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Record W4388965956 · doi:10.1007/s11695-023-06913-8

IFSO Consensus on Definitions and Clinical Practice Guidelines for Obesity Management—an International Delphi Study

2023· article· en· W4388965956 on OpenAlexaff
Paulina Salminen, Lilian Kow, Ali Aminian, Lee M. Kaplan, Abdelrahman Nimeri, Gerhard Prager, Estuardo Behrens, Kevin P. White, Scott A. Shikora, Barham K. Abu Dayyeh, Nasreen Alfaris, Barbara L. Andersen, Luigi Angrisani, Ahmad Bashir, Rachel L. Batterham, Mohit Bhandari, Dale S. Bond, Jean‐Marc Chevallier, Ricardo V. Cohen, Dror Dicker, Claudia K. Fox, Pierre Y. Garneau, Khaled Gawdat, Ashraf Haddad, Jacqués Himpens, Thomas H. Inge, Marina Kurian, Sílvia Leite Faria, Guilherme Macedo, Alexander D. Miras, Violeta Moizé, François Pattou, Luis Poggi, Jaime Ponce, Almino Ramos, Francesco Rubino, Andrés Sánchez-Pernaute, David B. Sarwer, Arya M. Sharma, Christine Stier, Christopher Thompson, Josép Vidal, Tarissa Beatrice Zanata Petry

Bibliographic record

VenueObesity Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversity of AlbertaHôpital du Sacré-Cœur de Montréal
FundersTurun YliopistoNational Institute for Health and Care Research
KeywordsMedicineConsensus conferenceSleeve gastrectomyDelphi methodGastric bypassObesityWeight managementMEDLINESevere obesityManagement of obesityVotingFamily medicineWeight lossGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction This survey of international experts in obesity management was conducted to achieve consensus on standardized definitions and to identify areas of consensus and non-consensus in metabolic bariatric surgery (MBS) to assist in an algorithm of clinical practice guidelines for the management of obesity. Methods A three-round Delphi survey with 136 statements was conducted by 43 experts in obesity management comprising 26 bariatric surgeons, 4 endoscopists, 8 endocrinologists, 2 nutritionists, 2 counsellors, an internist, and a pediatrician spanning six continents over a 2-day meeting in Hamburg, Germany. To reduce bias, voting was unanimous, and the statements were neither favorable nor unfavorable to the issue voted or evenly balanced between favorable and unfavorable. Consensus was defined as ≥ 70% inter-voter agreement. Results Consensus was reached on all 15 essential definitional and reporting statements, including initial suboptimal clinical response, baseline weight, recurrent weight gain, conversion, and revision surgery. Consensus was reached on 95/121 statements on the type of surgical procedures favoring Roux-en-Y gastric bypass, sleeve gastrectomy, and endoscopic sleeve gastroplasty. Moderate consensus was reached for sleeve gastrectomy single-anastomosis duodenoileostomy and none on the role of intra-gastric balloons. Consensus was reached for MBS in patients > 65 and < 18 years old, with a BMI > 50 kg/m 2 , and with various obesity-related complications such as type 2 diabetes, liver, and kidney disease. Conclusions In this survey of 43 multi-disciplinary experts, consensus was reached on standardized definitions and reporting standards applicable to the whole medical community. An algorithm for treating patients with obesity was explored utilizing a thoughtful multimodal approach. Graphical Abstract

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.177
metaresearch head score (Gemma)0.175
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1770.175
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0090.005
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0020.009
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.295
GPT teacher head0.457
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations189
Published2023
Admission routes1
Has abstractyes

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