First Reported Australian case of Fatal Streptococcal Group B Pneumonia (serotype 21) Necrotising fasciitis complicated by Toxic Shock Like Syndrome – A Case report and review
Bibliographic record
Abstract
Introduction: NF is a life-threatening infection and progressive disease resulting in widespread fulminant tissue destruction. It is rarely caused by Group B Streptococcus pneumonia. Early management with surgical removal of devitalized tissue and urgent antibiotic administration are key therapies. Aim: The aim of this report is to highlight the importance of atypical microorganisms seen in NF. Method: A case presentation and cohort summary of reported NF cases secondary to SPN from the year 2011 to 2020. Results: We report the case of a 67-year-old male, not on immune-suppressive medications, admitted to our intensive care unit with septic shock and multiorgan failure secondary to left leg NF following a 3-week history of cactus prick with an SPN bacteraemia and LRINEC score of 5 on admission. He required multiple surgical debridements and was commenced on appropriate antibiotics. Despite continuous vasopressor supportive therapy, high flux CRRT, and IVIG, our patient died after an 8-day inpatient stay. A 10-year review showed only 5 reported GBSPn NF cases with an associated mortality rate of 40%. Conclusion: A high clinical suspicion of SPN infections in NF is required to avoid high mortality with early diagnosis and targeted anti-microbial therapy. Severity scores may not align with clinical severity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".