This study evaluates a combined manual pre-treatment and negative-pressure cleaning process for dental implant instruments, demonstrating improved cleaning quality and higher qualification rates while significantly reducing manual operation time. The approach enhances standardization, efficiency, and safety in instrument reprocessing, supporting its practical adoption in clinical sterilization workflows.
Research Article
Clinical Evaluation of Combined Manual Pre-treatment and Negative-Pressure Cleaning for Dental Implant Instrument Reprocessing
In This Article
Summary
Abstract
This study evaluates a combined manual pre-treatment and negative-pressure cleaning process for dental implant instruments to improve cleaning quality and efficiency. A total of 200 contaminated dental implant toolkits were randomly assigned to a control group (traditional manual cleaning) or an experimental group (manual pre-treatment combined with negative-pressure cleaning), with 100 toolkits in each group. Cleaning quality was assessed using visual inspection, magnification, residual blood detection, and ATP fluorescence testing, and cleaning time was recorded.
The experimental group demonstrated higher qualification rates across multiple indicators compared to the control group, including improved outcomes under magnification and residual blood testing, as well as a higher complete qualification rate. Manual cleaning time was significantly reduced in the experimental group (6.48 ± 2.78 min) compared to the control group (28.94 ± 2.57 min). Although total processing time increased due to automated cleaning cycles, manual handling time was markedly reduced.
Overall, the combined approach improves cleaning quality, reduces manual workload, and enhances standardization. This approach enhances efficiency, standardization, and safety in clinical instrument reprocessing.
Introduction
With the continuous development of dental implant technology, implants have become an important treatment option for patients with missing teeth due to their excellent restorative function and aesthetic appeal. The instruments used in implant surgeries have complex structures and intricate geometries, which place high demands on cleaning quality1. Inadequate cleaning can result in residual organic or inorganic materials that not only affect the effective contact of sterilization agents2,3 but also form bacterial biofilms, reducing sterilization effectiveness and potentially causing hospital-associated infections, thus threatening patient safety4. Cleaning is a critical prerequisite for effective disinfection and sterilization of reusable medical devices, particularly those with complex geometries and lumens, as retained organic soil (e.g., protein and blood) can persist despite apparent cleanliness and compromise downstream sterilization performance5.
These processes are essential to remove organic and inorganic contaminants and reduce microbial load, thereby supporting safe and effective instrument reprocessing in high-risk clinical settings6.
Furthermore, improper cleaning may cause instrument damage, shorten their lifespan, and increase maintenance and replacement costs7. Dental implant instrument sets usually include various instruments, such as implants, drills, and guide sleeves, along with their specialized containers, making cleaning significantly more challenging than for regular surgical instruments. Complex design features (e.g., narrow lumens or intricate shapes) have been shown to act as barriers to effective cleaning, increasing the risk of residual soil and biofilm accumulation even after manual or semi-automated cleaning processes1.
Currently, most Central Sterile Supply Departments (CSSDs) still use manual scrubbing or spraying disinfectants for cleaning, which has issues such as low efficiency, long cleaning times, high personnel dependence, and inconsistent execution, making implant instruments a major challenge in clinical cleaning work8. Previous studies have consistently reported persistent contamination in complex instruments despite standard cleaning procedures, with residual organic and microbial contamination frequently detected even after routine reprocessing, particularly in devices with intricate geometries and lumens that hinder effective cleanings9,10. Although multiple automated and semi-automated cleaning technologies have been introduced to improve consistency and reduce dependence on manual performance, studies indicate that residual soil/debris within lumened or complex instruments remains a persistent problem in real-world reprocessing, even after routine cleaning, supporting the need for improved methods and objective verification in CSSD settings9,11. However, standardized and validated cleaning strategies for dental implant instrument sets remain limited.
Recent advances in automated reprocessing systems, including ultrasonic-assisted and washer–disinfector technologies, have improved standardization; however, their effectiveness may still be limited in removing tightly adhered contaminants within narrow lumens or complex instrument geometries due to incomplete fluid penetration and insufficient mechanical disruption under standard pressure conditions12,13.
