Artificial Intelligence Stress Echo (FINESSE) Project (FINESSE)

Risk Prediction Model in Patients With Suspected Coronary Artery Disease Based on Contemporary Stress Echocardiography Data Using Artificial Intelligence

The goal of this observational study is to learn whether combining stress echocardiography (stress echo) results with routine clinical information can better predict important heart outcomes in adults (18+) with chest pain who were assessed for suspected coronary artery disease.

The main questions it aims to answer are:

Can an artificial intelligence / machine learning model using stress echo findings plus clinical factors (such as blood pressure, diabetes, smoking, other health conditions, medications, and body measurements) predict major heart-related events (such as heart attack, stroke, death related to heart disease, or the need for coronary procedures) more accurately than stress echo results alone?

Can the model help identify which patients are most likely to benefit from further invasive assessment and possible coronary revascularisation (for example, a stent or bypass surgery)?

Which combination of stress echo measurements and clinical factors contributes most to risk prediction?

Participants will:

Not be asked to attend extra visits or have additional tests for this study.

Have their existing stress echo reports and routinely collected hospital record data analysed (approximately 3,000 people who previously had dobutamine stress echo at Milton Keynes University Hospital).

In some cases, if outcomes are not fully available from hospital records, the research team may check additional sources (such as GP records, or contacting the patient if appropriate) to confirm whether a major heart-related event occurred.

Study Overview

Detailed Description

This is a single-centre, retrospective observational study using an existing dataset of pharmacological (dobutamine) stress echocardiography (SE) reports generated within Milton Keynes University Hospital over approximately 15 years, starting from 2002. The SE dataset comprises reports/letters produced by a single, experienced clinician, which reduces inter-observer variability and supports consistent interpretation across the cohort.

Data sources and cohort construction

SE reports (in document format) will be converted into a structured research database. A computer science team will develop a generalisable approach to extract structured variables from the clinical SE reports, building on prior proof-of-concept work demonstrating feasibility of converting these reports into a database.

The dataset includes clinical variables (e.g., cardiovascular risk factors, comorbidities, prescribed medications, and anthropometrics) alongside SE-derived measures (including ischaemia detection and wall motion scoring at rest and peak stress).

Stress echocardiography technique (context for imaging-derived variables)

The study dataset reflects contemporary dobutamine SE practice at MKUH, with contrast-enhanced imaging used in the majority of cases (SonoVue contrast with rota pump infusion equipment). Studies were performed predominantly on Philips echocardiography systems, with image acquisition across standard stages (resting, intermediate, peak stress, and recovery) and standard views (apical 4-, 2-, and 3-chamber; parasternal long- and short-axis). Reporting used dedicated platforms enabling stage-by-stage comparison.

Outcome ascertainment and linkage

Following database completion, a research nurse will query the hospital Electronic Data Management system to ascertain major adverse cardiovascular events (MACE) for the cohort. Where outcomes cannot be confirmed from hospital systems (e.g., patients no longer served by the hospital), missing outcome information will be explored via primary care physician contact and/or patient contact as appropriate.

Data processing, quality checks, and handling missingness

Extracted data will undergo cleaning prior to analysis. Natural Language Processing (NLP) and feature engineering approaches will be used to transform extracted information into model-ready features. As part of preprocessing, data fields will be checked for completeness and consistency before modelling. Missing outcome data will be addressed through the external outcome checks described above.

Statistical / machine learning approach and internal validation

After preprocessing, subset feature selection methods will be applied to identify the most informative predictors for risk classification. Supervised learning will be used to discriminate between lower-risk cases and cases requiring further investigation, with additional modelling approaches (including regression techniques) planned to support quantification of disease stage in abnormal cases. Overfitting will be mitigated through use of techniques robust to overfitting (e.g., ensemble methods) and internal validation using k-fold cross-validation (five folds), ensuring separation of training and validation data.

Sample size and additional analyses

The study will utilise the available full dataset (approximately 3,000 patients) to maximise model development and internal validation. A cost analysis is also planned using the available data.

Study Type

Observational

Enrollment (Actual)

2281

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Buckinghamshire
      • Milton Keynes, Buckinghamshire, United Kingdom, MK6 5LD
        • Milton Keynes University Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Single-centre retrospective cohort drawn from Milton Keynes University Hospital records, consisting of approximately 3,000 adults who underwent clinically indicated pharmacological (dobutamine) stress echocardiography for assessment of chest pain / suspected coronary artery disease (dataset dating back to 2002, covering ~15 years of reports). Stress echocardiography report variables are extracted and linked to routine clinical outcome data for analysis.

Description

Inclusion Criteria:

  • Age 18 years or older at the time of the index stress echocardiography.
  • Referred for pharmacological (dobutamine) stress echocardiography at Milton Keynes University Hospital for assessment of suspected coronary artery disease / chest pain.
  • Stress echocardiography report available in the hospital dataset for data extraction and conversion into a structured database.

