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Record W2901506980 · doi:10.1093/ofid/ofy210.905

1068. Evaluation of Cefazolin vs. Anti-Staphylococcal Penicillins for the Treatment of Methicillin-Susceptible Staphylococcus aureus Bloodstream Infections in Acutely-Ill Adult Patients: Results of a Systematic Review and Meta-Analysis

2018· review· en· W2901506980 on OpenAlexaboutno aff
Benjamin J. Lee, Janie K. Constantino-Corpuz, Kristel Apolinario, Sheila K Wang, Barbara Nadler, Marc H. Scheetz, Nathaniel J. Rhodes

Bibliographic record

VenueOpen Forum Infectious Diseases · 2018
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsnot available
Fundersnot available
KeywordsCefazolinMedicineInternal medicineCochrane LibraryStaphylococcus aureusMeta-analysisTolerabilityAdverse effectMicrobiologyAntibioticsBiology

Abstract

fetched live from OpenAlex

Abstract Background Anti-staphylococcal penicillins (ASPs) have been regarded as first-line in the treatment of serious MSSA bloodstream infections (BSI) with cefazolin considered an alternative. Recent studies have suggested that infection outcomes between cefazolin and ASPs may be similar. The objective of this study was to compare the clinical efficacy and tolerability of cefazolin to ASPs for MSSA BSI. Methods A systematic review and meta-analysis was conducted. Articles were identified via PubMed, Web of Science, and the Cochrane Library. Studies written in English comparing cefazolin to ASPs for MSSA BSI in adult patients were included. Study quality was assessed using the Cochrane Risk of Bias Assessment Tool and the Newcastle-Ottawa Scale for prospective and retrospective studies, respectively. All review stages were independently conducted by two reviewers, with a third reviewer adjudicating any discrepancies. The fixed- or random-effects model was utilized, as appropriate. A planned subgroup analysis was conducted between high (>15%) vs. low (<14.9%) mortality probability as defined by logit functions applied at the study level. Results Nine studies were identified. Pooled data extracted from 1,726 cefazolin- and 2,716 ASP-patients indicated that cefazolin was associated with a significant reduction in treatment failure (OR: 0.70; 95% CI: 0.61–0.82; P < 0.001; I2 = 14%) and crude, all-cause mortality (OR: 0.69; 95% CI: 0.59–0.81; P < 0.001; I2 = 18%) compared with ASPs. Within a subset of studies (n = 6) demonstrating low mortality probability (<14.9%), cefazolin therapy remained protective against failure (OR: 0.70; P < 0.001; I2 = 39%) and mortality (OR: 0.70; P < 0.001; I2 = 35%). Within the high mortality probability (>15%) subset, no significant differences for failure or mortality were noted. The risk of adverse events was higher with ASPs (OR: 2.58; 95% CI: 1.00–6.64; P = 0.05). Conclusion Cefazolin was associated with significantly lower rates of failure, mortality, and treatment-related adverse events when compared with ASPs among less severely ill patients. Prospective, randomized controlled trials are needed to establish the role of these agents in serious MSSA BSI. Disclosures All authors: No reported disclosures.

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)0.014
metaresearch head score (Gemma)0.025
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 score0.023
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.025
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0230.046
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.002
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 head0.092
GPT teacher head0.399
Teacher spread0.307 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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