Evidence map›Paper›PMID 20054346›Full record

ArticleJournal of human hypertension2010

The effect of blood pressure and cholesterol variability on the precision of Framingham cardiovascular risk estimation: a simulation study.

T Marshall

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of human hypertension, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. The NHS Health Check programme: a comparison against established standards for screening.The British journal of general practice : the journal of the Royal College of General Practitioners · 2014
    Article
  3. Article
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

1 author.

T MarshallDepartment of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK. T.P.Marshall@bham.ac.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This simulation study investigates the effects of within-individual variability in estimated cardiovascular risk on categorization of patients as high risk. Published estimates of within-individual blood pressure and cholesterol variability were used to generate blood pressure and cholesterol levels for hypothetical subjects at a range of ages. These were used to calculate the estimated cardiovascular risk of each individual. The relationship between an individual's mean cardiovascular risk and within-individual coefficient of variation for cardiovascular risk was determined. Using the derived relationship, mean cardiovascular risk and within-individual variation in risk was calculated for 5018 adults from a population health survey. From this, was determined their probability of being classified as high risk (>20% 10-year cardiovascular risk) and the test characteristics of risk estimation at a range of ages. Within-individual variability in cardiovascular risk and potential for misclassification are both greater in lower-risk populations. At age 35-44 years, the positive predictive value of a diagnosis of high risk is 0.61 (95% confidence interval (CI): 0.59-0.64), and at age 65-74 years, it is 0.94 (95% CI: 0.91-0.96). About 39% of adults under 45 years diagnosed as high risk are not at high risk. Cardiovascular risk assessment should be targeted at high-risk populations.

Indexed as

Blood PressureComputer SimulationModels, CardiovascularAdultAgedAge FactorsBiomarkersCardiovascular DiseasesCholesterolFemaleHumansMaleMiddle AgedReproducibility of ResultsRisk AssessmentRisk FactorsBiomarkersCholesterol

Identifiers

PMID20054346

What OpenQuestion holds

Textmetadata
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.