MétaCan
Menu
Back to cohort
Record W2324977108 · doi:10.1177/1534734615626626

Knowledge, Attitude, and Practice in the Management of Mixed Arteriovenous Leg Ulcers

2016· article· en· W2324977108 on OpenAlexaff
Kevin Woo, Kim Sears

Bibliographic record

VenueThe International Journal of Lower Extremity Wounds · 2016
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicinePsychosocialAnklePhysical therapyCompression therapyCross-sectional studyFamily medicineSurgeryPathology

Abstract

fetched live from OpenAlex

Leg ulceration is a chronic health condition that constitutes a significant disease burden. In this cross-sectional descriptive study, a sample of wound care clinicians were asked to respond to a web-based survey. Based on a review of literature and recommended best practices in the management of mixed arteriovenous (AV) ulcers, a questionnaire was developed to examine the knowledge, attitude, and practice pattern in the management of AV ulcers. A total of 436 clinicians participated in the survey. A number of assessment techniques were perceived to be relevant for the assessment of AV ulcers; medical history and the appearance of ulcers were the most commonly used methods in clinical practice. While over 80% of the participants conceded that compression should be used to promote wound healing, half of them would consider using compression for AV ulcers if ankle brachial index was less than 0.8. Half of the participants considered an ankle brachial index of 0.8 or higher as the optimal cutoff value for safe compression. The majority of respondents disagreed with the perception that caring for people with AV ulcers was unrewarding. However, challenges to promote treatment adherence, address psychosocial concerns, and optimize symptom management are common.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.330
Teacher spread0.304 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of Lower Extremity WoundsSame topicDiagnosis and Treatment of Venous DiseasesFrench-language works237,207