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Record W3122860141 · doi:10.1097/bto.0000000000000514

Intramedullary Delivery of Local Antibiotics Via Calcium Sulfate Beads for Chronic Osteomyelitis With a Simple, Novel Surgical Technique

2021· article· en· W3122860141 on OpenAlexaff
Johnathan R. Lex, Jay Toor, Hayley E.M. Spurr, Jean-Philippe Cloutier, Hans J. Kreder

Bibliographic record

VenueTechniques in Orthopaedics · 2021
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineIntramedullary rodMedullary cavitySurgeryDebridement (dental)FemurOsteomyelitisAnatomy

Abstract

fetched live from OpenAlex

Aim: The aim of this manuscript was to describe a novel surgical technique that can be used intraoperatively to aid in the management of chronic diaphyseal osteomyelitis through the delivery of antibiotics into the medullary canal. Technique: Following standard intramedullary and reamer irrigator aspirator preparation of the femoral canal, a negative-pressure gradient is created through the canal. A 32-Fr chest tube is placed antegrade down the femur and used as a conduit for delivering antibiotic beads. A 20-Fr chest tube can be used to manually piston the beads further down the canal. Uses, Outcomes, and Pitfalls: This technique can be used to administer prefabricated calcium sulfate antibiotic beads or hand-made antibiotic polymethylmethacrylate beads evenly throughout the medullary canal of long-bones. It is a simple, cost-effective, one-surgery solution to assist clinicians when managing patients presenting with this difficult problem.

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)0.000
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: Case report · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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 designCase report
Domainnot available
GenreMethods

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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