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Record W4384126807 · doi:10.1111/1753-0407.13437

Interventional metabology: A review of bariatric arterial embolization and endovascular denervation for treating metabolic disorders

2023· review· en· W4384126807 on OpenAlexaff
Zhi Wang, Dan‐Qi Zhu, Xiangyun Zhu, Dechen Liu, Qing‐Yue Cao, Tao Pan, Qi Zhang, Xiaochun Gu, Ling Li, Gao‐Jun Teng

Bibliographic record

VenueJournal of Diabetes · 2023
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsPancreas Centre (Canada)
FundersNational Natural Science Foundation of China
KeywordsMedicineGlycemicMetabolic syndromeType 2 Diabetes MellitusEmbolizationInterventional radiologyDenervationDiabetes mellitusWeight lossObesitySurgeryIntensive care medicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The rising prevalence of metabolic disorders such as obesity and type 2 diabetes mellitus (T2DM) poses a major challenge to global health. Existing therapeutic approaches have limitations, and there is a need for new, safe, and less invasive treatments. Interventional metabolic therapy is a new addition to the treatment arsenal for metabolic disorders. This review focuses on two interventional techniques: bariatric arterial embolization (BAE) and endovascular denervation (EDN). BAE involves embolizing specific arteries feeding ghrelin-producing cells to suppress appetite and promote weight loss. EDN targets nerves that regulate metabolic organs to improve glycemic control in T2DM patients. We describe the current state of these techniques, their mechanisms of action, and the available safety and effectiveness data. We also propose a new territory called "Interventional Metabology" to encompass these and other interventional approaches to treating metabolic disorders.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.329
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

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