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Record W3215833367 · doi:10.1097/corr.0000000000002076

Reply to the Letter to the Editor: Can Topical Vancomycin Prevent Periprosthetic Joint Infection in Hip and Knee Arthroplasty? A Systematic Review

2021· review· en· W3215833367 on OpenAlexaff
Nicholas M. Desy, Richard Ng, Murray T. Wong

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2021
Typereview
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPeriprostheticMedicineLetter to the editorMeta-analysisSystematic reviewArthroplastyMEDLINEVancomycinIntensive care medicineMedical physicsSurgeryPathologyLaw

Abstract

fetched live from OpenAlex

To the Editor, We thank Drs. Pijls and Nelissen for their comments and analysis related to our article entitled “Can Topical Vancomycin Prevent Periprosthetic Joint Infection in Hip and Knee Arthroplasty? A Systematic Review” [2]. Their interpretations and experiences are valuable contributions to this important and often challenging topic of periprosthetic joint infection (PJI). We appreciate that Drs. Pijls and Nelissen raised the concept of “vote counting,” which, as they stated in their letter, should be avoided when performing systematic reviews [1]. We acknowledge that this method has limitations and may lead to inaccurate conclusions. However, we would assert that we did not perform vote counting in our study as alleged by Drs. Pijls and Nelissen in their letter. We presented the results and indicated which ones (and how many) identified an advantage associated with vancomycin; the fact that most studies did not was not the key finding. The key finding was how broadly most of those studies’ findings bracketed the line of no-difference. Such consistently wide 95% CIs across so many studies, in this situation, is the key finding, not the number of studies that found a “significant difference.” We refrained from performing a meta-analysis as part of our study because data pooling (meta-analysis) of nonrandomized studies is considered poor meta-analytic practice, as the kinds of biases likely present in studies of that design typically will overstate the apparent benefits of the treatment being studied. Instead, as is appropriate for the kinds of studies we analyzed, we performed a systematic review of the best-available evidence. We also agree that the fact that a study does not identify a statistical difference does not necessarily mean that an effect is absent. Most of the studies included in our review were likely underpowered to demonstrate statistical differences. However, to justify a treatment that has risks, such as vancomycin powder, it seems important to have high-quality studies demonstrating an advantage to doing so. Our systematic review found insufficient evidence at this time to recommend the routine use of topical vancomycin powder for PJI prophylaxis. Adequately powered randomized controlled trials are needed. Furthermore, the random effects model done by Drs. Pijls and Nelissen shows a number needed to treat of approximately 145 in favor of topical vancomycin powder. The authors raise the question: “Do we want to expose 145 patients to possibly reduce one occurrence of PJI considering that we do not know the safety concerns associated with vancomycin and we could possibly introduce antimicrobial resistance, which makes treatment of PJI cases more difficult or even impossible in the future?” While those are valid concerns, we feel that the best way to answer these questions is through a methodologically sound randomized controlled trial.

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)0.022
metaresearch head score (Gemma)0.147
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.147
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0030.003
Science and technology studies0.0020.003
Scholarly communication0.0040.006
Open science0.0050.002
Research integrity0.0240.027
Insufficient payload (model declined to judge)0.0050.004

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 head0.086
GPT teacher head0.429
Teacher spread0.344 · 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 designSystematic review
Domainnot available
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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