Risk factors for mortality among patients with Staphylococcus aureus bacteremia: a single-centre retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Staphylococcus aureus bacteremia is associated with significant morbidity and mortality. Given the paucity of recent Canadian data, we estimated the mortality rate associated with S. aureus bacteremia in a tertiary care hospital and identified risk factors associated with mortality. METHODS: We retrospectively reviewed the records of adults with S. aureus bacteremia admitted to a tertiary care centre in southwestern Ontario between 2008 and 2012. Cox regression analysis was used to evaluate associations between predictor variables and all-cause, in-hospital, and 90-day postdischarge mortality. RESULTS: Of the 925 patients involved in the study, 196 (21.2%) died in hospital and 62 (6.7%) died within 90 days after discharge. Risk factors associated with in-hospital and all-cause mortality included age, sepsis (adjusted hazard ratio [adjusted HR] 1.49, 95% confidence interval [CI] 1.08-2.06, p = 0.02), admission to the intensive care unit (adjusted HR 3.78, 95% CI 2.85-5.02, p < 0.0001), hepatic failure (adjusted HR 3.36, 95% CI 1.91-5.90, p < 0.0001) and metastatic cancer (adjusted HR 2.58, 95% CI 1.77-3.75, p < 0.0001). Methicillin resistance, hepatic failure, cerebrovascular disease, chronic obstructive pulmonary disease and metastatic cancer were associated with postdischarge mortality. INTERPRETATION: The all-cause mortality rate in our cohort was 27.9%. Identification of predictors of mortality may guide empiric therapy and provide prognostic clarity for patients with S. aureus bacteremia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".