인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Background Hemodialysis (HD) treatment, the main renal replacement therapy, is accompanied by a significant environmental burden in terms of water and energy consumption and medical waste generation. Electricity consumption is an important part of the carbon footprint of hemodialysis treatment; however, direct and clear studies on the amount of electricity used per treatment in dialysis machines are lacking. Methods The electricity consumption of hemodialysis treatments of four different models of dialysis machines (4008S V10, AK200S, Dialog+, and TR8000) was measured and recorded from 1 March 2024 to 1 March 2025 using an electricity metering socket. The electricity consumption per treatment was calculated and compared between the different dialysis machines. Using multiple linear regression to analyze the relationship between electricity consumption per treatment and intake water temperature, number of treatments each day, and disinfection protocol. Results The median electricity consumption (kWh) per treatment of the four dialysis machines was 2.45, 2.60, 3.23, and 2.54, respectively. Electricity consumption per treatment varied significantly across dialysis machine models. Multiple regression revealed negative correlations between per-treatment electricity consumption and intake water temperature, daily treatment count, and disinfection protocol; the regression coefficients ( B ) were −0.113, −0.373, and −0.188, respectively, which were statistically significant. Conclusions The electricity consumption of dialysis machines per treatment is influenced by a variety of factors, of which the intake water temperature has the most significant effect. Electricity consumption differed between dialysis machine models. These differences likely stem from variations in machine design, usage, and maintenance practices.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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