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 Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...

You might also read

Related Articles

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

Sort by
Same author

Elevated on-treatment D-dimer level is associated with major bleeding during extended anticoagulation for venous thromboembolism.

Haematologica·2026
Same author

Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.

Science translational medicine·2026
Same author

The diagnostic performance of the YEARS and Pulmonary Embolism Graduated D-dimer algorithms in patients with prior venous thrombosis suspected of pulmonary embolism.

Research and practice in thrombosis and haemostasis·2026
Same author

Guideline-based prognostic factors associated with mortality in pulmonary embolism: a systematic review and meta-analysis.

Thorax·2026
Same author

Patterns of presentation of suspected and confirmed recurrent venous thromboembolism in patients with prior venous thromboembolism.

Research and practice in thrombosis and haemostasis·2026
Same author

Impact of concurrent antiplatelet use on the safety and efficacy of thromboprophylaxis with apixaban in patients with cancer: A post-hoc analysis of the AVERT trial.

Thrombosis research·2026

Related Experiment Video

Updated: Jun 7, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Diagnosis: use of clinical probability algorithms.

Esteban Gandara1, Philip S Wells

  • 1Department of Medicine, Division of Hematology, The Ottawa Hospital and The University of Ottawa, Ottawa, Ontario, Canada.

Clinics in Chest Medicine
|November 5, 2010
PubMed
Summary

Clinical prediction rules improve the diagnosis of pulmonary embolism when combined with clinical assessment and D-dimer testing. This strategy enhances patient management by guiding appropriate diagnostic testing and reducing unnecessary procedures.

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Related Experiment Videos

Last Updated: Jun 7, 2026

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

Area of Science:

  • Cardiology
  • Pulmonary Medicine
  • Diagnostic Imaging

Background:

  • Pulmonary embolism (PE) diagnosis requires careful assessment.
  • Current diagnostic strategies involve clinical evaluation, D-dimer testing, and imaging.
  • Clinical prediction rules (CPRs) have emerged as valuable tools.

Purpose of the Study:

  • To review the role of CPRs in diagnosing PE.
  • To evaluate the clinical application of CPRs in diagnostic algorithms.
  • To summarize evidence supporting CPRs in PE management.

Main Methods:

  • Literature review of diagnostic strategies for suspected PE.
  • Analysis of studies describing and validating CPRs for PE.
  • Synthesis of evidence on the integration of CPRs into clinical practice.

Main Results:

  • CPRs, when used with pretest probability assessment, improve diagnostic accuracy for PE.
  • The combination of CPRs, D-dimer, and imaging optimizes patient management.
  • Evidence supports the use of specific CPRs in diagnostic algorithms.

Conclusions:

  • CPRs are integral to modern PE diagnostic strategies.
  • Effective application of CPRs leads to better patient outcomes.
  • Further integration of CPRs into clinical algorithms is recommended.