Evidence map›Paper›PMID 41825917›Full record

ArticleBMJ global health2026

Cost-effectiveness of three screening strategies for atrial fibrillation in Sri Lanka: a decision-tree modelling analysis using community-based prevalence data.

Shribavan Kanesamoorthy, Zainab Abdali, Tiffany E Gooden, Sheron Antony Vethanayagam, Powsiga Uruthirakumar, Chamira Kodippily, Balachandran Kumarendran, Neil Thomas, Krishnarajah Nirantharakumar, Gregory Y H Lip and 7 more

Abstract read
In one paragraph

Article in BMJ global health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

17 authors.

Shribavan KanesamoorthyDepartment of Community and Family Medicine, University of Jaffna, Jaffna, Sri Lanka.ORCID http://orcid.org/0000-0002-9242-9503
Zainab AbdaliDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Tiffany E GoodenDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-3905-5477
Sheron Antony VethanayagamDepartment of Community and Family Medicine, University of Jaffna, Jaffna, Sri Lanka.
Powsiga UruthirakumarDepartment of Community and Family Medicine, University of Jaffna, Jaffna, Sri Lanka.
Chamira KodippilyNational Intensive Care Surveillance-Mahidol Oxford Tropical Medicine Research Unit, Colombo, Sri Lanka.
Balachandran KumarendranDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0001-7786-5932
Neil ThomasDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Krishnarajah NirantharakumarDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Gregory Y H LipDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Mahesan GuruparanHandy Memorial Cardiology Unit, Jaffna Teaching Hospital, Jaffna, Sri Lanka.
Rashan HaniffaCentre for Inflammation Research, The University of Edinburgh, Edinburgh, UK.
Surenthirakumaran RajendraDepartment of Community and Family Medicine, University of Jaffna, Jaffna, Sri Lanka.
Abi BeaneCentre for Inflammation Research, The University of Edinburgh, Edinburgh, UK.ORCID http://orcid.org/0000-0003-4058-7670
Kumaran SubaschandrenDepartment of Community and Family Medicine, University of Jaffna, Jaffna, Sri Lanka.
Sue JowettDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK s.jowett@bham.ac.uk.
NIHR Global Health Research Group on Atrial Fibrillation Management

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEarly diagnosis and treatment of atrial fibrillation (AF) are crucial to reduce AF-related complications and associated healthcare costs. In low-resource settings, digital health technologies could help achieve this; however, costs of different screening strategies are key for policy change.

methodsThis decision-tree model representing the Sri Lankan public health system perspective used prevalence data from a community-based cross-sectional study of 10 000 individuals aged ≥50 years in Northern Province, Sri Lanka. Participants were screened for AF using AliveCor, a handheld single-lead ECG device. Three screening strategies (systematic, opportunistic and targeted) were compared against each other. The incremental cost-effectiveness ratio (ICER) is presented, representing the incremental total aggregated cost between screening strategies divided by the incremental number of new detected AF cases to generate a cost per additional new AF cases detected for a 1-year time horizon.

resultsSystematic screening detected 48 new AF cases, and the targeted screening detected 47. Systematic screening was more expensive (Sri Lankan rupees (Rs) 698 422; US$2123) for 10 000 screened individuals compared with targeted screening (Rs 492 002; US$1496) for 7780 screened individuals. Opportunistic screening was the cheapest strategy (Rs 360 617; US$1096) for screening 6556 individuals; however, only 30 new AF cases were identified. The ICER of targeted screening was lower compared with opportunistic screening (Rs 7729; US$23 per additional detected AF case) whereas the ICER of systematic screening compared with opportunistic screening was higher at Rs 18 767 (US$57) per detected AF case. When the systematic screening strategy was compared with targeted screening, the cost per additional detected AF case increased to Rs 206 420 ($628).

conclusionTargeted screening with AliveCor was the most cost-effective strategy. Systematic screening, while having similar effectiveness, was not cost-effective due to the high additional costs to detect just one further case. These findings support integrating targeted screening into Sri Lanka's primary care pathways.

Indexed as

Atrial FibrillationMass ScreeningAgedCost-Benefit AnalysisCost-Effectiveness AnalysisCross-Sectional StudiesDecision TreesFemaleHumansMaleMiddle AgedPrevalenceSri LankaCardiovascular diseaseCommunity-based surveyHealth economicsScreening

Identifiers

PMID41825917
PMCPMC12993347

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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.