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Observational Study
. 2021 Jul 25;18(14):3309-3317.
doi: 10.7150/ijms.51569. eCollection 2021.

Severity of frailty as a significant predictor of mortality for hemodialysis patients: a prospective study in China

Affiliations
Observational Study

Severity of frailty as a significant predictor of mortality for hemodialysis patients: a prospective study in China

Wenjing Fu et al. Int J Med Sci. .

Abstract

Background: Frailty is known to be highly prevalent in older hemodialysis (HD) patients. We studied the prevalence of frailty and its associated factors in Chinese HD patients. We further studied if frailty could predict survival in HD patients. Methods: This is a prospective study involving patients receiving maintenance HD in the dialysis center of Xuanwu Hospital, Beijing. Study subjects were enrolled from October to December, 2017 and followed up for two years. Demographic data, comorbidities and biological parameters were collected. Frailty was assessed using the Fried frailty phenotype at baseline. Cox regression analysis was performed to identify the relationship between frailty and mortality in HD patients. Kaplan-Meier was plotted using the cutoff value obtained by ROC curve to evaluate survival rates in different frailty status. Results: Total of 208 HD patients were enrolled with a mean age of 60.5±12.7 years. According to the frailty criteria, at baseline the prevalence of robust, pre-frail and frail in HD patients was 28.7%, 45.9%, and 25.4%, respectively. The two-year all-cause mortality was 18.8% (39/207) and underlying causes of death included coronary artery disease (CAD), cerebrovascular disease (CVD), hyperkalemia, severe infection, malignant tumor and others. Survival curve showed the patients with frailty score ≥4 to have significantly shorter survival time as compared to patients with frailty score ≤ 3. Frailty predicted two-year mortality when frailty score ≥4 with a sensitivity of 70% and a specificity of 83.67% with an AUC of 0.819. Frailty score was positively associated with age and ratio of ultrafiltration volume to dry weight, while negatively associated with levels of serum albumin, uric acid and diastolic blood pressure after HD. Conclusions: Our results confirm frailty to be very common among HD patients and severity of frailty was a significant predictor of mortality for HD patients. Factors such as age, malnutrition and low blood pressure are the factors to be associated with frailty. Interdialytic weight gain inducing excessive ultrafiltration volume is an important risk factor.

Keywords: Aging; Chinese; Frail; Hemodialysis; Mortality; Ultrafiltration volume.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Prevalence of frailty according to age groups.
Figure 2
Figure 2
Plot versus criterion values based on frailty score in predicting two-year mortality of HD patients. Notes: Data of frailty score are presented as numbers and death is set as 1, survival is set as 0.
Figure 3
Figure 3
A Kaplan-Meier curve based on frailty scores and mortality. Note: Frailty score≥4 is set as 1, <4 is set as 0; death is set as 1, survival is set as 0. OR of frailty score≥4 is 1.680 (95%CI:15.025-21.612); OR of frailty score<4 is 0.675 ( 95%CI: 22.365-25.013). P=0.001. B Survival curve based on frailty scores and mortality after adjusted for covariates. Covariates include age, ratio of ultrafiltration volume to dry weight, Hb and CAD. Data of frailty score are presented as numbers and death is set as 1, survival is set as 0. Note: Frailty score≥4 is set as 1, <4 is set as 0; death is set as 1, survival is set as 0. OR of frailty score≥4 is 1.673 (95%CI:16.109-21.633); OR of frailty score<4 is 0.690 (95%CI: 22.307-25.011). P=0.001.
Figure 3
Figure 3
A Kaplan-Meier curve based on frailty scores and mortality. Note: Frailty score≥4 is set as 1, <4 is set as 0; death is set as 1, survival is set as 0. OR of frailty score≥4 is 1.680 (95%CI:15.025-21.612); OR of frailty score<4 is 0.675 ( 95%CI: 22.365-25.013). P=0.001. B Survival curve based on frailty scores and mortality after adjusted for covariates. Covariates include age, ratio of ultrafiltration volume to dry weight, Hb and CAD. Data of frailty score are presented as numbers and death is set as 1, survival is set as 0. Note: Frailty score≥4 is set as 1, <4 is set as 0; death is set as 1, survival is set as 0. OR of frailty score≥4 is 1.673 (95%CI:16.109-21.633); OR of frailty score<4 is 0.690 (95%CI: 22.307-25.011). P=0.001.

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References

    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. Fried LP, Ferrucci L, Darer J, Williamson JD, Anderson G. Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci. 2004;59(3):255–63. - PubMed
    1. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752–62. - PMC - PubMed
    1. McAdams-DeMarco MA, Suresh S, Law A, Salter ML, Gimenez LF, Jaar BG. et al. Frailty and falls among adult patients undergoing chronic hemodialysis: a prospective cohort study. BMC Nephrol. 2013;14:224. - PMC - PubMed
    1. Kim SW, Han HS, Jung HW, Kim KI, Hwang DW, Kang SB. et al. Multidimensional frailty score for the prediction of postoperative mortality risk. JAMA Surg. 2014;149(7):633–40. - PubMed

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