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Record W2808997146 · doi:10.12968/ijpn.2018.24.6.288

Prevalence of skin tears among frail older adults living in Canadian long-term care facilities

2018· article· en· W2808997146 on OpenAlexaffabout
Kevin Woo, Kim LeBlanc

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsCanadian Association of Occupational TherapistsQueen's University
Fundersnot available
KeywordsGerontologyMedicineLong-term careTearsFamily medicineNursingSurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: To explore the prevalence of skin tears in the Canadian long-term care (LTC) population. SUBJECTS AND SETTING: The setting included 678 residents residing in four LTC facilities in western Canada. DESIGN: A cross-sectional prevalence study to establish the prevalence of skin tears in four LTC facilities in Canada. RESULTS: The prevalence of skin tears was 14.7%. Primary associated risk factors included advanced age, being male and having an increased pressure ulcer risk. CONCLUSION: This study was an important step in establishing the burden of skin tears in the Canadian LTC population. Findings supported the International Skin Tear Advisory Panel (ISTAP) risk reduction programme's claim that increases in age and being of the male sex increase the risk for skin tears. The results support a possible link between skin tear risk factors and risk factors associated with pressure ulcers.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.401
Teacher spread0.374 · 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.

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

Citations44
Published2018
Admission routes2
Has abstractyes

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