Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A thrombolytic decision tree.

J G Kellett, J O'Riordan

    M.D. Computing : Computers in Medical Practice
    |May 1, 1992
    PubMed
    Summary
    This summary is machine-generated.

    Thrombolytic therapy benefits older patients with myocardial infarction more than younger ones. A decision model shows increased advantages with advancing age, contrary to initial expectations for younger individuals.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Inpatient serum amylase testing post-ERCP.

    Irish medical journal·2025
    Same author

    Efferent limb stimulation prior to loop ileostomy closure: a systematic review and meta-analysis.

    Techniques in coloproctology·2023
    Same author

    Both acuity and long term prognosis are important Emergency Department metrics: comparison of mobility assessment with the Emergency Severity Index.

    Acute medicine·2023
    Same author

    Evaluation of systemic vasoconstriction and prognosis using thermography: a systematic review.

    Acute medicine·2021
    Same author

    Fever increases heart rate and respiratory rate; a prospective observational study of acutely admitted medical patients.

    Acute medicine·2019
    Same author

    Differences in identification of patients' deterioration may hamper the success of clinical escalation protocols.

    QJM : monthly journal of the Association of Physicians·2019
    Same journal

    A clean slate: initiating a graduate program in health informatics.

    M.D. computing : computers in medical practice·2001
    Same journal

    Drugs, codes, standards, and other incompatible things in the dark.

    M.D. computing : computers in medical practice·2001
    Same journal

    Ambulatory care. Implementing an integrated clinical and practice management system.

    M.D. computing : computers in medical practice·2001
    Same journal

    Currents in medical informatics. The Woods Hole experience.

    M.D. computing : computers in medical practice·2001
    Same journal

    Computer telephony integration. Bringing together a host of new applications for healthcare.

    M.D. computing : computers in medical practice·2001
    Same journal

    eHealthcareWorld 2000. Getting down to business.

    M.D. computing : computers in medical practice·2001
    See all related articles

    Area of Science:

    • Cardiology
    • Medical Decision Making
    • Health Informatics

    Background:

    • Myocardial infarction (MI) is a leading cause of mortality worldwide.
    • Thrombolytic therapy is a critical treatment for acute MI, but its optimal application remains debated.
    • Patient age is a significant factor influencing treatment outcomes and risks.

    Purpose of the Study:

    • To develop a decision analysis model for estimating thrombolytic therapy outcomes in patients aged 50-80 with suspected acute myocardial infarction.
    • To evaluate the impact of patient age on the benefits and risks associated with thrombolytic therapy.
    • To explore counterintuitive findings regarding age-related efficacy of thrombolytic treatment.

    Main Methods:

    • Construction of a decision analysis model utilizing data from medical literature.

    Related Experiment Videos

  • Inclusion of key variables: patient age, time from pain onset, probability of acute MI, and probabilities of death, stroke, and hemorrhage.
  • Sensitivity analyses performed by varying input parameters to assess their impact on treatment outcomes.
  • Main Results:

    • The model demonstrated that the benefits of thrombolytic therapy increase with patient age.
    • Younger patients (within the 50-80 age range) derived less significant benefit from thrombolytic therapy compared to older patients.
    • Sensitivity analyses revealed complex interactions between age, time to treatment, and adverse event probabilities.

    Conclusions:

    • Thrombolytic therapy demonstrates a counterintuitive benefit profile, with greater advantages observed in older individuals (50-80 years old).
    • Younger patients within this demographic may not experience the same level of benefit from thrombolytic interventions.
    • The decision model provides valuable insights for personalized treatment strategies in acute myocardial infarction based on age.