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Microbial contamination patterns in dental unit waterlines and evaluation of a centralized automated cleaning and
Tingting Yin1, Miao He2, Boyi Ma1
1State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University,Wuhan 430079, Hubei Province, China.
Objective:
This study aimed to quantitatively characterize microbial contamination patterns in dental unit waterlines (DUWLs) and to evaluate a centralized, data-driven cleaning and disinfection system in a university dental hospital.
Methods:
We conducted a cross-sectional survey combined with longitudinal monitoring of DUWL samples from 56 dental chairs in three clinical departments of a university hospital. One-way analysis of variance, Kruskal-Wallis tests, paired t tests, linear regression, correlation analysis, and multiple linear regression were used to evaluate interdepartmental differences, sampling site-specific contamination risk, temporal trends, and independent predictors. Based on the statistical findings, a centralized cleaning and disinfection system was designed and subsequently validated.
Results:
A total of 726 water samples were analyzed. Statistically significant differences in microbial colony counts were observed between departments (p < 0.001), with the Optics Valley Teeth Cleaning Center exhibiting the highest contamination levels. Significant differences were also detected among sampling points (p < 0.001), with the handpiece water outlet identified as the highest-risk location. Active dental procedures were associated with a significant increase in microbial colony counts (p < 0.001). Under conventional disinfection, contamination levels increased progressively from April to July (p < 0.01). Significant positive correlations were identified among contamination levels at different sampling points. Multiple linear regression identified month, sampling site, treatment status, and department as independent predictors of microbial contamination. Implementation of the centralized cleaning and disinfection system significantly extended the duration of compliance with established water quality standards from 1.2 ± 0.4 days to 4.1 ± 0.7 days (p < 0.001).
Conclusion:
We observed significant interdepartmental variation, site-specific contamination risk profiles, and clear temporal patterns in DUWL microbial contamination. The centralized cleaning and disinfection system, developed based on these statistical findings, significantly improved microbial control and prolonged compliance with water quality standards.
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