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Record W3167589754 · doi:10.9778/cmajo.20200188

The real-world cost-effectiveness of bariatric surgery for the treatment of severe obesity: a cost–utility analysis

2021· article· en· W3167589754 on OpenAlexaffvenue
E Lester, Raj Padwal, Daniel W. Birch, Arya M. Sharma, Helen So, Feng Ye, Scott Klarenbach

Bibliographic record

VenueCMAJ Open · 2021
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineQuality-adjusted life yearObservational studyCohortObesityHealth careCohort studyComorbidityClinical trialCost effectivenessEmergency medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Severe obesity is associated with adverse health outcomes and increased risk of death. This study evaluates the real-world cost-utility of therapy for severe obesity, from the publicly funded health care system and societal perspectives. METHODS: ) who were enrolled in a regional obesity program over 2 years. We extrapolated 10-year and lifetime Markov models, validated and supplemented with literature sources, to compare medical, surgical and standard care therapies. We performed deterministic and probabilistic sensitivity analyses. RESULTS: The cohort included 500 adults living with severe obesity, 150 of whom received laparoscopic surgical therapy. From a publicly funded health system perspective, at 2 years, surgical therapy had an incremental cost-effectiveness ratio (ICER) of $54 456 per quality-adjusted life-year (QALY) compared with standard care therapy. Over a lifetime, it had an ICER of $14 056 per QALY. From the societal perspective, at 2 years, surgical therapy had an ICER of $340 per QALY; over a lifetime, it was the dominant option. The results were robust to sensitivity analysis. INTERPRETATION: From a public health care perspective, surgery for severe obesity is cost effective, and when approached from a societal perspective, it becomes cost saving. Real-world data support using surgical therapy for severe obesity, and our results contribute to the health economic and clinical literature with regard to a robust analysis from a societal perspective.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.046
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
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 head0.071
GPT teacher head0.353
Teacher spread0.282 · 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

Citations23
Published2021
Admission routes2
Has abstractyes

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