Evidence map›Paper›PMID 34632840›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2022

Development and Validation of a Discrete Event Simulation Model to Evaluate the Cardiovascular Impact of Population Policies for Obesity.

Arantzazu Arrospide, Oliver Ibarrondo, Iván Castilla, Igor Larrañaga, Javier Mar

Open access · hybridAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 11% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. A Tutorial on Discrete Event Simulation Models Using a Cost-Effectiveness Analysis Example in R.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
    Article
  2. Article
  3. Using Age-Specific Rates for Parametric Survival Function Estimation in Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Article
  4. Article
  5. Article
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 at 2 institutions in 1 country.

Arantzazu ArrospideOsakidetza Basque Health Service, Debagoiena Integrated Health Organisation, Alto Deba Hospital, Gipuzkoa Primary Care-Integrated Health Organisation Research Unit, Arrasate-Mondragón, Pais Vasco, Spain.ORCID 0000-0003-3537-6588
Oliver IbarrondoOsakidetza Basque Health Service, Debagoiena Integrated Health Organisation, Alto Deba Hospital, Gipuzkoa Primary Care-Integrated Health Organisation Research Unit, Arrasate-Mondragón, Pais Vasco, Spain.
Iván CastillaKronikgune Institute for Health Services Research, Health Services Research on Chronic Patients Network (REDISSEC), Barakaldo, Spain.
Igor LarrañagaOsakidetza Basque Health Service, Debagoiena Integrated Health Organisation, Alto Deba Hospital, Gipuzkoa Primary Care-Integrated Health Organisation Research Unit, Arrasate-Mondragón, Pais Vasco, Spain.
Javier MarOsakidetza Basque Health Service, Debagoiena Integrated Health Organisation, Alto Deba Hospital, Gipuzkoa Primary Care-Integrated Health Organisation Research Unit, Arrasate-Mondragón, Pais Vasco, Spain.
Hospital Alto Deba · ESUniversidad de La Laguna · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOur aim was to describe the development and validation of an obesity model representing the cardiovascular risks associated with different body mass index (BMI) categories, through simulation, designed to evaluate the epidemiological and economic impact of population policies for obesity.

methodsA discrete event simulation model was built in R considering the risk of cardiovascular events (heart failure, stroke, coronary heart disease, and diabetes) associated with BMI categories in the Spanish population. The main parameters included in the model were estimated from Spanish hospital discharge records and the Spanish Health Survey and allowed both first-order and second-order (probabilistic sensitivity analysis) uncertainty to be programmed into the model. The simulation yielded the incidence and prevalence of cardiovascular events as validation outputs. To illustrate the capacity of the model, we estimated the reduction in cardiovascular events and cost-utility (incremental cost/incremental quality-adjusted life-years [QALYs]) of a hypothetical intervention that fully eliminated the cardiovascular risks associated with obesity and overweight.

resultsThe Validation Status of Health-Economic decision models (AdViSHE) tool was applied. Internal validation plots showed adequate goodness of fit for the Spanish population. External validation was achieved by comparing the simulated and real incidence by age group for stroke, acute myocardial infarction, and heart failure. The intervention reduced the population hazard ratios of stroke, acute myocardial infarction, and heart failure to 0.81, 0.74, and 0.78, respectively, and added 0.74 QALYs to the whole population.

conclusionsThis obesity simulation model evidenced good properties for estimating the long-term epidemiological and economic impact of policies to tackle obesity in Spain. The conceptual model could be implemented for other counties using country-specific input data.

Indexed as

ObesityStrokeCost-Benefit AnalysisHumansModels, EconomicPublic PolicyQuality-Adjusted Life Yearsacute myocardial infarctioncardiovascular riskdiabetes mellituseconomicsincidenceobesitystroke

Identifiers

PMID34632840
PMCPMC8777309
OpenAlexW3207118165

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.