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Record W1634208395 · doi:10.1111/wrr.12052

How mechanical deformations contribute to the effectiveness of negative‐pressure wound therapy

2013· review· en· W1634208395 on OpenAlexafffund
Patrick Daigle, Marc‐Antoine Despatis, Guillaume Grenier

Bibliographic record

VenueWound Repair and Regeneration · 2013
Typereview
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchHealth Research Foundation
KeywordsNegative-pressure wound therapyWound healingMedicineMyofibroblastWound careIntensive care medicineAction (physics)SurgeryPathologyFibrosis

Abstract

fetched live from OpenAlex

Negative-pressure wound therapy (NPWT) has significantly improved healing rates and patient comfort since its inception. However, a considerable number of questions have been raised regarding its mechanisms of action. Many health care workers and researchers have attempted to clarify the role of NPWT in wound healing. The purpose of this perspective article is to assemble some of the concepts that have been put forward in order to propose an integrated view of the mechanisms involved in NPWT. Particular emphasis will be placed on mechanically induced tissue deformations and their involvement in some of the key processes of wound healing, including nutrient and oxygen transport, blood vessel formation, and cellular proliferation and differentiation, mainly of myofibroblasts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.313
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations37
Published2013
Admission routes2
Has abstractyes

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