Community-acquired necrotizing pneumonia due to methicillin-sensitive Staphylococcus aureus secreting Panton-Valentine leukocidin: a review of case reports
Bibliographic record
Abstract
BACKGROUND: Community-acquired necrotizing pneumonia caused by Panton-Valentine leukocidin (PVL)-secreting Staphylococcus aureus is a highly lethal infection that mainly affects healthy children and young adults. Both methicillin-sensitive S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA) may carry the PVL-phage, but the majority of publications relate to community-associated methicillin-resistant S. aureus (CA-MRSA) or mixed patient groups. This study focuses on necrotizing pneumonia due to methicillin-sensitive S. aureus strains, with the purpose to determine factors associated with outcome. METHODS: We report a patient with PVL secreting MSSA necrotizing pneumonia and performed a systematic review of similar case in the literature. We analyzed factors associated with outcome. RESULTS: A total of 32 patient descriptions were retained for analysis. Septic shock (p = 0.007), influenza-like prodrome (p = 0.02), and the absence of a previous skin and soft-tissue infection (p = 0.024) were associated with fatal outcome. In multivariate analysis, influenza-like prodrome (odds ratio (OR), 7.44; 95% confidence interval (CI), 1.24-44.76; p = 0.028) and absence of previous skin and soft-tissue infection (OR, 0.09; 95% CI, 0.01-0.86; p = 0.036) remained significant predictors of death. CONCLUSIONS: Influenza-like prodrome may be predictive of adverse outcome in PVL-secreting MSSA necrotizing pneumonia. In contrast, previous skin and soft-tissue infection may be associated with improved prognosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".