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Record W3201394398 · doi:10.1055/s-0041-1731792

Negative Pressure Wound Therapy: Mechanism of Action and Clinical Applications

2021· review· en· W3201394398 on OpenAlexaff
Shanel Normandin, Tyler Safran, Sebastian Winocour, Carrie K. Chu, Joshua Vorstenbosch, Amanda Murphy, Peter Davison

Bibliographic record

VenueSeminars in Plastic Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsMcGill UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineNegative-pressure wound therapyMechanism (biology)Action (physics)Mechanism of actionIntensive care medicinePathologyBiochemistryAlternative medicineEpistemology

Abstract

fetched live from OpenAlex

Negative pressure wound therapy (NPWT) promotes healing by evenly applying negative pressure on the surface of the wound. The system consists of a sponge, a semiocclusive barrier, and a fluid collection system. Its effectiveness is explained by four main mechanisms of action, including macrodeformation of the tissues, drainage of extracellular inflammatory fluids, stabilization of the environment of the wound, and microdeformation. Rarely will complications linked to NPWT occur, but special care must be taken to prevent events such as toxic shock syndrome, fistulization, bleeding, and pain. New NPWT modalities have been recently developed to make NPWT suitable for a wider variety of wounds. These include NPWT with instillation therapy (NPWTi-d), different cleansing options, and application of NPWT on primarily closed incisions. Finally, vacuum-assisted wound closure therapy has been demonstrated to be efficient for various clinical settings, such as the management of diabetic foot ulcers, pressure ulcerations, chronic wounds, and skin grafts.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.096
GPT teacher head0.407
Teacher spread0.311 · 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 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

Citations161
Published2021
Admission routes1
Has abstractyes

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