Corrected QT interval and corresponding risk of torsades de pointes in drug-induced QT prolongation
This risk tool accurately predicts torsade de pointes (TdP) risk for drug-induced QT prolongation, allowing users to select the desired sensitivity and specificity for detecting torsades des points using different cut-offs:
 
  • Cut-off 1 (Bazett's QTc = 500 ms): By selecting this cut-off value, the calculator will have a sensitivity and specificity of 93.8% and 97.2% in detecting torsades des pointes, respectively. This setting aims at reducing the probability of unnecessary cardiac monitoring as much as possible.
 
  • Cut-off 2 (Bazett's QTc = 440 ms): By selecting this cut-off value, the calculator will have a sensitivity and specificity of 98.5% and 66.7% in detecting torsades de points, respectively. This setting aims at reducing the risk of missing torsades des points as much as possible.
Research authors: Chan A, Isbister GK, Kirkpatrick CM, and Dufful SB.
  • Cardiology
  • {{ modelType }}
  • Details
  • Validate model
  • Save input
  • Load input

Corrected QT interval based on Bazett's formula: ms

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

Conditional information

Context information:
The aim of the underlying study was to evaluate the performance of the QT nomogram in assessing the risk of TdP, comparing QT-heart rate combinations for known cases of drug-induced TdP cases to those of a negative control group with normal QT-HR values.

Source:
Chan A, Isbister GK, Kirkpatrick CM, Dufful SB. Drug-induced QT prolongation and torsades de pointes: evaluation of a QT nomogram. QJM. 2007;100(10):609-15.

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