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Record W3024924919

The Wound Trend Scale: A Retrospective Review of Utility and Predictive Value in the Assessment and Documentation of Lower Leg Ulcers.

2016· review· en· W3024924919 on OpenAlexaff
Noreen A Campbell, Donna L Campbell, Andrea Turner

Bibliographic record

VenuePubMed · 2016
Typereview
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsIsland Health
Fundersnot available
KeywordsMedicineWound careAmputationAnkleEtiologyFoot (prosody)Medical recordSurgeryDiabetic foot ulcerRetrospective cohort studyDiabetes mellitusReferralPeripheral neuropathyDiabetic footPhysical therapyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Wound assessment is essential to manage wound care. The Wound Trend Scale (WTS) is a paper-and-pen instrument comprised of 14 parameters designed to guide assessment of findings relevant to lower leg ulcer management and includes an infection screen and cues for physician consultation. To determine its clinical utility, predictive value, and reliability, data were retrospectively analyzed from a random sampling of medical records of patients seen at a Foot and Leg Clinic between January 1, 2007 and December 31, 2008. Patients had 1 leg or foot ulcer, 3 consecutive assessments scheduled according to wound status (twice weekly if at high risk for nonhealing or amputation, weekly for moderate risk, or 1 to 2 months if stable), known outcomes, and a maximum treatment period of 3 months. Patient demographics included ulcer etiology, comorbid conditions (diabetes, neuropathy, peripheral arterial disease), and wound outcomes (closed, infection, amputation and surgery). Predictive values, inter- and intrarater reliability (assessed among the authors and 5 additional nurses with expertise using the study instrument), and the impact of WTS education on the wound assessment process were determined using 5 representative cases. Parameters were compared using the t-test. Seventy (70) patient records were examined and subdivided by ulcer site: foot (below ankle, 37) and leg (ankle and above, 33). Of the 13 etiologies, the foot group had 4 and the leg group 10; the foot group had more diabetes (92%), neuropathy (76%), and peripheral arterial disease (95%) than the leg group (52%, 5%, and 70%, respectively). Ulcer duration before referral averaged 16.42 (range 4-144) months. Wound outcomes included closed (57), infection (21), amputation (13), and surgery (3). Healing predictive values were sensitivity (99%), specificity (87%), and positive and negative predictive values and test efficiency (all 96%). Inter- and intrarater reliability were .85 (range .16-.96) and .86 (range .50-1.00), respectively. On admission, leg ulcers had larger surface area (P <0.05), more edema (P <0.01), more granulation (P <0.05), and higher total WTS scores (P <0.05) than foot ulcers, which had more infections (P <0.05). Foot ulcers at the third assessment had decreased tissue depth (P <0.05), increased epithelial tissue (P <0.01), and lower total WTS score (P <0.05). Significant third assessment parameters for leg ulcers were reduced depth (P <0.001), less necrotic tissue (P <0.001), less exudate (P <0.01), improved periwound condition (P <0.05), reduced edema (P <0.001), and increased epithelialization (P <0.01). After exposure to the WTS experience, the number of parameters assessed increased from 2.6 (registered nurses) and 1.5 (student nurses) to both using 15 (P <0.001). Nurses complied 100% with physician consultation for cued risks. Patient outcomes were 81% closure, and 70% had physician consultation for the risks identified. WTS predictive performance was excellent and improved nursing assessment practices. Future research to identify parameter criteria validity is warranted.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.027
GPT teacher head0.341
Teacher spread0.313 · 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 designObservational
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

Citations4
Published2016
Admission routes1
Has abstractyes

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