Developing an electronic surprise question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions
This study is unique in methodology with prospectively evidenced outcomes. The model algorithm allocated GSFSQ equivalent EOL prognosis universally to a cohort of acutely admitted patients with statistical accuracy validated against prospective mortality outcomes.
Authors
- Vijay Klaire
- Baldev Singh (ORCID: https://orcid.org/0000-0003-3460-6759)
- Hannah Jennens
- Emma Parry (ORCID: https://orcid.org/0000-0003-0278-6898)
- Adam Ryder (ORCID: https://orcid.org/0009-0004-9976-711X)
- Mona Sidhu
- Nisha Kumari-Dewat (ORCID: https://orcid.org/0009-0008-3030-006X)
- K. M. Ahasan Ahmed
- Ananth Viswanath
Institutions
- New Cross Hospital (GB)
- Leverhulme Trust (GB)
- Wolverhampton Hospital (GB)
- Keele University (GB)
Publication Details
- Journal
- Clinical Medicine
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1016/j.clinme.2025.100292
- Citations
- 2
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 2.71
Funders
- National Institute for Health and Care Research