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LINK . SPRINGER . COM {}

  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Link.springer.com Make Money
  6. Keywords
  7. Topics
  8. Questions
  9. Schema
  10. External Links
  11. Analytics And Tracking
  12. Libraries
  13. CDN Services

We are analyzing https://link.springer.com/article/10.1186/1472-6963-3-13.

Title:
Physicians' ability to predict the risk of coronary heart disease | BMC Health Services Research
Description:
Background Coronary 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
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {πŸ“š}

  • Insurance
  • Health & Fitness
  • Business & Finance

Content Management System {πŸ“}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {πŸ“ˆ}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 7,642,828 visitors per month in the current month.

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How Does Link.springer.com Make Money? {πŸ’Έ}

We find it hard to spot revenue streams.

The purpose of some websites isn't monetary gain; they're meant to inform, educate, or foster collaboration. Everyone has unique reasons for building websites. This could be an example. Link.springer.com has a secret sauce for making money, but we can't detect it yet.

Keywords {πŸ”}

risk, physicians, chd, scenarios, patients, estimates, pubmed, article, treatment, events, study, therapy, coronary, disease, accurate, heart, year, patient, google, scholar, cas, relative, estimate, providers, research, primary, health, cardiovascular, lipidlowering, ability, absolute, general, estimation, data, information, pignone, care, factors, overestimation, central, previous, prediction, prevention, actual, medicine, baseline, inaccurate, reduction, results, subjects,

Topics {βœ’οΈ}

open access license coronary heart disease health services research evidence based management pre-publication history receive lipid-lowering drugs hmg-coa reductase inhibitor pharmacological lipid-lowering therapy involved lipid-lowering therapy lipid-lowering agents primary health care article download pdf general internal medicine alicia fernandez acted privacy choices/manage cookies internal medicine residents preventive medicine residents full access article pignone public health service risk prediction ability primary care providers ldl cholesterol levels central england additional risk factors high cholesterol levels cost-effectiveness analyses suggest preventive care guidelines studied risk prediction affect risk prediction lipid-lowering agent risk factor categories lipid-lowering drugs lipid lowering drugs chd risk factors 'copyright information' section chd risk prediction 4-point likert scale linear regression mayo-smith mf d'agostino rb dresselhaus tr peabody jw introducing cognitive psychology previous studies examining relative risk reduction providers misestimate risk risk-reducing therapies primary prevention trials lipid-lowering therapy

Questions {❓}

  • Chatellier G, Blinowska A, Menard J, Degoulet P: Do physicians estimate reliably the cardiovascular risk of hypertensive patients?
  • Grover SA, Lowensteyn I, Esrey KL, Steinert Y, Joseph L, Abrahamowicz M: Do doctors accurately assess coronary risk in their patients?
  • Jackson PR, Wallis EJ, Haq IU, Ramsay LE: Statins for primary prevention: at what coronary risk is safety assured?

