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Record W4281701973 · doi:10.1097/ipc.0000000000001135

High-Dose Vancomycin in the Treatment of Clostridioides difficile Infection

2022· article· en· W4281701973 on OpenAlexaff
Mazen S. Bader, Dominik Mertz, John Hawboldt, Alison Farrell, Abdulaziz Alajmi, Keon Maleki-Yazdi

Bibliographic record

VenueInfectious Diseases in Clinical Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcMaster UniversityMemorial University of NewfoundlandImpactHamilton Health SciencesJuravinski Hospital
Fundersnot available
KeywordsClostridioidesMedicineVancomycinInternal medicineIntensive care medicineStaphylococcus aureusBacteria

Abstract

fetched live from OpenAlex

Background There is significant variability in guideline recommendations regarding the dosing of vancomycin in treating Clostridioides difficile infection (CDI). The aim of this systematic review and meta-analysis was to investigate the efficacy of high-dose vancomycin compared with other current standard of care and other CDI treatment regimens. Methods We conducted a comprehensive literature search in PubMed, the Cochrane Library, Embase, and Web of Science for publications that studied the comparative effectiveness of high-dose vancomycin to other CDI treatment regimens for the period up to July 2020. Results A total of 14 studies, 6 randomized controlled trials (372 participants) and 8 observational controlled studies (952 participants), with a total of 1324 patients were included in the final analysis. There was no statistically significant effect between high-dose vancomycin and other treatment options of CDI on clinical cure/response (odd ratio [OR], 0.70; 95% confidence interval [CI], 0.34 to 1.43; I 2 = 59%), clinical relapse and recurrence (OR, 1.01; 95% CI, 0.72–1.42; I 2 = 61%), and mortality (OR, 1.03; 95% CI, 0.37–2.84; I 2 = 44%). Conclusions High-dose oral vancomycin was not superior to other treatment regimens for the outcomes of clinical response and cure, recurrence, and mortality of CDI.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.411
Teacher spread0.360 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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