HEARTWISE - P-CARDIAC for Chinese: Population-based Study

NCT ID: NCT06262828

Last Updated: 2024-10-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

3800 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-04-25

Study Completion Date

2028-04-30

Brief Summary

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Cardiovascular disease (CVD) is one of the prominent diseases that affect many people. One cost-effective solution is to identify people at higher risk of CVD by CVD risk prediction model. China-PAR, TRS-2P, and SMART2 are common risk prediction models for prevention. However, these risk scores were mostly based on the routinely self-check health information and multivariable regression without time-varying consideration. Investigators developed a Machine Learning (ML) based risk prediction model, Personalized CARdiovascular DIsease risk Assessment for Chinese (P-CARDIAC) among a predominantly Chinese population in Hong Kong to estimates the 10 years of secondary recurrent CVD risk for the high-risk individuals. The study objective is to evaluate the accuracy of the P-CARDIAC performance in practice among a large-scale Hong Kong population in medicine specialist outpatient clinic (SOPC) and cardiac clinic. The results will reassure cardiologists that the P-CARDIAC risk score is sensitive to the heart disease symptoms. Investigators anticipate that the results may help to facilitate P-CARDIAC in clinical setting and provide more practical information with the development of P-CARDIAC.

Detailed Description

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This study has two parts to conduct for different outcomes.

Part one is a prospective population-based cohort study. Investigators hypothesize that patients with a higher frequency or larger number of types of cardiac event symptoms are likely to have a higher P-CARDIAC risk score. The correlation between P-CARDIAC risk score and the increasing in number of types and in number of times a patient reported to have heart disease symptoms, e.g. chest pain, shortness of breath, fatigue, swelling in legs, ankles or feet will be examined. The results reassure cardiologists that the P-CARDIAC risk score is sensitive to the heart disease symptoms. Patients who are at a higher risk of recurrent CVD event are likely to have more medications and to have a sooner follow up appointment. At such, investigators also hypothesize a positive relationship between P-CARDIAC risk score and the number of class of medications prescribed and a negative correlation between P-CARDIAC risk score and the time to next SOPC follow up appointment.

Part two of the study will involve Delphi technique to determine P-CARDIAC risk thresholds with reference to current clinical management guideline such as American Heart Association (AHA)/American College of Cardiology (ACC) Multisociety Guideline (AHA/ACC) and European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS) (ESC/EAS), and this part will not involve patient contact. Investigators will compare the P-CARDIAC risk score and the clinician's rating of a patient's recurrent CVD risk on a 10% random subgroup of patients from part one in a "silent deployment" approach, ie, an individual patient's P-CARDIAC risk score will not be communicated to cardiologists. Cardiologists will be invited to rate if they think the patient is at high or low risk according to existing risk scores and the proposed treatment management and target based on treatment guidelines based on their experience. Each patient profile will be reviewed by at least 2 cardiologists and discussed to reach a consensus. Investigators will then evaluate the sensitivity of P-CARDIAC risk score with clinician's judgment. Prior to the commencement of Part two, investigators will collect insights from cardiologists regarding the interpretability of performance metrics and acceptable threshold of model performance for clinical practice. In addition, through this exercise, the research team will assist cardiologists to draft a guideline for follow up for patients at different risk level.

Conditions

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Cardiovascular Diseases CVD

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Individuals aged 18 - 80 years old who visit the medical or cardiology SOPC clinics at the Queen Mary Hospital (QMH), Pok Oi Hospital (POH), Kwong Wah Hospital (KWH), Princess Margaret Hospital (PMH), Queen Elizabeth Hospital (QEH), Tuen Mun Hospital (TMH) and experienced prior CVD event (such as peripheral artery diseases, coronary heart diseases, myocardial infarction, stroke, revascularization) before the scheduled SOPC clinic visit date are eligible to participate in this study. Participants will be also able to comprehend English or Traditional Chinese as well.

Exclusion Criteria

* People with history of dementia, psychiatric diseases or physical impairment.
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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The University of Hong Kong

OTHER

Sponsor Role lead

Responsible Party

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Dr Sze Ling Celine Chui

Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Sze Ling Celine Chui, PhD

Role: PRINCIPAL_INVESTIGATOR

School of Nursing, The University of Hong Kong

Locations

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School of Nursing, The University of Hong Kong

Hong Kong, , Hong Kong

Site Status RECRUITING

Countries

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Hong Kong

Facility Contacts

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Sze Ling Celine Chui, PhD

Role: primary

(852) 3917 6629

References

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Zhiting G, Jiaying T, Haiying H, Yuping Z, Qunfei Y, Jingfen J. Cardiovascular disease risk prediction models in the Chinese population- a systematic review and meta-analysis. BMC Public Health. 2022 Aug 24;22(1):1608. doi: 10.1186/s12889-022-13995-z.

Reference Type BACKGROUND
PMID: 35999550 (View on PubMed)

Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM, McBride P, Schwartz JS, Shero ST, Smith SC Jr, Watson K, Wilson PW, Eddleman KM, Jarrett NM, LaBresh K, Nevo L, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Smith SC Jr, Tomaselli GF; American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014 Jun 24;129(25 Suppl 2):S1-45. doi: 10.1161/01.cir.0000437738.63853.7a. Epub 2013 Nov 12. No abstract available.

Reference Type BACKGROUND
PMID: 24222016 (View on PubMed)

Damman P, van 't Hof AW, Ten Berg JM, Jukema JW, Appelman Y, Liem AH, de Winter RJ. 2015 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: comments from the Dutch ACS working group. Neth Heart J. 2017 Mar;25(3):181-185. doi: 10.1007/s12471-016-0939-y.

Reference Type BACKGROUND
PMID: 27966184 (View on PubMed)

Writing Committee Members; Drozda JP Jr, Ferguson TB Jr, Jneid H, Krumholz HM, Nallamothu BK, Olin JW, Ting HH; ACC/AHATask Force On Performance Measures; Heidenreich PA, Albert NM, Chan PS, Curtis LH, Ferguson TB Jr, Fonarow GC, Ho PM, O'Brien S, Russo AM, Thomas RJ, Ting HH, Varosy PD. 2015 ACC/AHA Focused Update of Secondary Prevention Lipid Performance Measures: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. Circ Cardiovasc Qual Outcomes. 2016 Jan;9(1):68-95. doi: 10.1161/HCQ.0000000000000014. Epub 2015 Dec 14. No abstract available.

Reference Type BACKGROUND
PMID: 26666514 (View on PubMed)

Barrett D, Heale R. What are Delphi studies? Evid Based Nurs. 2020 Jul;23(3):68-69. doi: 10.1136/ebnurs-2020-103303. Epub 2020 May 19. No abstract available.

Reference Type BACKGROUND
PMID: 32430290 (View on PubMed)

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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CIRB-2024-240-3

Identifier Type: -

Identifier Source: org_study_id

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