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Record W4375845576 · doi:10.1093/ofid/ofad246

The Impact of Antimicrobial Therapy Duration in the Treatment of Prosthetic Joint Infections Depending on Surgical Strategies: A Systematic Review and Meta-analysis

2023· review· en· W4375845576 on OpenAlex
Flaminia Olearo, Veronica Zanichelli, Aimilia Exarchakou, Anna Both, Ilker Uςkay, Martin Aepfelbacher, Holger Rohde

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typereview
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineMeta-analysisOdds ratioConfidence intervalMEDLINEAntibioticsAntimicrobialWeb of scienceInternal medicineSurgery

Abstract

fetched live from OpenAlex

The aim of this systematic review was to address the question if short antibiotic treatment (SAT; at least 4 but <12 weeks) versus long antibiotic treatment (LAT) affects outcomes in prosthetic joint infections (PJIs). Database research (Medline, Embase, Web of Science, Scopus, Cochrane) retrieved 3740 articles, of which 10 studies were included in the analysis. Compared to LAT, 11% lower odds of treatment failure in the SAT group were found, although the difference was not statistically significant (pooled odds ratio, 0.89 [95% confidence interval, .53-1.50]). No difference in treatment failure was found between SAT and LAT once stratified by type of surgery, studies conducted in the United States versus Europe, study design, and follow-up. There is still no conclusive evidence that antibiotic treatment of PJIs for 12 weeks or longer is associated with better outcomes, irrespective of the type of surgical procedure. Most recent, high-quality studies tend to favor longer antibiotic courses, making them preferable in most situations.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.380
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.103
GPT teacher head0.423
Teacher spread0.321 · 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