Predicting international normalised ratio ≥ 4.5 in hospitalised patients using vitamin K antagonists
Vitamin K antagonists (VKAs) used for the prevention and treatment of thromboembolic disease, increase the risk of bleeding complications. This model was developed and validated to predict the risk of an international normalised ratio (INR) ≥4.5 during a hospital stay.

We developed and validated a clinical prediction model for an INR ≥4.5 in VKA-treated patients admitted to our hospital. The model includes factors that are collected during routine care and are extractable from electronic patient records, enabling easy use of this model to predict an increased bleeding
risk in clinical practice.
Research authors: Albert R. Dreijer, Joseph S. Biedermann, Jeroen Diepstraten, Anouk D. Lindemans, Marieke J.H.A. Kruip, Patricia M.L.A. van den Bemt, Yvonne Vergouwe
  • Clinical pharmacology
  • {{ modelType }}
  • Details
  • Validate model
  • Save input
  • Load input

Predicted risk of INR ≥ 4.5

{{ resultSubheader }}
{{ chart.title }}
Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

The prediction model can help physicians to identify patients at the lower spectrum of thromboembolic risk and those for whom the risk of bleeding during vitamin K antagonist (VKA) therapy is high. Using the prediction model may also help
when counselling and informing patients about their potential risk for haemorrhage while on anticoagulants, and in identifying those patients who might benefit from more careful management of anticoagulation. Alternatively, these patients can also be switched to direct oral anticoagulants (DOACs), which cause less major bleeding, such as intracranial haemorrhages, compared to VKAs

Note
Notes are only visible in the result download and will not be saved by Evidencio
{{ file.classification }}

Calculations alone should never dictate patient care, and are no substitute for professional judgement. See our full disclaimer.

Underlying models Part of
Comments
Comment
Please enter a comment
Comments are visible to anyone

Model feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments
On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:
logo

Please sign in to enable Evidencio print features

In order to use the Evidencio print features, you need to be logged in.
If you don't have an Evidencio Community Account you can create your free personal account at:

https://www.evidencio.com/registration

Printed results - Examples {{ new Date().toLocaleString() }}


Evidencio Community Account Benefits


With an Evidencio Community account you can:

  • Create and publish your own prediction models.
  • Share your prediction models with your colleagues, research group, organization or the world.
  • Review and provide feedback on models that have been shared with you.
  • Validate your models and validate models from other users.
  • Find models based on Title, Keyword, Author, Institute, or MeSH classification.
  • Use and save prediction models and their data.
  • Use patient specific protocols and guidelines based on sequential models and decision trees.
  • Stay up-to-date with new models in your field as they are published.
  • Create your own lists of favorite models and topics.

A personal Evidencio account is free, with no strings attached!
Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction models.


Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Evidencio v3.0 © 2015 - 2021 Evidencio . All Rights Reserved