Emerging group C and group G streptococcal endocarditis: A Canadian perspective
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine the incidence of infective endocarditis (IE) in patients with bacteremia caused by group C and group G streptococci (GCGS) and to characterize the burden of disease, clinical characteristics, and outcomes through a case series of patients with GCGS IE. METHODS: Individuals with blood cultures growing GCGS in Manitoba, Canada, between January 2012 and December 2015 were included. Clinical and echocardiographic parameters were collected retrospectively. IE was suspected or confirmed according to the modified Duke criteria. RESULTS: Two hundred and nine bacteremic events occurred in 198 patients. Transthoracic echocardiography (TTE) was performed in 33%. Suspected or confirmed IE occurred in 6% of all patients and in 18% of those with TTE. Native valve infection was more common than prosthetic valve and device-related infections (75%, 17%, and 8%, respectively). Metastatic infection was observed in 64%, primarily to the lungs (57%), skin (43%), osteoarticular system (29%), and central nervous system (29%). Sepsis occurred in 58% and streptococcal toxic shock syndrome in 50% of those with IE, with overall mortality of 17%. CONCLUSIONS: IE from GCGS bacteremia is common and is frequently associated with severe disease, embolic events, and mortality. In the appropriate clinical context, GCGS bacteremic events should prompt investigation for IE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".