A population-based cohort study to establish clinical characteristics and outcomes of patients experiencing methicillin-sensitive <i>Staphylococcus aureus</i> bacteremia as a function of the cefazolin high inoculum effect
Bibliographic record
Abstract
Abstract Background Staphylococcus aureus bacteremia is a leading cause of morbidity and mortality. Several phenotypes (e.g. methicillin-resistance) influence patient outcomes. The high inoculum effect (HIE) is characterized by reduced susceptibility to beta-lactam antibiotics, most notably cefazolin, at high inoculums in-vitro . Methods A population-based cohort was used to assess all MSSA bacteremia in Calgary, Alberta, from 2012-14 and 2019 (n=1.5 million). Isolates underwent genomic sequencing and cefazolin susceptibility testing at 10 5 and 10 7 CFU/ml where the HIE was defined as a 4X-increase in minimum-inhibitory concentration (MIC) and pronounced (PIE) defined as MIC≥16 ug/ml at 10 7 CFU/ml. Results The incidence of MSSA bacteremia with HIE decreased from 38.9 to 24.2% between the two time periods. Patients infected with HIE phenotype could not be differentiated based on demographics, source of bacteremia, or clinical biomarkers at presentation. Sequencing confirmed associations of HIE with blaZ A, agr3, and clonal complex 30. HIE was not associated with outcomes including clearance-time and all-cause mortality when assessed in aggregate or as a function of treatment. Relapses, however, were only documented with cefazolin. PIE was observed in 3.7% of isolates and was associated with significant increased all-cause 180-day mortality, irrespective of treatment, but not at one year. Discussion The HIE, but not PIE, is common in an unselected general population cohort. Neither demographics nor clinical biomarkers can be used to predict HIE. If there is a deleterious impact of this phenotype on patient outcomes, it is modest and may be masked by empiric therapy provided prior to MSSA bacteremia confirmation. Importance Statement A prospective cohort study by Miller et al. (2018) observed a significant increase in 30-day mortality in individuals experiencing methicillin-sensitive Staphylococcus aureus (MSSA) bacteremia, with isolates exhibiting the high-inoculum effect (HIE) phenotype, when treated with the cefazolin. Our study sought to understand the epidemiology and impact of the HIE, using a population-based study design thereby mitigating the selection bias associated with other conventional cohort studies (focused on specific hospitals, at-risk groups, or clinics). We address the effects of HIE on clinical outcomes, predictive factors, and associated genomic contributors for the HIE phenotype within an unbiased population. These data are important for clinicians by highlighting if it is possible to predict HIE phenotype based on clinical and genomic factors, and to establish if cefazolin use associates with worse outcomes when MSSA causing bacteremia exhibits the HIE phenotype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".