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Record W2607246330 · doi:10.23907/2013.003

Forensic Considerations in Bariatric Surgery Patients

2013· article· en· W2607246330 on OpenAlexaff
Judy Melinek, Nikolas P. Lemos

Bibliographic record

VenueAcademic Forensic Pathology · 2013
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsMedicineSurgeryCause of deathDiabetes mellitusPopulationDiseaseObesityGeneral surgeryIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Bariatric surgery is gaining in popularity in the United States and around the world as a treatment for morbid obesity. Patients seek surgery in order to lose weight and limit the long-term effects of insulin-resistant diabetes, heart disease and lung disease, including risk of sudden death. While gastric bypass in patients with morbid obesity can reduce the risk of diabetes and myocardial infarction to population levels, the risk of death remains increased. These patients may die suddenly and unexpectedly as a direct result of surgery, as an indirect result of surgery, or of end-organ damage wrought by years of obesity, completely unrelated to the surgery. Proper forensic pathologic assessment of these patients requires an understanding of the anatomic changes caused by bariatric surgery, the complications and the metabolic consequences of the different procedures. In order to better understand this subgroup of patients, a search of the peer-reviewed medical literature at the National Library of Medicine was conducted for articles using the keywords bariatric, surgery, gastric bypass, autopsy, review, toxicology, alcohol, drug, ethanol, absorption, elimination, litigation, forensic, and death. This review outlines the most common laparoscopic and open surgical procedures; the common immediate post-surgical complications that lead to morbidity and mortality; forensic toxicological considerations in bariatric patients; and the long-term complications and other causes that could lead to unexpected death in these patients.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.266
Teacher spread0.239 · 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 designNot applicable
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

Citations1
Published2013
Admission routes1
Has abstractyes

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