Probability of ulcer recurrence in diabetic patients - Evidencio
Probability of ulcer recurrence in diabetic patients
Recurrence of plantar foot ulcers is a common and major problem in diabetes but not well understood. This model calculates the probability of ulcer recurrence in diabetic patients.
Research authors: Waaijman R, de Haart M, Arts MLJ, Wever D, Verlouw AJW, Nollet F, Bus SA.
Version: 1.27
  • Public
  • Surgery
  • {{ modelType }}
  • Details
  • Validate algorithm
  • Save input
  • Load input
Display
Units

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

Calculated risk for ulcer recurrence

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

Conditional information


Model performance:
In the original study popuation (N=171), a total of 71 (41,5%) patients had a recurrent ulcer. The optimal probability cutoff point of P = 0.275 yielded an 81% sensitivity (correctly classifying the group with ulcer recurrence) and 50% specificity (correctly classifying the group without ulcer recurrence) for this model.

Model development:
This model was based on univariate and multivariate multilevel logistic regression analysis of 71 ulcer recurrences. In the multivariate analysis, a higher minor lesion index (odds ratio [OR] 9.06 [95%CI 2.98–27.57]), longer cumulative duration of past foot ulcers (1.03 [1.00–1.06]), and more day-to-day variation in stridecount (0.93 [0.89–0.99]) remained independently significantly related to ulcer recurrence.

Source:
Waaijman R, de Haart M, Arts ML, Wever D, Verlouw AJ, Nollet F, Bus SA. Risk factors for plantar foot ulcer recurrence in neuropathic diabetic patients. Diabetes Care. 2014;37(6):1697-1705.

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

This algorithm is provided for educational, training and information purposes. It must not be used to support medical decision making, or to provide medical or diagnostic services. Read our full disclaimer.

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

Algorithm feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments
On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:
{{ comment.content }}
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 algorithms.
  • Share your prediction algorithms with your colleagues, research group, organization or the world.
  • Review and provide feedback on algorithms that have been shared with you.
  • Validate your algorithms and validate algorithms from other users.
  • Find algorithms based on Title, Keyword, Author, Institute, or MeSH classification.
  • Use and save prediction algorithms and their data.
  • Use patient specific protocols and guidelines based on sequential algorithms and decision trees.
  • Stay up-to-date with new algorithms in your field as they are published.
  • Create your own lists of favorite algorithms 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 algorithms.

Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Terms & Conditions | Privacy Policy | Disclaimer | Contact | Refuse cookies |
Evidencio v3.35 © 2015 - 2025 Evidencio. All Rights Reserved