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Screening for cardiovascular disease risk and subsequent management in low and middle income countries: challenges and opportunities

Overview of attention for article published in Public Health Reviews, November 2015
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Title
Screening for cardiovascular disease risk and subsequent management in low and middle income countries: challenges and opportunities
Published in
Public Health Reviews, November 2015
DOI 10.1186/s40985-015-0013-0
Pubmed ID
Authors

Pascal Bovet, Arnaud Chiolero, Fred Paccaud, Nick Banatvala

Abstract

Cardiovascular disease (CVD), mainly heart attack and stroke, is the leading cause of premature mortality in low and middle income countries (LMICs). Identifying and managing individuals at high risk of CVD is an important strategy to prevent and control CVD, in addition to multisectoral population-based interventions to reduce CVD risk factors in the entire population. We describe key public health considerations in identifying and managing individuals at high risk of CVD in LMICs. A main objective of any strategy to identify individuals at high CVD risk is to maximize the number of CVD events averted while minimizing the numbers of individuals needing treatment. Scores estimating the total risk of CVD (e.g. ten-year risk of fatal and non-fatal CVD) are available for LMICs, and are based on the main CVD risk factors (history of CVD, age, sex, tobacco use, blood pressure, blood cholesterol and diabetes status). Opportunistic screening of CVD risk factors enables identification of persons with high CVD risk, but this strategy can be widely applied in low resource settings only if cost effective interventions are used (e.g. the WHO Package of Essential NCD interventions for primary health care in low resource settings package) and if treatment (generally for years) can be sustained, including continued availability of affordable medications and funding mechanisms that allow people to purchase medications without impoverishing them (e.g. universal access to health care). This also emphasises the need to re-orient health systems in LMICs towards chronic diseases management. The large burden of CVD in LMICs and the fact that persons with high CVD can be identified and managed along cost-effective interventions mean that health systems need to be structured in a way that encourages patient registration, opportunistic screening of CVD risk factors, efficient procedures for the management of chronic conditions (e.g. task sharing) and provision of affordable treatment for those with high CVD risk. The focus needs to be in primary care because that is where most of the population can access health care and because CVD programmes can be run effectively at this level.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 27 22%
Researcher 14 11%
Student > Ph. D. Student 12 10%
Student > Bachelor 10 8%
Student > Postgraduate 8 6%
Other 24 19%
Unknown 29 23%
Readers by discipline Count As %
Medicine and Dentistry 33 27%
Nursing and Health Professions 20 16%
Social Sciences 10 8%
Economics, Econometrics and Finance 5 4%
Agricultural and Biological Sciences 3 2%
Other 19 15%
Unknown 34 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 November 2015.
All research outputs
#20,657,128
of 25,374,917 outputs
Outputs from Public Health Reviews
#257
of 278 outputs
Outputs of similar age
#289,740
of 393,196 outputs
Outputs of similar age from Public Health Reviews
#5
of 5 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 278 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 393,196 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
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