Evidence map›Paper›PMID 39773784›Full record

ArticleBMJ open2025

Clinical validation of an artificial intelligence-based decision support system for diagnosis and risk stratification of heart failure (STRATIFYHF): a protocol for a prospective, multicentre longitudinal study.

Sarah Jane Charman, Nduka C Okwose, Amy Groenewegen, Annamaria Del Franco, Maria Tafelmeier, Andrej Preveden, Cristina Garcia Sebastian, Amy S Fuller, David Sinclair, Duncan Edwards and 22 more

Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06377319 (Clinical Validation of an Artificial Intelligence Based Decision Support System for Predicting Risk, Diagnosis, and Progression of Heart Failure), which is not on this 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

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.

NCT06377319 not yet recruitingnot on this map

Clinical Validation of an Artificial Intelligence Based Decision Support System for Predicting Risk, Diagnosis, and Progression of Heart Failure

TypeobservationalSponsorCoventry UniversityRan2024 to 2027Enrolled1,600ConditionsHeart FailureArmsCardiac Output Response to Stress (CORS) test
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

32 authors.

Sarah Jane CharmanNewcastle University Translational and Clinical Research Institute, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0002-3029-7672
Nduka C OkwoseCentre for Health and Life Sciences, Coventry University - Coventry Campus, Coventry, UK.
Amy GroenewegenDepartment of General Practice, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0003-2393-1927
Annamaria Del FrancoUniversity Hospital Careggi, Firenze, Italy.ORCID http://orcid.org/0000-0003-1405-9436
Maria TafelmeierDepartment of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany.
Andrej PrevedenUniversity of Novi Sad Faculty of Medicine, Novi Sad, Serbia.
Cristina Garcia SebastianHospital Universitario Ramón y Cajal, Madrid, Spain.
Amy S FullerCentre for Health and Life Sciences, Coventry University - Coventry Campus, Coventry, UK.
David SinclairNewcastle University Population Health Sciences Institute, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0002-3468-7475
Duncan EdwardsDepartment of Public Health and Primary Care, Primary Care Unit, University of Cambridge, Cambridge, UK.
Anne Pauline NelissenDepartment of General Practice, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.
Petros MalitasPKNM Solutions Sàrl, Colombier, Vaud, Switzerland.
Aikaterini ZisakiPKNM Solutions Sàrl, Colombier, Vaud, Switzerland.
Josep DarbaDepartment of Economics, University of Barcelona, Barcelona, Spain.
Zoran BosnicUniversity of Ljubljana Faculty of Computer and Information Science, Ljubljana, Slovenia.
Petar VracarUniversity of Ljubljana Faculty of Computer and Information Science, Ljubljana, Slovenia.
Fausto BarloccoUniversity Hospital Careggi, Firenze, Italy.
Dimitris FotiadisDepartment of Biomedical Research, Foundation for Research and Technology - Hellas, Hellas, Greece.
Prithwish BanerjeeDepartment of Cardiology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.ORCID http://orcid.org/0000-0001-7793-1733
Guy A MacGowanNewcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
Oscar FernandezNewcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
José ZamoranoHospital Universitario Ramón y Cajal, Madrid, Spain.
Marta Jiménez-Blanco BravoHospital Universitario Ramón y Cajal, Madrid, Spain.
Lars S MaierDepartment of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany.
Iacopo OlivottoExperimental and Clinical Medicine, University of Florence, Firenze, Italy.ORCID http://orcid.org/0000-0003-1751-9266
Frans H RuttenDepartment of General Practice, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0002-5052-7332
Jonathan MantDepartment of Public Health and Primary Care, Primary Care Unit, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-9531-0268
Lazar VelickiUniversity of Novi Sad Faculty of Medicine, Novi Sad, Serbia.
Petar M SeferovićUniversity of Belgrade Faculty of Medicine, Belgrade, Serbia.
Nenad FilipovicBioIRC, Research and Development Center for Bioengineering, Kragujevac, Serbia.
Djordje G JakovljevicNewcastle University Translational and Clinical Research Institute, Newcastle upon Tyne, UK ad5287@coventry.ac.uk.
STRATIFYHF investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHeart failure (HF) is a complex clinical syndrome. Accurate risk stratification and early diagnosis of HF are challenging as its signs and symptoms are non-specific. We propose to address this global challenge by developing the STRATIFYHF artificial intelligence-driven decision support system (DSS), which uses novel analytical methods in determining the risk, diagnosis and prognosis of HF. The primary aim of the present study is to collect prospective clinical data to validate the STRATIFYHF DSS (in terms of diagnostic accuracy, sensitivity and specificity) as a tool to predict the risk, diagnosis and progression of HF. The secondary outcomes are the demographic and clinical predictors of risk, diagnosis and progression of HF. METHODS AND ANALYSIS: STRATIFYHF is a prospective, multicentre, longitudinal study that will recruit up to 1600 individuals (n=800 suspected/at risk of HF and n=800 diagnosed with HF) aged ≥45 years old, with up to 24 months of follow-up observations. Individuals suspected of HF will be divided into two categories based on current definitions and predefined inclusion criteria. All participants will have their medical history recorded, along with data on physical examination (signs and symptoms), blood tests including serum natriuretic peptides levels, ECG and echocardiogram results, as well as demographic, socioeconomic and lifestyle data, and use of complete novel technologies (cardiac output response to stress test and voice recognition biomarkers). All measurements will be recorded at baseline and at 12-month follow-up, with medical history and hospitalisation also recorded at 24-month follow-up. Cardiovascular MRI assessment will be completed in a subset of participants (n=20-40) from eligible clinical centres only at baseline. Each clinical centre will recruit a subset of participants (n=30) who will complete a 6-month home-based monitoring of clinical characteristics and accelerometry (wrist-worn monitor) to determine the feasibility and acceptability of the STRATIFYHF mobile application. Focus groups and semistructured interviews will be conducted with up to 15 healthcare professionals and up to 20 study participants (10 at risk of HF and 10 diagnosed with HF) to explore the needs of patients and healthcare professionals prior to the development of the STRATIFYHF DSS and to evaluate the acceptability of this mobile application. ETHICS AND DISSEMINATION: Ethical approval has been granted by the East Midlands - Leicester Central Research Ethics Committee (24/EM/0101). Dissemination activities will include journal publications and presentations at conferences, as well as development of training materials and delivery of focused training on the STRATIFYHF DSS and mobile application. We will develop and propose policy guidelines for integration of the STRATIFYHF DSS and mobile application into the standard of care in the HF care pathway. TRIAL REGISTRATION NUMBER: NCT06377319.

Indexed as

Artificial IntelligenceDecision Support Systems, ClinicalHeart FailureAgedFemaleHumansLongitudinal StudiesMaleMiddle AgedMulticenter Studies as TopicObservational Studies as TopicPrognosisProspective StudiesRisk AssessmentValidation Studies as TopicArtificial IntelligenceClinical Decision-MakingHeart failureRisk management

Identifiers

PMID39773784
PMCPMC11749309

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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 Socratic graph.