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Record W2099813365 · doi:10.1038/oby.2005.253

Characteristics of Patients Undergoing Bariatric Surgery in Canada

2005· article· en· W2099813365 on OpenAlexaffabout
Raj Padwal

Bibliographic record

VenueObesity Research · 2005
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsMedicineDyslipidemiaComorbidityDiabetes mellitusObesityConcomitantDiseaseMortality rateSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The increasing prevalence of obesity has led to an increased use of bariatric surgery in the treatment of severely obese individuals. The characteristics of patients undergoing bariatric procedures outside of clinical studies and on a national level have not previously been reported. RESEARCH METHODS AND PROCEDURES: Acute-care hospital discharge data from the Canadian Institute for Health Information were analyzed to determine the demographic and clinical features and in-hospital mortality rates of individuals undergoing bariatric surgery in Canada. Data from individuals undergoing surgery in fiscal year 2002/2003 were compared with data from 1993/1994. RESULTS: Over 1100 bariatric surgeries were performed in Canada in 2002/2003, with the vast majority being performed in middle-aged women. Ten percent of patients had hypertension or diabetes, and only 1% or fewer had dyslipidemia or cardiovascular or cerebrovascular disease. Compared with 1993/1994, patients undergoing surgery in 2002/2003 were older, more likely to have diabetes or hypertension, and had shorter hospital stays. In-hospital mortality rates were <1% in both years. DISCUSSION: In the last decade, there has been a small increase in the average age and the number of patients with concomitant cardiovascular risk factors who are undergoing bariatric procedures in Canada. However, the vast majority of surgeries are being performed in middle-aged women with little cardiovascular comorbidity, and this is likely contributing to very low in-hospital death rates. Such individuals likely represent a highly selected sample of severely obese patients within Canada.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.136
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.300
Teacher spread0.256 · 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 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

Citations27
Published2005
Admission routes2
Has abstractyes

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