Evidence map›Paper›PMID 24913241›Full record

ArticleObesity surgery2014

Cost-utility analysis of gastric bypass for severely obese patients in Spain.

Iván Castilla, Javier Mar, Cristina Valcárcel-Nazco, Arantzazu Arrospide, Juan M Ramos-Goñi

Abstract read
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In one paragraph

Article in Obesity surgery, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Development and Validation of a Discrete Event Simulation Model to Evaluate the Cardiovascular Impact of Population Policies for Obesity.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Iván CastillaHealth Services Research on Chronic Patients Network (REDISSEC), Santa Cruz de Tenerife, Spain, ivan.castillarodriguez@sescs.es.
Javier Mar
Cristina Valcárcel-Nazco
Arantzazu Arrospide
Juan M Ramos-Goñi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo assess the cost-utility of gastric bypass versus usual care for patients with severe obesity in Spain.

methodsWe have implemented a discrete-event simulation model with two branches: one branch involves gastric bypass, thereby reducing patients' BMI, and another branch where patients do not undergo surgery. The model analyzes the emergence of comorbidities (stroke, coronary obstructive disease, diabetes, and breast cancer) associated with obesity during a lifetime horizon. The selected measure of effectiveness is health-related quality of life. Both costs and effects are discounted at 3 %. A probabilistic sensitivity analysis is also performed using second-order Monte Carlo simulation; acceptability curves for different time horizons were also calculated.

resultsPatients with gastric bypass result in a lifetime increase of 5.63 quality-adjusted life years (QALYs) (18.18 vs. 12.55 QALYs). In addition, because of the reduced spending associated with the treatment of various obesity-related comorbidities, final savings stand at 13,994 <euro>. The total cost of the intervention branch is close to half the cost of the non-intervention branch (17,431 vs. 31,425 <euro>).

conclusionsGastric bypass is an intervention that dominates over the option of not intervening when a lifetime horizon is considered.

Indexed as

Cost-Benefit AnalysisAdolescentAgedComorbidityFemaleGastric BypassHumansMaleMiddle AgedObesity, MorbidQuality-Adjusted Life YearsQuality of LifeSpain

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.