A clinical tool for predicting survival in ALS

201693 citationsJournal Articlehybrid Open Access

Authors

Jonathan A. Knibb · Royal Sussex County Hospital

Noa Keren · King's College London

Anna Kulka · King's College London

P. Nigel Leigh · Brighton and Sussex Medical School

Sarah Opie-Martin · King's College London

Christopher E. Shaw · King's College London

Miho Tsuda ·

Abstract

A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors.

Topics & Keywords

Amyotrophic Lateral Sclerosis Research Prion Diseases and Protein Misfolding Biochemical Acid Research Studies

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: Journal of Neurology Neurosurgery & Psychiatry

Volume 87, Issue 12, pp. 1361-1367

DOI: 10.1136/jnnp-2015-312908

Field-Weighted Citation Impact: 6.29