral pneumonia.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".