Evidence map›Paper›PMID 40401607›Full record

ArticleJournal of the American Heart Association2025

Comparing 3 Evidence-Based Strategies to Reduce Cardiovascular Disease Burden: An Individual-Based Cardiometabolic Policy Simulation.

Sylvia Lutze, Steve Bachmeier, Alison Bowman, Nicole DeCleene, Hussain Jafari, Matthew Kappel, Caroline Kinuthia, Paulina Lindstedt, Megan Lindstrom, Rajan Mudambi and 4 more

Abstract readComparative Study
In one paragraph

Article in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Sylvia LutzeInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0009-0005-7858-0222
Steve BachmeierInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.
Alison BowmanInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.
Nicole DeCleeneInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.
Hussain JafariInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.
Matthew KappelInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0003-2430-5661
Caroline KinuthiaInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.
Paulina LindstedtInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0001-6623-430X
Megan LindstromInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0001-5229-1231
Rajan MudambiInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0001-8649-7561
Christian RazoInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0002-0098-9563
Kjell SwedinInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0003-0778-295X
Abraham FlaxmanInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0001-6033-4713
Gregory RothInstitute for Health Metrics and Evaluation University of Washington Seattle WA USA.ORCID 0000-0002-8355-9146

Funding

Impact of Interventions on Future Trends in Subnational Burden of Cardiovascular Diseases in the USR01HL136868 · NHLBI · UNIVERSITY OF WASHINGTON · PI Gregory Andrew Roth · 2018 to 2026
$5.7M
NHLBI NIH HHS R01 HL136868
6 · The paper itself

Abstract

backgroundUnderstanding the real-world impact of clinical trials that change risk factors is important for health policy. We developed a microsimulation that estimates the population-level benefits in each US state of cardiometabolic interventions.

methodsWe designed a state-specific agent-based simulation model with 51 million in silico individuals and estimated results for 2023 to 2040. Input data reflected current cardiometabolic health and the effects of interventions and risk factors. We constructed 3 health policy intervention scenarios based on randomized controlled trials proven to improve cardiometabolic population health: improved access to fixed-dose combination antihypertensive medication, a pharmacist-led intervention with phone-based reminders to increase adherence to statin and antihypertensive medications at the time they are initiated, and a community-based lifestyle and behavior intervention designed to prevent diabetes. Outcomes included CVD events, deaths, and disability-adjusted life years (DALYs).

resultsOur simulation included a representative population of the United States, accurate at the age, sex, and state level. By 2040, the fixed-dose combination intervention was estimated to have prevented 776 000 (95% uncertainty interval, 578 000-956 000) CVD DALYs and 44 600 (95% uncertainty interval, 32 700-55 600) deaths annually. The pharmacist-led intervention prevented 170 000 (95% uncertainty interval, 129 000-208 000) CVD DALYs, and the community-based intervention prevented 152 000 (95% uncertainty interval, 128 000-173 000) CVD DALYs.

conclusionsA fixed-dose combination of antihypertensives could prevent 1.2% of total CVD DALYs, with smaller benefits from adherence and lifestyle-focused programs. Impact of interventions varied by state. Providing accurate population-level estimates can help local health policy decision-makers implement the most impactful interventions.

Indexed as

Antihypertensive AgentsCardiovascular DiseasesComputer SimulationEvidence-Based MedicineHealth PolicyRisk Reduction BehaviorAdultAgedFemaleHumansHydroxymethylglutaryl-CoA Reductase InhibitorsMaleMedication AdherenceMiddle AgedQuality-Adjusted Life YearsUnited StatesAntihypertensive AgentsHydroxymethylglutaryl-CoA Reductase Inhibitorsadherenceantihypertensivecardiovascular diseasecommunity‐based interventionmicrosimulation

Identifiers

PMID40401607
PMCPMC12229188

What OpenQuestion holds

Texttitle and abstract
LicenceCC BY-NC-ND
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.