Schema {πŸ—ΊοΈ}

WebPage:
      mainEntity:
         headline:Physicians' ability to predict the risk of coronary heart disease
         description:Coronary 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. Twelve 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%. 79 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. Physicians overestimate the absolute risk of CHD events and the potential absolute benefit of drug therapy.
         datePublished:2003-07-11T00:00:00Z
         dateModified:2003-07-11T00:00:00Z
         pageStart:1
         pageEnd:6
         sameAs:https://doi.org/10.1186/1472-6963-3-13
         keywords:
            coronary heart disease
            risk prediction
            cholesterol
            anticholesteremic agents
            Public Health
            Health Administration
            Health Informatics
            Nursing Research
         image:
         isPartOf:
            name:BMC Health Services Research
            issn:
               1472-6963
            volumeNumber:3
            type:
               Periodical
               PublicationVolume
         publisher:
            name:BioMed Central
            logo:
               url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
               type:ImageObject
            type:Organization
         author:
               name:Michael Pignone
               affiliation:
                     name:University of North Carolina
                     address:
                        name:Division of General Internal Medicine and Cecil Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, USA
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                        name:Population Health Support Division, Air Force Medical Operations Agency, Brooks AFB, USA
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               name:Tom A Elasy
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                     name:Vanderbilt University
                     address:
                        name:Division of General Internal Medicine and Center for Health Services Research, Vanderbilt University, Nashville, USA
                        type:PostalAddress
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               name:Alicia Fernandez
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                     name:San Francisco General Hospital, University of California
                     address:
                        name:Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, USA
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      context:https://schema.org
ScholarlyArticle:
      headline:Physicians' ability to predict the risk of coronary heart disease
      description:Coronary 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. Twelve 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%. 79 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. Physicians overestimate the absolute risk of CHD events and the potential absolute benefit of drug therapy.
      datePublished:2003-07-11T00:00:00Z
      dateModified:2003-07-11T00:00:00Z
      pageStart:1
      pageEnd:6
      sameAs:https://doi.org/10.1186/1472-6963-3-13
      keywords:
         coronary heart disease
         risk prediction
         cholesterol
         anticholesteremic agents
         Public Health
         Health Administration
         Health Informatics
         Nursing Research
      image:
      isPartOf:
         name:BMC Health Services Research
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            1472-6963
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            Periodical
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         name:BioMed Central
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            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
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            name:Michael Pignone
            affiliation:
                  name:University of North Carolina
                  address:
                     name:Division of General Internal Medicine and Cecil Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, USA
                     type:PostalAddress
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            email:[email protected]
            type:Person
            name:Christopher J Phillips
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                  name:Air Force Medical Operations Agency
                  address:
                     name:Population Health Support Division, Air Force Medical Operations Agency, Brooks AFB, USA
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                  type:Organization
            type:Person
            name:Tom A Elasy
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                  name:Vanderbilt University
                  address:
                     name:Division of General Internal Medicine and Center for Health Services Research, Vanderbilt University, Nashville, USA
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            name:Alicia Fernandez
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                  name:San Francisco General Hospital, University of California
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                     name:Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, USA
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      address:
         name:Population Health Support Division, Air Force Medical Operations Agency, Brooks AFB, USA
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      name:Vanderbilt University
      address:
         name:Division of General Internal Medicine and Center for Health Services Research, Vanderbilt University, Nashville, USA
         type:PostalAddress
      name:San Francisco General Hospital, University of California
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         name:Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, USA
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      name:Michael Pignone
      affiliation:
            name:University of North Carolina
            address:
               name:Division of General Internal Medicine and Cecil Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, USA
               type:PostalAddress
            type:Organization
      email:[email protected]
      name:Christopher J Phillips
      affiliation:
            name:Air Force Medical Operations Agency
            address:
               name:Population Health Support Division, Air Force Medical Operations Agency, Brooks AFB, USA
               type:PostalAddress
            type:Organization
      name:Tom A Elasy
      affiliation:
            name:Vanderbilt University
            address:
               name:Division of General Internal Medicine and Center for Health Services Research, Vanderbilt University, Nashville, USA
               type:PostalAddress
            type:Organization
      name:Alicia Fernandez
      affiliation:
            name:San Francisco General Hospital, University of California
            address:
               name:Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, USA
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Division of General Internal Medicine and Cecil Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, USA
      name:Population Health Support Division, Air Force Medical Operations Agency, Brooks AFB, USA
      name:Division of General Internal Medicine and Center for Health Services Research, Vanderbilt University, Nashville, USA
      name:Division of General Internal Medicine, San Francisco General Hospital, University of California, San Francisco, USA

External Links {πŸ”—}(87)

Analytics and Tracking {πŸ“Š}

  • Google Tag Manager

Libraries {πŸ“š}

  • Clipboard.js
  • Prism.js

CDN Services {πŸ“¦}

  • Crossref

4.82s.