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Record W1945570926 · doi:10.1186/s13022-015-0015-0

Safety and efficacy of a side-to-side duodeno-ileal anastomosis for weight loss and type-2 diabetes: duodenal bipartition, a novel metabolic surgery procedure

2015· article· en· W1945570926 on OpenAlexaff
Michel Gagner

Bibliographic record

VenueAnnals of Surgical Innovation and Research · 2015
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineAnastomosisDuodenumIleumWeight lossSurgeryGastroenterologyJejunumInternal medicineObesity

Abstract

fetched live from OpenAlex

BACKGROUND: Partial bypass of the GI tract may promote weight loss by decreased absorption of nutrients and changes in incretins. The aim of the study was to evaluate the safety and efficacy of performing a side-to-side duodeno-ileal anastomosis. METHODS: Seven 40-50 kg female Yorkshire pigs were allocated to a duodeno-ileal anastomosis (DIA), and were compared to a control group (SHAM). Swine's weights were followed for 56 days. Gastroscopies were also performed at 28 days. Blood samples were also taken at regular intervals (CBC and Basic biochemistry profiles). At autopsy, gross changes and histological changes of the liver, duodenum and ileum samples were performed. RESULTS: While the SHAM group gained 33.2 % more weight at 56 days, the DIA group had shown a weight loss of -6.8 %, for a difference of 40.0 % between the 2 groups (p < 0.05). One pig developed an incisional hernia. Gastroscopies demonstrated normal healing without ulceration or inflammation at 28 days. Histological examination of the anastomosis at 56 days showed normal and smooth healing, with absence of liver toxicity. CONCLUSION: In this porcine model with short follow-up, a side-to-side duodeno-ileal anastomosis provided excellent weight loss without apparent nutritional or grossly aberrant histological changes.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.143
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.178
GPT teacher head0.410
Teacher spread0.232 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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