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. 2023 May 1;37(6):967-975.
doi: 10.1097/QAD.0000000000003501. Epub 2023 Jan 31.

Development of Frail RISC-HIV: a Risk Score for Predicting Frailty Risk in the Short-term for Care of People with HIV

Stephanie A Ruderman  1 , Robin M Nance  1 , Lydia N Drumright  1 , Bridget M Whitney  1 , Andrew W Hahn  1 , Jimmy Ma  1 , Lara Haidar  2 , Sherif Eltonsy  2 , Kenneth H Mayer  3 , Joseph J Eron  4 , Meredith Greene  5 , William C Mathews  6 , Allison Webel  1 , Michael S Saag  7 , Amanda L Willig  7 , Charles Kamen  8 , Mary McCaul  9 , Geetanjali Chander  1   9 , Edward Cachay  6 , William B Lober  1 , Chintan Pandya  9 , Francisco Cartujano-Barrera  8 , Stephen B Kritchevsky  10 , Steven N Austad  7 , Alan Landay  11 , Mari M Kitahata  1 , Heidi M Crane  1 , Joseph A C Delaney  2
Affiliations

Development of Frail RISC-HIV: a Risk Score for Predicting Frailty Risk in the Short-term for Care of People with HIV

Stephanie A Ruderman et al. AIDS. .

Abstract

Objective: Frailty is common among people with HIV (PWH), so we developed frail risk in the short-term for care (RISC)-HIV, a frailty prediction risk score for HIV clinical decision-making.

Design: We followed PWH for up to 2 years to identify short-term predictors of becoming frail.

Methods: We predicted frailty risk among PWH at seven HIV clinics across the United States. A modified self-reported Fried Phenotype captured frailty, including fatigue, weight loss, inactivity, and poor mobility. PWH without frailty were separated into training and validation sets and followed until becoming frail or 2 years. Bayesian Model Averaging (BMA) and five-fold-cross-validation Lasso regression selected predictors of frailty. Predictors were selected by BMA if they had a greater than 45% probability of being in the best model and by Lasso if they minimized mean squared error. We included age, sex, and variables selected by both BMA and Lasso in Frail RISC-HIV by associating incident frailty with each selected variable in Cox models. Frail RISC-HIV performance was assessed in the validation set by Harrell's C and lift plots.

Results: Among 3170 PWH (training set), 7% developed frailty, whereas among 1510 PWH (validation set), 12% developed frailty. BMA and Lasso selected baseline frailty score, prescribed antidepressants, prescribed antiretroviral therapy, depressive symptomology, and current marijuana and illicit opioid use. Discrimination was acceptable in the validation set, with Harrell's C of 0.76 (95% confidence interval: 0.73-0.79) and sensitivity of 80% and specificity of 61% at a 5% frailty risk cutoff.

Conclusions: Frail RISC-HIV is a simple, easily implemented tool to assist in classifying PWH at risk for frailty in clinics.

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Conflict of interest statement

Conflicts of interest: The authors report no potential conflicts of interest, including relevant financial interests, activities, relationships, and affiliations.

Figures

Figure 1.
Figure 1.
Receiver operating characteristics (ROC) curve for the Frail RISC-HIV, with notable cutoffs indicated for percent risk of becoming frail Abbreviations: Frailty Risk in the Short-term for Care of PWH, Frail RISC-HIV
Figure 2.
Figure 2.
Lift plot (by decile) of frailty risk per 1000 in the validation set vs training set
See this image and copyright information in PMC

References

    1. Morley JE, Vellas B, van Kan GA, Anker SD, Bauer JM, Bernabei R, et al. Frailty consensus: a call to action. J Am Med Dir Assoc. 2013;14(6):392–7. - PMC - PubMed
    1. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–56. - PubMed
    1. Falutz J Frailty in People Living with HIV. Curr HIV/AIDS Rep. 2020;17(3):226–36. - PubMed
    1. Levett TJ, Cresswell FV, Malik MA, Fisher M, Wright J. Systematic Review of Prevalence and Predictors of Frailty in Individuals with Human Immunodeficiency Virus. J Am Geriatr Soc. 2016;64(5):1006–14. - PubMed
    1. Thurn M, Gustafson DR. Faces of Frailty in Aging with HIV Infection. Curr HIV/AIDS Rep. 2017;14(1):31–7. - PMC - PubMed

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