Exclusion Criteria:

  • Age under 18 years at the time of the index stress echocardiography.
  • No available/usable stress echocardiography report for extraction into the study database.
  • Unable to link the record to follow-up outcome information using routine hospital systems (with attempted supplementary checks where needed).
  • Patients who have registered a National Data Opt-out and are therefore not eligible for use of their confidential patient information for research/secondary purposes in this study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Dobutamine Stress Echocardiography Cohort
Adults who previously underwent clinically indicated dobutamine stress echocardiography at Milton Keynes University Hospital for assessment of chest pain/suspected coronary artery disease. Stress echocardiography findings and routinely collected clinical information from existing records will be extracted and linked to subsequent cardiovascular outcomes captured through routine care data. Analyses will examine differences in outcomes between participants with normal versus abnormal stress echocardiography findings (and across predicted risk strata generated by the model).
Clinically indicated dobutamine stress echocardiography performed as part of routine care for assessment of suspected coronary artery disease/chest pain. Echocardiographic images acquired at rest and during incremental dobutamine stress (with recovery imaging) are interpreted for inducible ischaemia and regional wall motion abnormalities (including wall motion scoring). Contrast enhancement may be used where needed to optimise endocardial border definition. For this observational study, no additional tests or procedures are performed beyond standard clinical practice; existing stress echocardiography reports and associated routine clinical data are analysed retrospectively.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Major adverse cardiovascular events (MACE) - composite
Time Frame: From the index dobutamine stress echocardiography date until the first major adverse cardiovascular event or death (whichever occurs first), or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
Composite of fatal myocardial infarction, non-fatal myocardial infarction, stroke, planned coronary revascularisation, and unplanned coronary revascularisation. (yes/no)
From the index dobutamine stress echocardiography date until the first major adverse cardiovascular event or death (whichever occurs first), or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
fatal myocardial infarction
Time Frame: From the index dobutamine stress echocardiography date until fatal myocardial infarction (MI as cause of death), or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
Fatal MI (yes/no)
From the index dobutamine stress echocardiography date until fatal myocardial infarction (MI as cause of death), or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
non-fatal myocardial infarction
Time Frame: From the index dobutamine stress echocardiography date until first non-fatal myocardial infarction, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
non-fatal MI (yes/no)
From the index dobutamine stress echocardiography date until first non-fatal myocardial infarction, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
stroke
Time Frame: From the index dobutamine stress echocardiography date until first stroke, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
stroke (yes/no)
From the index dobutamine stress echocardiography date until first stroke, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
planned coronary revascularisation
Time Frame: From the index dobutamine stress echocardiography date until first planned coronary revascularisation, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
planned coronary revascularisation (yes/no)
From the index dobutamine stress echocardiography date until first planned coronary revascularisation, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
unplanned coronary revascularisation
Time Frame: From the index dobutamine stress echocardiography date until first unplanned coronary revascularisation, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).
unplanned coronary revascularisation (yes/no)
From the index dobutamine stress echocardiography date until first unplanned coronary revascularisation, or censoring at last available follow-up; assessed for up to 15 years (follow-up duration varies by participant).

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Attila Kardos, MD, PhD, FRCP, FESC, Milton Keynes University Hospital NHS Foundation Trust

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 7, 2019

Primary Completion (Actual)

November 4, 2023

Study Completion (Estimated)

October 1, 2028

Study Registration Dates

First Submitted

February 9, 2026

First Submitted That Met QC Criteria

February 18, 2026

First Posted (Actual)

February 25, 2026

Study Record Updates

Last Update Posted (Actual)

February 25, 2026

Last Update Submitted That Met QC Criteria

February 18, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

De-identified, disclosure-controlled individual participant data will be made available to external researchers for accredited research purposes / research in the public interest. Data shared will be limited to the minimum necessary variables to meet the approved research purpose and will be processed to reduce re-identification risk (e.g., de-identification and disclosure control, including suppression/controls where needed). Data will only be released once the approvals and agreements described in the access criteria are in place.

IPD Sharing Time Frame

Requests may be submitted once the research proposal is ready for review. A decision is expected within ~21 days of receipt of a complete application (including all required supporting documents and agreements). Approved data will be transferred after sign-off and completion of the Third Party Agreement, and availability will be case-by-case subject to the database being maintained and the governance safeguards remaining appropriate.

IPD Sharing Access Criteria

Access is not open access. Researchers must apply via the Trust's R&D contact route with full details of the proposed research, justification, and the specific data required. The applicant must be the Principal Investigator for the proposed project and provide evidence of suitability (e.g., CV and GCP certificate where relevant) and enter into the Trust's third-party data access agreement. Requests are reviewed through the Trust governance process, including confirmation that appropriate peer review, patient/public involvement and ethics/regulatory approvals are in place where required. Final information governance sign-off is required before release. Transfers are completed by the database/data custodian and recorded (data transferred, format, and date).

NOTE: Some items (incl. outcome data received from NHS England) may need an MKUH-NHSE contract amendment to name the requester and may incur charges. Contact MKUH R&D: research@mkuh.nhs.uk for further information.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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