A Case of Necrotizing Fasciitis/Myositis and Streptococcal Toxic Shock Syndrome Caused by emm22/ST46 Strain of Streptococcus pyogenes
Bibliographic record
Abstract
Abstract: Streptococcus pyogenes , also known as Group A Streptococcus (GAS), can cause severe invasive diseases with high fatality rates. We report a case of necrotizing fasciitis and myositis complicated by Streptococcal Toxic Shock-Like Syndrome (STSS) caused by the invasive emm 22/ST46 strain of Streptococcus pyogenes in China. A previously healthy 57-year-old Chinese Canadian man presented with right calf pain and ulceration following a hike in the Gobi Desert, which progressed to unconsciousness and severe infection. Despite initial treatment, his condition deteriorated, leading to his transfer to our intensive care unit. Metagenomic Next-Generation Sequencing identified Streptococcus pyogenes , and antimicrobial susceptibility testing revealed resistance to erythromycin, tetracycline, and clindamycin. Despite broad-spectrum antimicrobial therapy, debridement, and supportive measures, the patient’s condition necessitated amputation of the right lower limb. He recovered and was discharged from the hospital on Day 43. Whole-genome sequencing of the isolate identified 15 multiple virulence factors. Phylogenetic analysis revealed that the closest relative of the isolate was a strain identified in China. This case underscores the importance of early recognition and treatment of invasive GAS infections to prevent severe outcomes, and we should pay attention to invasive emm 22/ST46 GAS infections in China. Keywords: group A Streptococcus , streptococcal toxic shock-like syndrome, amputation, superantigens, metagenomic next-generation sequencing
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".