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 Experiment Videos

Using the Hospital Frailty Risk Score to Predict In-Hospital Mortality Across All Ages.

Huda Kutrani1, Jim Briggs1, David Prytherch1

  • 1Centre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, UK.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

From Chatbots to MythTok: A Narrative Review of LLMs as Health Information Mediators on Social Media.

Studies in health technology and informatics·2026
Same author

Exploring User Trust and Adoption of AI Chatbots for Health and Fitness Management Across Age Groups.

Studies in health technology and informatics·2026
Same author

Aligning AI-Native 6G Healthcare Systems with EU Ethical and Legal Frameworks.

Studies in health technology and informatics·2026
Same author

Balancing Personalisation and Interoperability: An Enterprise Architecture Approach to Person-Centred Digital Health.

Studies in health technology and informatics·2026
Same author

Crucial Concepts in 'Opening the Personal Gate Between Technology and Health Care'.

Studies in health technology and informatics·2026
Same author

Laparoscopic Versus Robot-Assisted Low Anterior Resection With Mesorectal Excision For Rectal Cancer (2014-2021): A Propensity-Weighted Multicentre Cohort Study of Long-term Oncological Outcomes (RESOLUTION).

Diseases of the colon and rectum·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

The Hospital Frailty Risk Score (HFRS) effectively predicts in-hospital mortality in adult patients, outperforming the Charlson Comorbidity Index (CCI). Combining both scores offers the highest accuracy for predicting patient outcomes.

Area of Science:

  • Gerontology and Geriatric Medicine
  • Health Services Research
  • Clinical Epidemiology

Background:

  • Frailty is a significant predictor of adverse outcomes in hospitalized adults.
  • Existing comorbidity indices may not fully capture frailty-related mortality risk.
  • The Hospital Frailty Risk Score (HFRS) is a validated tool for assessing frailty in hospital settings.

Purpose of the Study:

  • To investigate the association between the Hospital Frailty Risk Score (HFRS) and in-hospital mortality.
  • To compare the predictive performance of HFRS against the Charlson Comorbidity Index (CCI).
  • To evaluate the combined predictive accuracy of HFRS and CCI for mortality.

Main Methods:

  • Retrospective cohort analysis of adult patients (≥16 years) admitted between 2010-2019.
Keywords:
AgeFrailtyHospital Frailty Risk ScoreIn-hospital mortality

Related Experiment Videos

  • HFRS calculated for patients with prior hospitalizations within two years.
  • Logistic regression models used to assess mortality prediction across nine periods; AUROC curves compared HFRS and CCI.

    • Main Results:

    • The proportion of patients with intermediate or high frailty risk increased with longer mortality prediction periods.
    • HFRS models demonstrated superior predictive accuracy (AUROC: 0.782-0.829) compared to CCI (AUROC: 0.690-0.708).
    • The combination of HFRS and CCI yielded the highest predictive accuracy for in-hospital mortality.

    Conclusions:

    • HFRS is an effective and robust predictor of in-hospital mortality across all adult age groups.
    • HFRS surpasses the predictive capability of the CCI for mortality risk assessment.
    • Combining HFRS with CCI enhances the accuracy of in-hospital mortality prediction.