ArticleBiomedical engineering online2025
Hemodialysis equipment malfunction incidence and risk profiling in clinical settings: a retrospective single-center cohort analysis.
Article in Biomedical engineering online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundHemodialysis equipment alarms significantly impact clinical workflow and patient safety. This study aimed to characterize alarm patterns, identify risk factors, and evaluate management effectiveness in hemodialysis facilities.
methodsA retrospective cohort analysis was conducted at 1 hemodialysis center from January 2020 to December 2023. Equipment alarm data from hemodialysis stations (Nikkiso, Gambro, and B.Braun) were systematically collected and analyzed. Multivariate regression and machine learning approaches identified risk factors and developed predictive model.
resultsAmong 4231 recorded alarm events over 32 months, the monthly alarm rate averaged 132.2 ± 54.4 events. The COVID-19 pandemic period (2020-2021) accounted for 82.2% of alarms, with a significant 78.3% reduction post-pandemic (P = 0.022). B.Braun equipment generated 68.7% of alarms, significantly higher than Gambro (21.2%) and Nikkiso (10.1%) devices (P < 0.001). Engineering analysis revealed B.Braun's lower pressure thresholds (150 vs. 180 mmHg), higher sensor sensitivity (1 vs. 2-5 mmHg resolution), and conservative air detection algorithms (0.3 vs. 0.5 mL) contributed to increased alarm frequency. Pressure-related alarms predominated (37.4%), while 94.5% occurred during active treatment phases. Vascular access complications contributed to 19.8% of events, with permanent catheters being the primary source (47.3%). Patient-related factors accounted for 83.6% of human factor contributions. Patients with BMI > 30 kg/m
conclusionsEquipment-specific alarm patterns and human factors significantly influence hemodialysis alarm burden. Implementation of predictive analytics and targeted interventions substantially improves alarm management effectiveness and clinical outcomes.
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