Evidence map›Paper›PMID 34215234›Full record

ArticleBMC public health2021

Cardiovascular disease (CVD): assessment, prediction and policy implications.

Shazia Rehman, Erum Rehman, Muhammad Ikram, Zhang Jianglin

Erratum issuedAbstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The effect of high temperatures on risk of hospitalization in northern Vietnam.Environmental science and pollution research international · 2022
    Pooled it
  2. Trial
  3. Are RNA Therapies a Solid Foundation or a Frontier Yet to Be Conquered?International journal of molecular sciences · 2026
    Review
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  16. Identification of In Vivo Internalizing Cardiac-Specific RNA Aptamers.bioRxiv : the preprint server for biology · 2024
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Shazia RehmanDepartment of Dermatology, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The first Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518020, Guangdong, China.
Erum RehmanDepartment of Mathematics& Statistics, School of Statistics, Southwestern University of Finance and Economics, Chengdu, China.
Muhammad IkramCollege of Management, Research Institute of Business Analytics and Supply Chain, Management, Shenzhen University, Shenzhen, China.
Zhang JianglinDepartment of Dermatology, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, The first Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518020, Guangdong, China. zhangjl@csu.edu.cn.

Funding

Union Program of Science and Health of Hunan Province, China 2019JJ80011
6 · The paper itself

Abstract

backgroundThe study aims to predict and assess cardiovascular disease (CVD) patterns in highly affected countries such as Pakistan, India, China, Kenya, the USA, and Sweden. The data for CVD deaths was gathered from 2005 to 2019.

methodsWe utilized non-homogenous discrete grey model (NDGM) to predict growth of cardiovascular deaths in selected countries. We take this process a step further by utilizing novel Synthetic Relative Growth Rate (RGR) and Synthetic Doubling Time (Dt) model to assess how many years it takes to reduce the cardiovascular deaths double in numbers.

resultsThe results reveal that the USA and China may lead in terms of raising its number of deaths caused by CVDs till 2027. However, doubling time model suggests that USA may require 2.3 years in reducing the cardiovascular deaths.

conclusionsThis study is significant for the policymakers and health practitioners to ensure the execution of CVD prevention measures to overcome the growing burden of CVD deaths.

Indexed as

Cardiovascular DiseasesChinaHumansIndiaKenyaPakistanPolicyRisk FactorsSwedenCardiovascular diseaseCVDDoubling time model, assessment, forecastRelative growth rate

Identifiers

PMID34215234
PMCPMC8253470

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.