Evidence map›Paper›PMID 36104666›Full record

ArticleBMC public health2022

Evaluation of cardiovascular diseases risk calculators for CVDs prevention and management: scoping review.

Mohammed Abd ElFattah Mohammed Darwesh Badawy, Lin Naing, Sofian Johar, Sokking Ong, Hanif Abdul Rahman, Dayangku Siti Nur Ashikin Pengiran Tengah, Chean Lin Chong, Nik Ani Afiqah Tuah

Open access · goldAbstract readScoping Review
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
10.2field-weighted citation impact, top 1% of its field
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

40 citing papers in PubMed, 68 citations in OpenAlex.

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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

8 authors at 3 institutions in 3 countries.

Mohammed Abd ElFattah Mohammed Darwesh BadawyPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.
Lin NaingPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.
Sofian JoharPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.
Sokking OngNCD Prevention Unit, Ministry of Health, Bandar Seri Begawan, Brunei Darussalam.
Hanif Abdul RahmanPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.
Dayangku Siti Nur Ashikin Pengiran TengahBrunei Neuroscience Stroke and Rehabilitation Centre, Pantai Jerudong Specialist Centre, Bandar Seri Begawan, Brunei Darussalam.
Chean Lin ChongRaja Isteri Pengiran Anak Saleha Hospital, Cardiology, Bandar Seri Begawan, Brunei Darussalam.
Nik Ani Afiqah TuahPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam. anni.mohamad@ubd.edu.bn.ORCID 0000-0002-7149-4349
Universiti Brunei Darussalam · BNMinistry of Health · BNRaja Isteri Pengiran Anak Saleha Hospital · BN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiovascular diseases (CVDs) are the leading cause of morbidity and mortality globally. This review aimed to summarise evidence on the key features, usability and benefits of CVD risk calculators using digital platforms for CVDs prevention and management in populations.

methodsWe used search engines and thematic analyses to conduct a scoping review. As the reporting guideline for this review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR).

resultsA total of 17 studies meeting eligibility criteria were included in the analysis, from which about 70% of the studies have prognostic level I (n = 8) and level II (n = 4) evidence. The review found that various guidelines are recommending different algorithms for CVD risk prediction. The QRISK® was the most accurate CVD risk calculator for several study populations, whereas World Health Organization/International Society of Hypertension (WHO/ISH) risk scores were the least accurate. The key features of CVD risk calculators are variables, predictive accuracy, discrimination index, applicability, understandability, and cost-effectiveness.

conclusionFor the selected risk prediction tool, development and validation research must be done, which considers a mix of stroke-specific risk and CVD risk to establish its usability in the local community and advantages to the particular health-care environment. To get healthcare professionals more involved in preventing and treating CVDs, each healthcare setting should use an online CVD risk assessment tool that is more useful, accurate, and easy to use, based on the population and health system.

Indexed as

Cardiovascular DiseasesHypertensionDelivery of Health CareHumansRisk AssessmentRisk FactorsCardiovascular diseasesCVD riskDigital healthPopulation healthRisk assessmentRisk calculator

Identifiers

PMID36104666
PMCPMC9471025
OpenAlexW4295901835

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.