z-logo
open-access-imgOpen Access
A classification tree to assist with routine scoring of the Clinical Frailty Scale
Author(s) -
Olga Theou,
Mario Ulises PérezZepeda,
Alexandra M van der Valk,
Samuel D. Searle,
Susan E. Howlett,
Kenneth Rockwood
Publication year - 2021
Publication title -
age and ageing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.014
H-Index - 143
eISSN - 1468-2834
pISSN - 0002-0729
DOI - 10.1093/ageing/afab006
Subject(s) - medicine , intraclass correlation , decision tree , rating scale , scoring system , decision tree learning , machine learning , psychometrics , clinical psychology , psychology , computer science , developmental psychology
Background the Clinical Frailty Scale (CFS) was originally developed to summarise a Comprehensive Geriatric Assessment and yield a care plan. Especially since COVID-19, the CFS is being used widely by health care professionals without training in frailty care as a resource allocation tool and for care rationing. CFS scoring by inexperienced raters might not always reflect expert judgement. For these raters, we developed a new classification tree to assist with routine CFS scoring. Here, we test that tree against clinical scoring. Objective/Methods we examined agreement between the CFS classification tree and CFS scoring by novice raters (clerks/residents), and the CFS classification tree and CFS scoring by experienced raters (geriatricians) in 115 older adults (mean age 78.0 ± 7.3; 47% females) from a single centre. Results the intraclass correlation coefficient (ICC) for the CFS classification tree was 0.833 (95% CI: 0.768–0.882) when compared with the geriatricians’ CFS scoring. In 93%, the classification tree rating was the same or differed by at most one level with the expert geriatrician ratings. The ICC was 0.805 (0.685–0.883) when CFS scores from the classification tree were compared with the clerk/resident scores; 88.5% of the ratings were the same or ±1 level. Conclusions a classification tree for scoring the CFS can help with reliable scoring by relatively inexperienced raters. Though an incomplete remedy, a classification tree is a useful support to decision-making and could be used to aid routine scoring of the CFS.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom