Frailty and short-term outcomes in elderly patients following elective noncardiac surgeries: A prospective cohort study

Zhu, Lan-yue; Ji, Mu‐Huo; Zhang, Yafei; Xia, Jiangyan; Yang, Jianjun

doi:10.1016/j.jclinane.2020.109820

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…In china, studies also showed similar results in annual healthcare costs ( 12 , 14 ). However, one study showed that there was no significant difference in hospitalized costs between frail and non-frail groups with elective non-cardiac surgeries ( 36 ), which is contrary to our results. These inconsistencies might have been due to the small sample size.…”

Section: Discussioncontrasting

confidence: 99%

Development and Validation of an Electronic Frailty Index Using Routine Electronic Health Records: An Observational Study From a General Hospital in China

Liang

Xie

et al. 2021

Front. Med.

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Background: This study aimed to develop and validate an electronic frailty index (eFI) based on routine electronic health records (EHR) for older adult inpatients and to analyze the correlations between frailty and hospitalized events and costs.Methods: We created an eFI from routine EHR and validated the effectiveness by the consistency of the comprehensive geriatric assessment-frailty index (CGA-FI) with an independent prospective cohort. Then, we analyzed the correlations between frailty and hospitalized events and costs by regressions.Results: During the study period, 49,226 inpatients were included in the analysis, 42,821 (87.0%) of which had enough data to calculate an eFI. A strong correlation between the CGA-FI and eFI was shown in the validation cohort of 685 subjects (Pearson's r = 0.716, P < 0.001). The sensitivity and specificity for an eFI≥0.15, the upper tertile, to identify frailty, defined as a CGA-FI≥0.25, were 64.8 and 88.7%, respectively. After adjusting for age, sex, and operation, an eFI≥0.15 showed an independent association with long hospital stay (odds ratio [OR] = 2.889, P < 0.001) and death in hospital (OR = 19.97, P < 0.001). Moreover, eFI values (per 0.1) were positively associated with total costs (β = 0.453, P < 0.001), examination costs (β = 0.269, P < 0.001), treatment costs (β = 0.414, P < 0.001), nursing costs (β = 0.381, P < 0.001), pharmacy costs (β = 0.524, P < 0.001), and material costs (β = 0.578, P < 0.001) after adjusting aforementioned factors.Conclusions: We successfully developed an effective eFI from routine EHR from a general hospital in China. Frailty is an independent risk factor for long hospital stay and death in hospital. As the degree of frailty increases, the hospitalized costs increase accordingly.

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Section: Discussioncontrasting

confidence: 99%

Development and Validation of an Electronic Frailty Index Using Routine Electronic Health Records: An Observational Study From a General Hospital in China

Liang

Xie

et al. 2021

Front. Med.

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“…Several small-sample studies have shown that frailty was associated with increased hospitalized costs for patients with colorectal surgery [31], cardiac surgery [32], or transcatheter aortic value implantation [33]. Another study showed that there was no difference in hospitalized costs between frail and non-frail groups in elderly patients with elective noncardiac surgeries from China [34]. These inconsistencies might have been due to the small sample size, but there might be other reasons.…”

Section: Association Between Frailty and Hospitalized Costsmentioning

confidence: 99%

Development and validation of an electronic frailty index using routine electronic health records: an observational study of 49,226 elderly inpatients from a general hospital in China

Liang

Xie

et al. 2020

Preprint

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Background Frailty assessment based on routine electronic health records (EHR) may be a good alternative to time-consuming frailty scales. This study mainly aimed to develop and validate an electronic frailty index (eFI) using routine EHR for elderly inpatients and analyse the correlations between frailty and hospitalized events and costs.Methods Based on the cumulative deficit model, we created an eFI from routine EHR. In a prospective cohort, we validated the effectiveness of the eFI by consistency with the comprehensive geriatric assessment-frailty index (CGA-FI). Then, we analysed the correlations between frailty and hospitalized events by logistic regression and costs by generalized linear regression models.Results During the study period, 49,226 elderly inpatients from the EHR were included in the analysis. There were 42,821 (87.0%) patients with sufficient data to calculate an eFI. The cut-off value for the upper tertile of the eFI for these patients was 0.15. A strong correlation between the CGA-FI and eFI was shown in the validation cohort of 685 subjects (Pearson’s r = 0.716, P < 0.001). The sensitivity and specificity for an eFI ≥ 0.15 to identify frailty defined as a CGA-FI ≥ 0.25 were 64.8% and 88.7%, respectively. After adjusting for age, gender, and operation, an eFI ≥ 0.15 showed an independent association with long hospital stay (odds ratio [OR] = 2.889, P < 0.001) and death in hospital (OR = 19.97, P < 0.001) for elderly inpatients from all departments. Moreover, after adjusting for age, gender, and operation, eFI values (per 0.1) were positively associated with total costs (β = 0.453, P < 0.001), examination costs (β = 0.269, P < 0.001), treatment costs (β = 0.414, P < 0.001), nursing costs (β = 0.381, P < 0.001), pharmacy costs (β = 0.524, P < 0.001), and material costs (β = 0.578, P < 0.001) for elderly inpatients from all departments.Conclusions It is feasible to develop an effective eFI from routine EHR for elderly inpatients from a general hospital in China. Frailty is an independent risk factor for long hospital stay and death in hospital. As the degree of frailty increases, the hospitalized costs for elderly inpatients increase accordingly.

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Frailty as a predictor of increased one-year mortality after elective non-cardiac surgery: A prospective cohort study

Zhu

Sun

Xia

et al. 2021

Journal of Clinical Anesthesia

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Frailty and short-term outcomes in elderly patients following elective noncardiac surgeries: A prospective cohort study

Cited by 4 publications

References 4 publications

Development and Validation of an Electronic Frailty Index Using Routine Electronic Health Records: An Observational Study From a General Hospital in China

Development and Validation of an Electronic Frailty Index Using Routine Electronic Health Records: An Observational Study From a General Hospital in China

Development and validation of an electronic frailty index using routine electronic health records: an observational study of 49,226 elderly inpatients from a general hospital in China

Frailty as a predictor of increased one-year mortality after elective non-cardiac surgery: A prospective cohort study

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