Comparative effectiveness of cefazolin versus cloxacillin as definitive antibiotic therapy for MSSA bacteraemia: results from a large multicentre cohort study
Bibliographic record
Abstract
OBJECTIVES: We compared the effectiveness of cefazolin versus cloxacillin in the treatment of MSSA bacteraemia in terms of mortality and relapse. METHODS: A retrospective cohort study examined consecutive patients with Staphylococcus aureus bacteraemia from six academic and community hospitals between 2007 and 2010. Patients with MSSA bacteraemia who received cefazolin or cloxacillin as the predominant definitive antibiotic therapy were included in the study. Ninety-day mortality was compared between the two groups matched by propensity scores. RESULTS: Of 354 patients included in the study, 105 (30%) received cefazolin and 249 (70%) received cloxacillin as the definitive antibiotic therapy. In 90 days, 96 (27%) patients died: 21/105 (20%) in the cefazolin group and 75/249 (30%) in the cloxacillin group. Within 90 days, 10 patients (3%) had a relapse of S. aureus infection: 6/105 (6%) in the cefazolin group and 4/249 (2%) in the cloxacillin group. All relapses in the cefazolin group were related to a deep-seated infection. Based on the estimated propensity score, 90 patients in the cefazolin group were matched with 90 patients in the cloxacillin group. In the propensity score-matched groups, cefazolin had an HR of 0.58 (95% CI 0.31-1.08, P = 0.0846) for 90 day mortality. CONCLUSIONS: There was no significant clinical difference between cefazolin and cloxacillin in the treatment of MSSA bacteraemia with respect to mortality. Cefazolin was associated with non-significantly more relapses compared with cloxacillin, especially in deep-seated S. aureus infections.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".