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Record W4414753210 · doi:10.1097/gox.0000000000007082

Modified Dynamic Lymphaticovenular Anastomosis for Surgical Management of Alzheimer Disease

2025· article· en· W4414753210 on OpenAlexaboutno aff
Zhegang Zhou, Xuhui Chen, Wei Kou, Fanbin Meng, Longbiao Yu, Jingjing Wen, Johnson Boey, Vitrag Shah, Paloma Malagón

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2025
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
FundersPeking University
KeywordsCognitive declineAnastomosisCognitionVeinAdverse effectDisease

Abstract

fetched live from OpenAlex

Alzheimer disease (AD) is a neurodegenerative disorder that frequently results in progressive cognitive decline. Despite the extensive research conducted on AD, there is presently no solution available due to its increasing prevalence. Recent research has suggested cervical lymphaticovenular anastomosis (LVA) as a therapeutic strategy to improve lymphatic outflow and potentially reduce AD symptoms. We established an amended LVA protocol to mitigate the risk of venous reflux, a prevalent issue associated with the original LVA methodology. A 64-year-old man of Chinese descent exhibited the typical signs and symptoms of AD. The absence of substantial progress with standard medical treatment led to the consideration of LVA. We used a lower limb vein graft for the LVA, anastomosing it to the cervical lymphatic vessels and external jugular vein. The cognitive function of the patient got better after LVA, as shown by higher Mini Mental State Examination and Montreal Cognitive Assessment scores. Fewer β-amyloid and tau protein deposits were observed on positron emission tomography/computed tomography scans. No adverse occurrences or issues were observed. The success in this case demonstrated the potential role of LVA in the management of AD. However, further thorough research is required to evaluate the efficacy of our technique.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuePlastic & Reconstructive Surgery Global OpenSame topicCerebrospinal fluid and hydrocephalusFrench-language works237,207