The Almelo Hip Fracture Score (AHFS) - Evidencio
The Almelo Hip Fracture Score (AHFS)
The AHFS can identify frail elderly at high risk of early mortality following hip fracture surgery accurately. With the AHFS, the patient can be classified into the low, medium or high risk group, which contributes to enhanced quality of care in clinical practice.

Note: The AHFS score still needs further (external) validation, and clinical evaluation before it can support decision making. 
Research authors: W.S. Nijmeijer, E.C. Folbert, M. Vermeer, J.P. Slaets, J.H. Hegeman
Version: 1.11
  • Public
  • Traumatology
  • {{ modelType }}
  • Details
  • Validate algorithm
  • Save input
  • Load input
Display
Units

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

Predicted risk of early mortality is: %

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

Conditional information

The AHFS showed a good discrimination with an area under the curve (AUC) of 0.82 on internal validation, and was higher than the adjusted Nottingham Hip Fracture Score (NHFS-a), which showed an AUC of 0.72. 

The AHFS identifies patients at low, medium, and high risk using the following thresholds: 

  • Low risk: AHFS ≤9 points
  • Medium risk: AHFS 10-12 points
  • High risk: AHFS ≥13 points
The 9 point threshold (low risk) represents a sensitivity of 78.1%, specificity of 72.5%, PPV of 18.8%, and a NPV of 97.6% in comparison with the other groups.
The 13 point threshold (high risk) represents a sensitivity of 42.2%, specificity of 92.5%, PPV of 31.4%, and a NPV of 95.2% in comparison with the other groups.

{{ 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