Evidence mapPaperPMID 42540096Full record

ArticleBMJ nutrition, prevention & health2026

User experience and feasibility of CVD risk models: a study on clinician and patient expectations, and implementation in primary healthcare with P-CARDIAC pilot study in Hong Kong.

Celine S L Chui, Celia Jiaxi Lin, Natalie Tsie, Marco Lee, Ashley Ching Yau Kwok, Judy Lee, Bonnie Leung, Meyone Yuen Tung Ng, Alston Conrad Chiu, Emmanuel Chun Ka Wong

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Article in BMJ nutrition, prevention & health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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No citing paper in PubMed yet.

4 · The record

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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

10 authors.

Celine S L ChuiSchool of Nursing, The University of Hong Kong, Hong Kong, People's Republic of China.ORCID https://orcid.org/0000-0003-1513-8726
Celia Jiaxi LinSchool of Nursing, The University of Hong Kong, Hong Kong, People's Republic of China.
Natalie TsieSchool of Nursing, The University of Hong Kong, Hong Kong, People's Republic of China.
Marco LeeDepartment of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China.
Ashley Ching Yau KwokDepartment of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People's Republic of China.
Judy LeeThe Hong Kong Society for Rehabilitation, Hong Kong, People's Republic of China.
Bonnie LeungA-Lively Community Pharmacy, Aberdeen Kai-fong Welfare Association, Hong Kong, People's Republic of China.
Meyone Yuen Tung NgSchool of Pharmacy, The Chinese University of Hong Kong, Hong Kong, People's Republic of China.
Alston Conrad ChiuDivision of Cardiology, Queen Mary Hospital, Hong Kong, People's Republic of China.
Emmanuel Chun Ka WongCardiology Division, The University of Hong Kong, Hong Kong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A newly developed machine-learning-driven cardiovascular disease (CVD) risk prediction tool, the Personalised CARdiovascular DIsease risk Assessment for Chinese (P-CARDIAC), tailored for the Hong Kong population, has demonstrated superior predictive performance compared with existing risk prediction tool. This study aims to explore the acceptability and expectations of P-CARDIAC among clinicians and the general public, and to assess its feasibility within pharmacist-led services in local primary healthcare systems. Methods: A cross-sectional study was conducted to investigate the awareness and expectations of risk prediction tools among clinicians and the general public. A pragmatic pilot study was carried out to implement P-CARDIAC in pharmacist-led services at local primary healthcare centres. Data analysis included descriptive statistics, univariate regression modelling and reliability assessments of validated measurement scales. Results: For the cross-sectional study, a total of 113 of the general public and 17 clinicians responded to the questionnaire. The general public demonstrated low awareness but high health-seeking behaviour related to CVD risk prediction tools. Clinicians, especially cardiologists, reported limited experience with such tools due to unavailability and limited user-friendliness. In the pilot study, 15 participants engaged with pharmacist-led services incorporating P-CARDIAC. They expressed positive perceptions of the tool, believing that it could support better medication adherence and disease management. The pharmacist-led services incorporating P-CARDIAC were well-received by participants. Conclusion: P-CARDIAC demonstrates promise as a local risk prediction tool to enhance cardiovascular care in Hong Kong. The study underscores the importance of improving awareness and adoption of such CVD risk tools.

Indexed as

Preventive counselling

Identifiers

PMID42540096
PMCPMC13425133

What Socratic holds

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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 Socratic graph.