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Record W4410230524 · doi:10.1016/j.cmi.2025.04.045

Cefazolin vs. antistaphylococcal penicillins for the treatment of methicillin-susceptible Staphylococcus aureus bacteraemia: a systematic review and meta-analysis

2025· review· en· W4410230524 on OpenAlexaff
Connor Prosty, Dean Noutsios, Todd C. Lee, Nick Daneman, Joshua S. Davis, Nynke G L Jager, Nesrin Ghanem‐Zoubi, Anna L. Goodman, Achim J. Kaasch, Ilse J.E. Kouijzer, Brendan McMullan, Emily G. McDonald, Steven Y. C. Tong, Sean Wei Xiang Ong

Bibliographic record

VenueClinical Microbiology and Infection · 2025
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsSunnybrook Health Science CentreMcGill University Health CentreMcGill University
Fundersnot available
KeywordsCefazolinBacteremiaStaphylococcus aureusMedicineMeta-analysisMicrobiologyCephalosporinStaphylococcal infectionsMicrococcaceaeIntensive care medicineAntibioticsAntibacterial agentInternal medicineBiologyBacteria

Abstract

fetched live from OpenAlex

BACKGROUND: There is debate on whether cefazolin or antistaphylococcal penicillins should be the first-line treatment for methicillin-susceptible Staphylococcus aureus (MSSA) bacteraemia. Ongoing trials are investigating whether cefazolin is non-inferior to (flu)cloxacillin, but it remains uncertain whether these findings apply to other antistaphylococcal penicillins. OBJECTIVES: We conducted a systematic review and meta-analysis comparing cefazolin with each of the individual antistaphylococcal penicillins for MSSA bacteraemia. METHODS: Data sources: We updated a 2019 systematic review but specifically focused on evaluating outcomes by individual antistaphylococcal penicillins. STUDY ELIGIBILITY CRITERIA: Study eligibility criteria include comparative observational studies. PARTICIPANTS: Participants include patients with MSSA bacteraemia. INTERVENTIONS: Interventions include cefazolin vs. the antistaphylococcal penicillins. ASSESSMENT OF RISK OF BIAS: Assessment of risk of bias involved the risk of bias in non-randomized studies of interventions tool. METHODS OF DATA SYNTHESIS: The primary outcome was 30-day all-cause mortality and we assessed for non-inferiority of cefazolin using a pre-specified non-inferiority margin of a pooled OR <1.2 using raw unadjusted data. Secondary outcomes were 90-day mortality, treatment-related adverse events (TRAEs), discontinuation due to toxicity, and nephrotoxicity. RESULTS: No randomized data have been published. A total of 30 observational studies at moderate or high risk of bias were included, which comprised 3869 patients who received cefazolin and 11 644 patients who received antistaphylococcal penicillins (flucloxacillin = 6721, unspecified = 2440, nafcillin = 1305, cloxacillin = 1258, and oxacillin = 120). Cefazolin was associated with a reduced odds of 30-day all-cause mortality (OR = 0.73, 95% CI: 0.62-0.85) compared with antistaphylococcal penicillins, meeting pre-specified non-inferiority. This effect was consistent vs. flucloxacillin (OR = 0.92, 95% CI: 0.73-1.16), nafcillin (OR = 0.58, 95% CI: 0.28-1.17), cloxacillin (OR = 0.42, 95% CI: 0.11-1.58), and oxacillin (OR = 0.31, 95% CI: 0.03-2.75). Point estimates favoured cefazolin for 90-day mortality, TRAEs, nephrotoxicity, and discontinuation due to toxicity overall and in each comparison with individual antistaphylococcal penicillins, except for TRAEs vs. cloxacillin. DISCUSSION: In moderate-to low-quality observational data, cefazolin was non-inferior for mortality and potentially superior for safety as compared with antistaphylococcal penicillins overall and across most individual comparisons.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.024
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.105
GPT teacher head0.423
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2025
Admission routes1
Has abstractno

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