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State-of-the-Art Review

Effect of bioelectrical impedance technology on the prognosis of dialysis patients: a meta-analysis of randomized controlled trials

, , , , &
Article: 2203247 | Received 21 Nov 2022, Accepted 11 Apr 2023, Published online: 03 May 2023
 

Abstract

Managing patient ‘dry weight’ according to clinical standards has deficiencies. Research has focused on the effectiveness of using bioelectrical impedance technology for fluid management in dialysis patients. Whether bioelectrical impedance monitoring can improve dialysis patients prognoses remain controversial. We performed a meta-analysis of randomized controlled trials to determine whether bioelectrical impedance was effective in improving dialysis patients prognoses. The primary outcome was all-cause mortality (13.6 ± 9.1 months). Secondary outcomes were left ventricular mass index (LVMI), arterial stiffness assessed using Pulse Wave Velocity (PWV), and N-terminal brain natriuretic peptide precursor (NT-proBNP). Of 4,641 citations retrieved, we identified 15 eligible trials involving 2763 patients divided into experimental (n = 1386) and control (n = 1377) groups. In 14 studies with mortality data, the meta-analysis showed that bioelectrical impedance intervention reduced the risk of all-cause mortality (rate ratios [RR]: 0.71; 95% confidence interval [CI]: 0.51, 0.99; p = .05; I2 = 1%). Subgroup analysis of patients on hemodialysis (RR: 0.72; 95% CI: 0.42, 1.22; p = .22) and peritoneal dialysis (RR: 0.62; 95% CI: 0.35, 1.07; p = .08) showed no significant mortality difference between intervention and control groups. It reduced the risk of all-cause mortality in the Asian population (RR: 0.52; p = .02), and reduced NT-proBNP (mean difference [MD]: −1495.73; p = 0.002; I2=0%) and PWV (MD: −1.55; p = .01; I2=89%). Bioelectrical impedance intervention reduced the LVMI in hemodialysis patients (MD: −12.69; p < .0001; I2=0%). Our analysis shows that in dialysis patients, bioelectrical impedance technology intervention could reduce, but not eliminate, the risk of all-cause mortality. Overall, this technology can improve the prognosis of dialysis patients.

Acknowledgment

We would like to thank all those involved in the work.

Authors contributions

Kaibi Y drafted and revised the manuscript and collected data. Shujun P and Nan Y help to screen the literature and collect data. Yueming L drafted and revised the manuscript and designed the tables/figures, Juan W drafted and revised the manuscript. Qiang H initiated the collaboration, as well as directed, drafted, and revised the manuscript.

Ethics statement

An ethics statement is not applicable because this study is based exclusively on published literature.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Additional information

Funding

This research was supported by the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (Grant No. LHDMZ22H050001); Construction of Key Projects by Zhejiang Provincial Ministry (Project No. WKJ-ZJ-2017), Zhejiang Province Chinese Medicine Modernization Program (Project No. 2020ZX001), Key Project of Scientific Research Foundation of Chinese Medicine (2022ZZ002), Key project of Zhejiang Science and Technology Department (202203118), and Key project of Basic Scientific Research Operating Funds of Hangzhou Medical College (KYZD202002).