Evidence map›Paper›PMID 12857356›Full record

ArticleBMC health services research2003

Physicians' ability to predict the risk of coronary heart disease.

Michael Pignone, Christopher J Phillips, Tom A Elasy, Alicia Fernandez

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 3 pooled it
1.0field-weighted citation impact, top 15% 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

24 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Risk scoring for the primary prevention of cardiovascular disease.The Cochrane database of systematic reviews · 2017
    Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Trial
  7. Risk scoring for the primary prevention of cardiovascular disease.The Cochrane database of systematic reviews · 2026
    Article
  8. Article
  9. Article
  10. A highly predictive cardiac positron emission tomography (PET) risk score for 90-day and one-year major adverse cardiac events and revascularization.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  11. Article
  12. Cardiovascular risk assessment: The foundation of preventive cardiology.American journal of preventive cardiology · 2020
    Review
  13. Article
  14. Article
  15. Review
  16. Cardiovascular risk assessment: a global perspective.Nature reviews. Cardiology · 2015 · on this map
    Review
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  18. Article
  19. Review
  20. 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

4 authors at 4 institutions in 1 country.

Michael PignoneDivision of General Internal Medicine and Cecil Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, NC, USA. pignone@med.unc.edu
Christopher J Phillips
Tom A Elasy
Alicia Fernandez
San Francisco General Hospital · USUnited States Air Force · USUniversity of North Carolina at Chapel Hill · USVanderbilt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary heart disease (CHD) is the leading cause of death in the United States. Previous research examining physicians ability to estimate cardiovascular risk has shown that physicians' generally overestimate the absolute risk of CHD events. This question has, however, only studied risk prediction for a limited number of patient care scenarios. The aim of this study is to measure the ability of physicians to estimate the risk of CHD events in patients with no previous history of coronary heart disease.

methodsTwelve primary prevention scenarios with a 5-year risk of CHD events were developed. This questionnaire was surveyed at 3 university teaching hospitals where the participants were a convenience sample of internal medicine residents and fellows or attending physicians in general internal medicine or cardiology. For each scenario, physicians were asked to estimate the baseline 5-year risk of a coronary heart disease event and the revised risk if the patient were to receive lipid-lowering drug therapy. Estimates of the baseline 5-year risk were compared with values calculated from Framingham risk equations. Inaccurate responses were defined as those with a ratio of estimated to actual risk of more than 1.5 or less than 0.67. Physicians' estimates of the relative risk reduction with therapy were considered to be accurate if they were between 25% and 40%.

results79 physicians (53 residents, 8 fellows, 18 attending physicians) completed the survey. Only 24% of physicians' risk estimates were accurate. In most cases, physicians overestimated the absolute risk of cardiovascular events without therapy (proportion overestimating ranged from 32-92% for the 12 individual scenarios). Physicians made larger errors in patient scenarios involving patients with high total or LDL cholesterol levels. Physicians' estimates of the relative risk reduction from treatment were more accurate: 43% of estimates were between 25 and 40%. Over 85% of physicians recommended treatment in 10 of 12 scenarios.

conclusionsPhysicians overestimate the absolute risk of CHD events and the potential absolute benefit of drug therapy.

Indexed as

Clinical CompetenceAge FactorsAnticholesteremic AgentsCardiologyCholesterolCoronary DiseaseFemaleHealth Care SurveysHospitals, UniversityHumansHydroxymethylglutaryl-CoA Reductase InhibitorsInternal MedicineMaleRisk AssessmentSurveys and QuestionnairesUnited StatesAnticholesteremic AgentsCholesterolHydroxymethylglutaryl-CoA Reductase Inhibitors

Identifiers

PMID12857356
PMCPMC183837
OpenAlexW1560389834

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.