Evidence map›Paper›PMID 22348281›Full record

ReviewBritish journal of clinical pharmacology2012

Cardiovascular risk.

Rupert A Payne

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in British journal of clinical pharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 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, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  12. Optimized Clinical Feature Analysis for Improved Cardiovascular Disease Risk Screening.IEEE open journal of engineering in medicine and biology · 2024
    Article
  13. Article
  14. Major Limitations of Cardiovascular Risk Scores.Cardiovascular therapeutics · 2024
    Review
  15. Daidzein Inhibits Human Platelet Activation by Downregulating Thromboxane AInternational journal of molecular sciences · 2023
    Article
  16. Review
  17. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Rupert A PayneGeneral Practice and Primary Care Research Unit, University of Cambridge, UK. rap55@medschl.cam.ac.uk

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making.

Indexed as

Decision MakingPractice Guidelines as TopicAlgorithmsCardiovascular DiseasesHumansPractice Patterns, Physicians'Predictive Value of TestsRisk AssessmentRisk Factors

Identifiers

PMID22348281
PMCPMC3477342

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.