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Record W2989100259 · doi:10.5435/jaaos-d-19-00332

Antibiotic Cement Spacers for Infected Total Knee Arthroplasties

2019· review· en· W2989100259 on OpenAlexaff
Paul F. Lachiewicz, Samuel S. Wellman, Jonathan Peterson

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2019
Typereview
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsObject Research Systems (Canada)
Fundersnot available
KeywordsPeriprostheticMedicineAntibioticsArthroplastySurgeryCementTotal knee arthroplastyComplicationDentistryComposite materialMaterials science

Abstract

fetched live from OpenAlex

Periprosthetic infection remains a frequent complication after total knee arthroplasty. The most common treatment is a two-stage procedure involving removal of all implants and cement, thorough débridement, insertion of some type of antibiotic spacer, and a course of antibiotic therapy of varying lengths. After some interval, and presumed eradication of the infection, new arthroplasty components are implanted in the second procedure. These knee spacers may be static or mobile spacers, with the latter presumably providing improved function for the patient and greater ease of surgical reimplantation. Numerous types of antibiotic cement spacers are available, including premolded cement components, surgical molds for intraoperative spacer fabrication, and the use of new metal and polyethylene knee components; all these are implanted with surgeon-prepared high-dose antibiotic cement. As there are advantages and disadvantages of both static and the various mobile spacers, surgeons should be familiar with several techniques. There is inconclusive data on the superiority of any antibiotic spacer. Both mechanical complications and postoperative renal failure may be associated with high-dose antibiotic cement spacers.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.347
Teacher spread0.303 · 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.

Study designNot applicable
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

Citations44
Published2019
Admission routes1
Has abstractyes

Explore more

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