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Prevalence and characteristics of lymphoedema at a wound-care clinic

2016· article· en· W2414196440 on OpenAlexaffabout
W. Wang, David Keast

Bibliographic record

VenueJournal of Wound Care · 2016
Typearticle
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsParkwood InstituteWestern University
Fundersnot available
KeywordsMedicineWound careLymphedemaConcomitantRetrospective cohort studyPhysical therapyEtiologyRehabilitationIntensive care medicineCancerSurgeryInternal medicineBreast cancer

Abstract

fetched live from OpenAlex

OBJECTIVE: Lymphoedema is estimated to affect up to 300,000 Canadians but remains underrecognised and undertreated. A retrospective chart review was conducted to determine the clinical characteristics and treatment practices of lymphoedema in a Canadian wound care clinic. METHOD: Data were collected retrospectively from dictated clinic notes of 326 lymphoedema patients at a wound clinic in a regional rehabilitation hospital. RESULTS: The mean age (±SD) of diagnosis was 66.8 (±15.5). Patients had 7.3 (±3.3) comorbidities and took 8.4 (±4.6) concomitant medications. The most common comorbidities were venous disease (73%), hypertension (60%), and obesity (46%). Clinic patients were less likely to be women, have arm lymphoedema, or have cancer-related aetiology compared with previous studies, reflecting a two-tiered model of care delivery in the area. Treatments prescribed by the clinic were consistent best practice recommendations for conservative treatment. CONCLUSION: A significant proportion of the wound clinic's patients had lymphoedema. Lack of resources, lack of awareness among primary care providers, and patient adherence are barriers to lymphoedema care.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.330

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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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