Incidence Trends and Epidemiology of Staphylococcus aureus Bacteremia: A Systematic Review of Population-Based Studies
Bibliographic record
Abstract
OBJECTIVES: bacteremia (SAB) from population-based studies from multiple countries. METHODS: A contemporary systematic review was conducted using Ovid Cochrane Central Register of Controlled Trials (1991+), Ovid Embase (1974+), Ovid Medical Literature Analysis and Retrieval System Online (MEDLINE) (1946+ including epub ahead of print, in-process & other non-indexed citations), and Web of Science Core Collection (Science Citation Index Expanded 1975+ and Emerging Sources Citation Index 2015+). Two authors (J.R.H. and J.A.Q.M.) independently reviewed all studies and included those that reported population-based incidence of SAB in patients aged 18 years and older. RESULTS: Twenty-six studies met inclusion criteria with the highest number (n=6) of studies conducted in Canada. The incidence of SAB ranged from 9.3 to 65 cases/100,000/year. The median age of patients with SAB ranged from 62 to 72 years and SAB cases were more commonly observed in men than in women. The most common infection sources were intravascular catheters and skin and soft tissue infections. SAB incidence trends demonstrated high variability for geographic regions and calendar years. Overall, there was no change in the incidence trend across all studies during the past two decades. CONCLUSION: Multiple factors, both pros, and cons are likely responsible for the overall stable SAB incidence in countries included in this systematic review. Some of these factors vary in geographic location and prompt additional investigations from countries not included in the current review so that a more global characterization is defined.
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".