Adaptation of the Risk Analysis Index for Frailty Assessment Using Diagnostic Codes.
JAMA Netw Open
; 7(5): e2413166, 2024 May 01.
Article
em En
| MEDLINE
| ID: mdl-38787554
ABSTRACT
Importance Frailty is associated with adverse outcomes after even minor physiologic stressors. The validated Risk Analysis Index (RAI) quantifies frailty; however, existing methods limit application to in-person interview (clinical RAI) and quality improvement datasets (administrative RAI). Objective:
To expand the utility of the RAI utility to available International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) administrative data, using the National Inpatient Sample (NIS). Design, Setting, andParticipants:
RAI parameters were systematically adapted to ICD-10-CM codes (RAI-ICD) and were derived (NIS 2019) and validated (NIS 2020). The primary analysis included survey-weighed discharge data among adults undergoing major surgical procedures. Additional external validation occurred by including all operative and nonoperative hospitalizations in the NIS (2020) and in a multihospital health care system (UPMC, 2021-2022). Data analysis was conducted from January to May 2023. Exposures RAI parameters and in-hospital mortality. Main Outcomes andMeasures:
The association of RAI parameters with in-hospital mortality was calculated and weighted using logistic regression, generating an integerized RAI-ICD score. After initial validation, thresholds defining categories of frailty were selected by a full complement of test statistics. Rates of elective admission, length of stay, hospital charges, and in-hospital mortality were compared across frailty categories. C statistics estimated model discrimination.Results:
RAI-ICD parameters were weighted in the 9â¯548â¯206 patients who were hospitalized (mean [SE] age, 55.4 (0.1) years; 3â¯742â¯330 male [weighted percentage, 39.2%] and 5â¯804â¯431 female [weighted percentage, 60.8%]), modeling in-hospital mortality (2.1%; 95% CI, 2.1%-2.2%) with excellent derivation discrimination (C statistic, 0.810; 95% CI, 0.808-0.813). The 11 RAI-ICD parameters were adapted to 323 ICD-10-CM codes. The operative validation population of 8â¯113â¯950 patients (mean [SE] age, 54.4 (0.1) years; 3â¯148â¯273 male [weighted percentage, 38.8%] and 4â¯965â¯737 female [weighted percentage, 61.2%]; in-hospital mortality, 2.5% [95% CI, 2.4%-2.5%]) mirrored the derivation population. In validation, the weighted and integerized RAI-ICD yielded good to excellent discrimination in the NIS operative sample (C statistic, 0.784; 95% CI, 0.782-0.786), NIS operative and nonoperative sample (C statistic, 0.778; 95% CI, 0.777-0.779), and the UPMC operative and nonoperative sample (C statistic, 0.860; 95% CI, 0.857-0.862). Thresholds defining robust (RAI-ICD <27), normal (RAI-ICD, 27-35), frail (RAI-ICD, 36-45), and very frail (RAI-ICD >45) strata of frailty maximized precision (F1 = 0.33) and sensitivity and specificity (Matthews correlation coefficient = 0.26). Adverse outcomes increased with increasing frailty. Conclusion and Relevance In this cohort study of hospitalized adults, the RAI-ICD was rigorously adapted, derived, and validated. These findings suggest that the RAI-ICD can extend the quantification of frailty to inpatient adult ICD-10-CM-coded patient care datasets.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Classificação Internacional de Doenças
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Mortalidade Hospitalar
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Fragilidade
Limite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
País/Região como assunto:
America do norte
Idioma:
En
Revista:
JAMA Netw Open
Ano de publicação:
2024
Tipo de documento:
Article
País de publicação:
Estados Unidos