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Dilemmas in measuring and using pressure ulcer prevalence and incidence: an international consensus

2009· article· en· W2078528741 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Wound Journal · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineIncidence (geometry)ReimbursementEpidemiologyIntensive care medicineHealth careMEDLINEEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Pressure ulcer prevalence and incidence data are increasingly being used as indicators of quality of care and the efficacy of pressure ulcer prevention protocols. In some health care systems, the occurrence of pressure ulcers is also being linked to reimbursement. The wider use of these epidemiological analyses necessitates that all those involved in pressure ulcer care and prevention have a clear understanding of the definitions and implications of prevalence and incidence rates. In addition, an appreciation of the potential difficulties in conducting prevalence and incidence studies and the possible explanations for differences between studies are important. An international group of experts has worked to produce a consensus document that aims to delineate and discuss the important issues involved, and to provide guidance on approaches to conducting and interpreting pressure ulcer prevalence and incidence studies. The group's main findings are summarised in this paper.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.773

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.080
GPT teacher head0.423
Teacher spread0.344 · 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