Secular trends in incidence of invasive beta-hemolytic streptococci and efficacy of adjunctive therapy in Quebec, Canada, 1996-2016
Bibliographic record
Abstract
OBJECTIVES: To examine secular changes in the incidence of invasive beta-hemolytic streptococcal infections, and to assess the efficacy of immunoglobulins and clindamycin as adjunctive therapies in the management of Streptococcus pyogenes infections. METHODS: Retrospective cohort study of all cases of invasive group A (GAS), B (GBS), C or G (GCGS) streptococcal infections managed in a Canadian tertiary center from 1996-2016. Population incidence was measured for diabetics and non-diabetics. Adjusted odds ratios (AOR) and their 95% confidence intervals (CI) were calculated by logistic regression. RESULTS: 741 cases were identified (GAS: 249; GBS: 304; GCGS: 188). While the incidence of invasive GAS infections fluctuated with no clear trend, incidence of invasive GBS and GCGS increased over time and were 8.4 and 6.3 times higher in diabetics. Mortality of invasive GAS infections decreased from 16% (6/37) in 1996-2001 to 4% (4/97) in 2011-15. Among patients with GAS infections, clindamycin administered concomitantly with a beta-lactam within 24 hours of admission decreased mortality (AOR: 0.04, 95%CI: 0.003-0.55, P = 0.02. Immunoglobulins had no such effect (AOR: 1.66, 95%CI: 0.16-17.36, P = 0.67). The protective effect of clindamycin was similar in patients with pneumonia/empyema compared to all others. CONCLUSION: Incidence of GBS and GCGS infections increased due to an expansion of the high-risk population (elderly diabetics), but also rose in non-diabetics. No such secular change was seen for invasive GAS infections. The decrease in mortality in patients with invasive GAS infections presumably reflects better case-management. Adjunctive clindamycin reduced mortality in invasive GAS infections; immunoglobulins did not, but power was limited. The highest mortality was seen in patients with GAS pneumonia/empyema, for whom clindamycin was protective but underused.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".