A classification tree to assist with routine scoring of the Clinical Frailty Scale.
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ABSTRACT: 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.
SUBMITTER: Theou O
PROVIDER: S-EPMC7929455 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Different scales are being used to measure frailty. This study examined the convergent validity of the electronic Frailty Index (eFI) with the Clinical Frailty Scale (CFS). Method: The cross-sectional study recruited patients from three regional community nursing teams in the South East of England. The CFS was rated at recruitment, and the eFI was extracted from electronic health records (EHRs). A McNemar test of paired data was used to compare discordant pairs between the eFI and the CFS, and an exact McNemar Odds Ratio (OR) was calculated. Findings: Of 265 eligible patients consented, 150 (57%) were female, with a mean age of 85.6 years (SD = 7.8), and 78% were 80 years and older. Using the CFS, 68% were estimated to be moderate to severely frail, compared to 91% using the eFI. The eFI recorded a greater degree of frailty than the CFS (OR = 5.43, 95%CI 3.05 to 10.40; p < 0.001). This increased to 7.8 times more likely in men, and 9.5 times in those aged over 80 years. Conclusions: This study found that the eFI overestimates the frailty status of community dwelling older people. Overestimating frailty may impact on the demand of resources required for further management and treatment of those identified as being frail.
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Project description:BackgroundFrailty assessment by paramedics in the prehospital setting is understudied. The goals of this study were to assess the inter-rater reliability and accuracy of frailty assessment by paramedics using the Clinical Frailty Scale (CFS).MethodsThis was a cross-sectional study with paramedics exposed to 30 clinical vignettes created from real-life situations. There was no teaching intervention prior to the study and paramedics were only provided with the French version of the CFS (definitions and pictograms). The primary outcome was the inter-rater reliability of the assessment. The secondary outcome was the accuracy, compared with the expert-based assessment. Reliability was determined by calculating an intraclass correlation coefficient (ICC). Accuracy was assessed through a mixed effects logistic regression model. A sensitivity analysis was carried out by considering that an assessment was still accurate if the score differed from no more than 1 level.ResultsA total of 56 paramedics completed the assessment. The overall assessment was found to have good inter-rater reliability (ICC = 0.87 [95%CI 0.81-0.93]). The overall accuracy was moderate at 60.6% (95%CI 54.9-66.1) when considering the full scale. It was however much higher (94.8% [95%CI 92.0-96.7] when close assessments were considered as accurate. The only factor associated with accurate assessment was field experience.ConclusionThe assessment of frailty by paramedics was reliable in this vignette-based study. However, the accuracy deserved to be improved. Future research should focus on the clinical impact of these results and on the association of prehospital frailty assessment with patient outcomes.RegistrationThis study was registered on the Open Science Framework registries ( https://doi.org/10.17605/OSF.IO/VDUZY ).
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Project description:Background: There is no consensus on the optimal method for the assessment of frailty. We compared the prognostic utility of two approaches (modified Frailty Index [mFI], Clinical Frailty Scale [CFS]) in older adults (≥65 years) hospitalised with COVID-19 versus age. Methods: We used a test and validation cohort that enrolled participants hospitalised with COVID-19 between 27 February and 30 June 2020. Multivariable mixed-effects logistic modelling was undertaken, with 28-day mortality as the primary outcome. Nested models were compared between a base model, age and frailty assessments using likelihood ratio testing (LRT) and an area under the receiver operating curves (AUROC). Results: The primary cohort enrolled 998 participants from 13 centres. The median age was 80 (range:65-101), 453 (45%) were female, and 377 (37.8%) died within 28 days. The sample was replicated in a validation cohort of two additional centres (n = 672) with similar characteristics. In the primary cohort, both mFI and CFS were associated with mortality in the base models. There was improved precision when fitting CFS to the base model +mFI (LRT = 25.87, p < 0.001); however, there was no improvement when fitting mFI to the base model +CFS (LRT = 1.99, p = 0.16). AUROC suggested increased discrimination when fitting CFS compared to age (p = 0.02) and age +mFI (p = 0.03). In contrast, the mFI offered no improved discrimination in any comparison (p > 0.05). Similar findings were seen in the validation cohort. Conclusions: These observations suggest the CFS has superior prognostic value to mFI in predicting mortality following COVID-19. Our data do not support the use of the mFI as a tool to aid clinical decision-making and prognosis.
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