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Record W3010710316 · doi:10.12968/jowc.2020.29.3.141

Economic evaluation of compression stockings for the prevention of venous leg ulcer recurrence in Ontario

2020· article· en· W3010710316 on OpenAlexaffabout
S. Djalalov, S Sehatzadeh, David Keast, William Wong

Bibliographic record

VenueJournal of Wound Care · 2020
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsUniversity of WaterlooLawson Health Research InstituteToronto Public Health
Fundersnot available
KeywordsMedicineCompression stockingsVaricose UlcerPhysical therapyCohortSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Approximately between 1.5 and 3.0 per 1000 people are affected by venous leg ulcers (VLUs). The treatment and management of VLUs is costly and recurrence is a major concern. There is evidence that compression stockings can reduce the rate of re-ulceration compared with no compression. We present the first cost-effective analysis of compression stockings in preventing recurrence of VLUs from the perspective of the Ontario healthcare system. METHOD: A cost-utility analysis with a five-year time horizon was conducted. Use of compression stockings was compared with usual care (no compression stockings). We simulated a hypothetical cohort of 65-year-old patients with healed VLUs, using a state-transition model. Model input parameters were obtained mainly from the published literature. We estimated quality-adjusted life years (QALYs) gained and direct medical costs. We conducted various sensitivity analyses. RESULTS: Compared with usual care, compression stockings were associated with higher costs and increased QALYs. Cost-utility analysis showed that the incremental cost-effectiveness ratio of compression stockings was $23,864 per QALY gained compared with no compression stockings. The most influential drivers of cost-effectiveness were the utility value of healed VLUs, cost of stockings, number of stocking replacements, monthly prevention cost and the risk of VLU recurrence. CONCLUSION: Compared with usual care, compression stockings were cost-effective in preventing VLUs, using a willingness-to-pay threshold of $50,000. These observations were consistent even when uncertainty in model inputs and parameters were considered.

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 score0.379
Threshold uncertainty score0.176

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 head0.081
GPT teacher head0.351
Teacher spread0.270 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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