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Record W2023297738 · doi:10.1089/wound.2014.0567

Clinical Biofilms: A Challenging Frontier in Wound Care

2014· review· en· W2023297738 on OpenAlexaff
Jennifer Hurlow, Kara Couch, Karen Laforet, Laura Bolton, Daniel Metcalf, Philip G. Bowler

Bibliographic record

VenueAdvances in Wound Care · 2014
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsCARE Canada
Fundersnot available
KeywordsBiofilmIntensive care medicineWound careMedicineClinical PracticeWound healingPatient careSurgeryBiologyNursingBacteria

Abstract

fetched live from OpenAlex

Significance: Biofilms have been implicated in a variety of wound complications. Recent Advances: Research has confirmed that biofilms form in wounds of patients experiencing delayed healing and may be a precursor to infection. Critical Issues: Research into the strength of this association is still in its infancy. Is biofilm formation a cause of these complications, a step toward them, or a signal that unresolved factors injuring tissue or delaying healing are setting the stage for biofilm formation, infection, and healing delay? To qualify biofilms for use in informing clinical practice decisions, biofilm characteristics supporting those decisions need standardized definitions and valid evidence that they predict or diagnose healing or infection outcomes. Literature searches of relevant terms reviewed biofilm definitions and validation of their role in predicting and diagnosing delayed wound healing or infection. Future Directions: Further research is needed to provide a rapid accurate technique to identify and characterize biofilms in ways that optimize their validity in diagnosing or screening patient risk of infection or delayed healing and to inform clinical decisions. This research will help validate biofilm's capacity to support wound care clinical practice decisions and establish their importance in guiding clinical practice.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.448
Teacher spread0.400 · 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

Citations142
Published2014
Admission routes1
Has abstractyes

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