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Record W4409155410 · doi:10.1097/asw.0000000000000299

Healing Rate and Time to Closure of Venous Leg Ulcers: A Real-World Service Evaluation of Neuromuscular Electrostimulation as an Adjunct to Compression Therapy

2025· article· en· W4409155410 on OpenAlexaff
Holly Murray, Rochelle Duong, Duncan Bain

Bibliographic record

VenueAdvances in Skin & Wound Care · 2025
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsMedicineRetrospective cohort studySurgeryRandomized controlled trialWound careAnesthesia

Abstract

fetched live from OpenAlex

OBJECTIVE: To perform a service evaluation of neuromuscular electrostimulation (NMES) as an adjunct to compression therapy, comparing the rate of wound margin advance and time to closure with a matched retrospective control group. METHODS: Fifteen patients with venous leg ulcers were prescribed NMES for 6 hours per day for 56 days or until wound closure (whichever occurred first), in addition to multilayer compression. Wounds were selected for size, with an inclusion criterion of a maximum of 12 cm 2 . Wound progress was compared with 15 retrospective control patients who were matched for ulcer size and duration. RESULTS: The retrospective group had a healing rate of 0.31 mm per week (95% CI, 29-37 mm/week), whereas the prospective compression plus NMES group had a healing rate of 0.56 mm per week (95% CI, 50-62 mm/week; P = .004). All wounds in both groups healed completely during the service evaluation. Mean time to closure for the retrospective group was 77 days (95% CI, 66-88 days), whereas the NMES group had a mean time to closure of 40 days (95% CI, 37-43 days; P = .005). CONCLUSIONS: Adding NMES of the common peroneal nerve to a care bundle including multicomponent compression resulted in significantly faster wound margin advance and significantly less time to heal in comparison with retrospective matched controls. Future randomized controlled trials or self-controlled studies of this approach would be of great interest to inform 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.364
Teacher spread0.348 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Skin & Wound CareSame topicDiagnosis and Treatment of Venous DiseasesFrench-language works237,207