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Record W2044195607 · doi:10.3810/pgm.2012.03.2541

Medical Management of Diabetic Foot Infections

2012· review· en· W2044195607 on OpenAlexaff
Mazen S. Bader, Annie Brooks

Bibliographic record

VenuePostgraduate Medicine · 2012
Typereview
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsHamilton Health SciencesJuravinski HospitalMcMaster University
Fundersnot available
KeywordsMedicineDiabetic footDiabetes mellitusAmputationDebridement (dental)Intensive care medicineAntibioticsPhysical examinationMedical historyFoot (prosody)Type 2 Diabetes MellitusSurgery

Abstract

fetched live from OpenAlex

Diabetic foot infections (DFIs) are a commonly encountered medical problem. They are associated with an increased frequency and length of hospitalization and risk for lower-extremity amputation. Furthermore, they have substantial economic consequences. Patients with diabetes mellitus are particularly susceptible to foot infections because of neuropathy, vascular insufficiency, and diminished neutrophil function. The approach to managing DFIs starts with determining if an infection exists. If an infection exists, then the type, severity, extent of infection, and risk factors for resistant organisms should be determined through history, physical examination, and additional laboratory and radiological testing. Optimal management requires surgical debridement, pressure offloading, effective antibiotic therapy, wound care and moisture, maintaining good vascular supply, and correction of metabolic abnormalities, such as hyperglycemia, through a multidisciplinary team. Empiric antibiotics for DFIs vary based on the severity of the infection, but must include anti-staphylococcal coverage.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.073
GPT teacher head0.380
Teacher spread0.308 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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