Successful management of severe group A streptococcal soft tissue infections using an aggressive medical regimen including intravenous polyspecific immunoglobulin together with a conservative surgical approach
Bibliographic record
Abstract
Intravenous polyspecific immunoglobulin G (IVIG) has been reported to be efficacious as adjunctive therapy in patients with toxic shock syndrome caused by a group A streptococci (GAS). GAS is also an important cause of necrotizing fasciitis, for which an early and extensive surgical intervention is currently advocated. Here we report on the use of an aggressive medical regimen including high-dose IVIG together with a conservative surgical approach in severe GAS soft tissue infection. We describe 7 patients with severe soft tissue infection caused by GAS, who all were treated with effective antimicrobials and high-dose IVIG. Surgery was either not performed or only limited exploration was carried out. Six of the patients had toxic shock syndrome. All patients survived. Immunostaining of tissue biopsies from 2 of the patients revealed high levels of GAS, superantigen and pro-inflammatory cytokines initially, which were dramatically reduced in a repeat biopsy of the initial operative site collected from 1 of the patients 66 h post-IVIG administration. The study suggests that the use of a medical regimen including IVIG in patients with severe GAS soft tissue infections may allow an initial non-operative or minimally invasive approach, which can limit the need to perform immediate wide debridements and amputations in unstable patients.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".