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Record W3088119025 · doi:10.1097/won.0000000000000693

Healing Rates of Venous Leg Ulcers Managed With Compression Therapy

2020· article· en· W3088119025 on OpenAlexaffabout
Erin M. Rajhathy, Heather D. Murray, Veronica A. Roberge, Kevin Woo

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsMedicineAnkleVaricose UlcerSurgeryLogistic regressionCompression therapyWound careVenous leg ulcerInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to explore average time to heal for patients with venous leg ulcers (VLUs) receiving standard of care that included compression and advanced wound dressings. DESIGN: Secondary analysis of an existing electronic database. SUBJECT AND SETTINGS: A convenience sample consisting of 1323 patients with VLUs from various community care sectors (homecare and clinics) across Canada. METHODS: The Wound Studies database used in the analysis consisted of data from 6 studies conducted prospectively between 1999 and 2009 in which the treatment and delivery of care for all lower leg ulcers (venous, arterial, and mixed) in Canada was examined. From these studies, only patients with VLUs, with an ankle-brachial pressure index of greater than 0.8, and surface area measurements of the ulcers at baseline, 3 months, and 6 months were included. Descriptive statistics were used to determine the proportion of patients who achieved closure at 3 and 6 months and explore the weekly and monthly healing rates for those who did and did not achieve closure. Logistic regression analysis was performed to identify predictive factors for healing. RESULTS: A total of 777 patients (mean age 69 years) met inclusion criteria. The proportion of patients who achieved closure at 3 and 6 months was 42.2% and 48.6%, respectively. Of the participants who achieved wound closure, monthly mean healing rate, measured by percentage of reduction in surface area, was 33.4% (0.56 cm, SD 1.4 [median 0.15 cm]) through month 3, and 31.0% (0.70 cm, SD 1.6 [median 0.08 cm]) through month 6. The overall monthly surface area reduction was 30%. CONCLUSION: Study findings suggest a monthly surface area reduction of 30% provides a baseline healing rate for VLUs managed with compression therapy and advanced dressings. Findings also suggest standard of care is not sufficient for healing in over 50% of the population, as the proportion of those who achieved closure at 3 and 6 months was 42.2% and 48.6%, respectively.

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 score0.570
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.305
Teacher spread0.272 · 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

Citations26
Published2020
Admission routes2
Has abstractyes

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