MétaCan
Menu
Back to cohort
Record W4406118021 · doi:10.12998/wjcc.v13.i12.98825

Enhancing outcomes in severe lymphedema through combined treatment strategies

2025· letter· en· W4406118021 on OpenAlexaff
Aidan Shulkin, Johnny Ionut Efanov

Bibliographic record

VenueWorld Journal of Clinical Cases · 2025
Typeletter
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineLymphedemaQuality of life (healthcare)Weight lossStage (stratigraphy)Physical therapySurgeryIntensive care medicineInternal medicineCancerNursing

Abstract

fetched live from OpenAlex

Lymphedema, particularly in its advanced stages, presents significant challenges in treatment, often necessitating a combination of therapies to manage symptoms effectively and improve patient outcomes. This article reviews the findings of Wang et al , regarding the use of lymphovenous anastomosis and complex decongestive therapy in treating severe, deformed stage III lymphedema with recurrent infections. The case report details the promising results achieved through this combined therapy, highlighting substantial reductions in limb volume and the complete resolution of recurrent lymphangitis. The patient experienced notable improvements in weight loss, physical function, and quality of life. Despite its strengths, the study has several limitations. It lacks specific details on the types of lymphovenous anastomoses performed and complex decongestive therapy protocols, such as frequency and adherence, making reproducibility difficult. The short follow-up period of six months limits understanding of long-term efficacy, and more consistent reporting of key metrics such as weight loss and body mass index would enhance outcome assessments. This article emphasizes the importance of integrating minimally invasive surgical techniques with conservative therapies to address both the symptoms and underlying causes of lymphedema. Further research is essential to standardize protocols and refine combined treatment strategies.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
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 head0.093
GPT teacher head0.423
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of Clinical CasesSame topicLymphatic System and DiseasesFrench-language works237,207