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Record W2096917861 · doi:10.5435/jaaos-22-03-153

Two-stage Revision Arthroplasty for Management of Chronic Periprosthetic Hip and Knee Infection

2014· review· en· W2096917861 on OpenAlexaff
Paul R.T. Kuzyk, Herman S. Dhotar, Amir Sternheim, Allan E. Gross, Oleg Safir, David Backstein

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2014
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsPeriprostheticMedicineStage (stratigraphy)ArthroplastySurgeryAntibioticsChronic infection

Abstract

fetched live from OpenAlex

In North America, two-stage revision arthroplasty is the treatment of choice for chronic periprosthetic infection of the hip and knee. Controversy exists regarding the diagnosis of persistent infection, cement spacer design, and duration of antibiotic therapy. Erythrocyte sedimentation rate and C-reactive protein tests have no clear cutoff values for detecting infection before reimplantation of hardware, and aspiration for microbial culture can yield false-negative results. Mobile spacers are as effective as static spacers for eradicating infection, but mobile spacers provide better interim function and may help to make the second stage of surgery technically easier. Some articulating spacer designs have fewer reports of spacer dislocation and fracture than do others. Although prolonged antibiotic therapy has been the standard of care for two-stage procedures, some have suggested that a short course of antibiotics is just as effective. When infection persists despite antibiotic therapy, the second stage of revision arthroplasty should be delayed until the first stage of the procedure is repeated.

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)0.001
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.341
Teacher spread0.311 · 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
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

Citations151
Published2014
Admission routes1
Has abstractyes

Explore more

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