Evidence map›Paper›PMID 32373711›Full record

ArticleInternational journal of cardiology. Heart & vasculature2020

Comparative performance of pooled cohort equations and Framingham risk scores in cardiovascular disease risk classification in a slum setting in Nairobi Kenya.

Frederick M Wekesah, Martin K Mutua, Daniel Boateng, Diederick E Grobbee, Gershim Asiki, Catherine K Kyobutungi, Kerstin Klipstein-Grobusch

Open access · goldAbstract read
In one paragraph

Article in International journal of cardiology. Heart & vasculature, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 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

7 authors at 3 institutions in 4 countries.

Frederick M WekesahAfrican Population and Health Research Center, Nairobi, Kenya.
Martin K MutuaAfrican Population and Health Research Center, Nairobi, Kenya.
Daniel BoatengJulius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.
Diederick E GrobbeeJulius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.
Gershim AsikiAfrican Population and Health Research Center, Nairobi, Kenya.
Catherine K KyobutungiAfrican Population and Health Research Center, Nairobi, Kenya.
Kerstin Klipstein-GrobuschAfrican Population and Health Research Center, Nairobi, Kenya.
African Population and Health Research Center · KEUtrecht University · NLUniversity Medical Center Utrecht · NL

Funding

Shared Core: Biobanking, Bioinformatics and Data ManagementU54HG006938 · NHGRI · WITS HEALTH CONSORTIUM (PTY), LTD · PI RAMSAY, MICHELE MICHELE · 2012 to 2022
$12.2M
NHGRI NIH HHS U54 HG006938
6 · The paper itself

Abstract

backgroundCardiovascular diseases (CVD) cause 18 million deaths annually. Low- and middle-income countries (LMICs) account for 80% of the CVD burden, and the burden is expected to grow in the region in the coming years. Screening for and identification of individuals at high risk for CVD in primary care settings can be accomplished using available CVD risk scores. However, few of these scores have been validated/recalibrated for use in sub-Saharan Africa (SSA).

methodsPooled cohort equations (PCE) and Framingham risk scores for 10-year CVD risk were applied on 1960 men and women aged 40 years and older from the AWI-Gen (Africa, Wits-INDEPTH Partnership for GENomic studies) study 2015. Low, moderate/intermediate or high CVD risk classifications correspond to <10%, 10-20% and >20% chance of developing CVD in 10 years respectively. Agreement between the risk scores was assessed using kappa and correlation coefficients.

resultsHigh CVD risk was 10.3% in PCE 2013, 0.4% in PCE 2018, 2.9% in Framingham and 3.6% in Framingham non-laboratory scores. Conversely, low CVD risk was 62.2% in PCE 2013 and 95.6% in PCE 2018, 84.0% and 80.1% in Framingham and Framingham non-laboratory scores, respectively. A moderate agreement existed between the Framingham functions (kappa = 0.64, 95% CI 0.59-0.68, correlation, r

conclusionsNewer cohort-based data is necessary to validate and recalibrate existing CVD risk scores in order to develop appropriate functions for use in SSA.

Indexed as

FraminghamKenyaPooled cohort equationsRiskRisk assessmentRisk communication

Identifiers

PMID32373711
PMCPMC7191575
OpenAlexW3021066579

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.