In addition, reports focusing on CSSD quality and safety continue to document operational challenges that reinforce the need for workflow standardization and technology-supported cleaning approaches, including clear manufacturer instructions and validated reprocessing procedures tailored for instrument complexity14. While pulsed vacuum/negative‑pressure cleaning devices have gained increasing attention, evidence specific to dental implant instrument sets remains limited, and comparative evaluations using multiple cleaning quality indicators and time‑efficiency metrics are still insufficient. Therefore, a clear research gap exists regarding the effectiveness of pressure-assisted automated cleaning systems specifically for dental implant instrument sets, particularly in terms of their ability to improve cleaning consistency, reduce manual workload, and enhance cleaning outcomes across multiple objective indicators.
This study aims to systematically evaluate a combined manual pre-treatment and negative-pressure cleaning workflow for dental implant instrument sets, which enhances fluid penetration and contaminant removal in complex instrument geometries, with the goal of improving cleaning quality, reducing manual workload, and enhancing process standardization in CSSD practice.
Based on preliminary clinical application, a combined manual pre-treatment and negative-pressure cleaning approach has shown potential to improve cleaning efficiency and reduce manual operation time; therefore, this study systematically evaluates its effectiveness in improving cleaning quality, reducing manual workload, and enhancing process standardization. Unlike conventional automated cleaning systems, the proposed approach integrates manual pre-treatment with negative-pressure-assisted cleaning, which enhances fluid penetration, promotes cavitation effects, and enables pressure-driven flushing within narrow lumens and facilitates more effective removal of contaminants from complex surfaces and internal lumens. This study conducts a comparative evaluation of this method to determine its effectiveness in clinical instrument reprocessing.
Protocol
Study Design and Ethical Considerations
This study was reviewed by the Ethics Committee of the Affiliated Stomatological Hospital of Anhui Medical University and was determined not to require formal ethical approval, as it involved only the reprocessing of medical instruments and did not include patient interaction or identifiable patient data. The study was conducted in accordance with institutional guidelines and relevant regulations. Accordingly, the requirement for informed consent was waived.
From July to December 2024, a total of 200 dental implant instrument sets were retrieved from the Disinfection Supply Center of the Affiliated Stomatological Hospital of Anhui Medical University. These were randomly divided into two groups using a random number table: the control group (traditional manual cleaning) and the experimental group (manual pre-treatment combined with a negative-pressure cleaning device), with 100 instrument sets in each group.
This study was designed as a prospective, randomized comparative study conducted under routine Central Sterile Supply Department (CSSD) operational conditions. Dental implant instrument sets (typically consisting of implant drills, guide sleeves, implant drivers, torque wrenches, and associated surgical accessories; composition varied depending on clinical procedure requirements), including variations in instrument geometry such as smooth surfaces, hinged components, and narrow lumens that may influence cleaning difficulty, were included in the study.
Randomization and Blinding
Randomization was performed using a computer-generated random number table to ensure equal allocation of instrument sets between the two groups. Allocation was conducted by a designated staff member not involved in outcome assessment. Cleaning quality evaluations were performed by trained personnel blinded to group assignment (evaluators were independent of the cleaning procedures and not involved in group allocation. Instrument sets were coded prior to evaluation to ensure blinding, and all assessments were conducted under standardized conditions using predefined evaluation criteria).
Cleaning Equipment and Procedures
One manual cleaning workstation (including washing tank, enzymatic cleaning tank, rinsing tank, and final rinsing tank), one ultrasonic cleaning machine (frequency: 40 kHz; temperature: 40–45 °C), one negative-pressure cleaning and disinfection device (vacuum level: -0.08 to -0.095 MPa; operating temperature: 48–62 °C; ultrasonic frequency: 40 kHz; cycle duration: 58 min; pulse cleaning mode enabled), one boiling machine (93 °C ± 1 °C), one drying cabinet (70–80 °C), one set of pressure steam spray guns with auxiliary devices, three high-pressure water guns (pressure: 0.2–0.3 MPa), and three calibrated digital timers. The negative-pressure cleaning and disinfection device operates based on vacuum-assisted cleaning principles, enhancing fluid penetration, ultrasonic cavitation, and pulse-driven flushing to improve contaminant removal.
All cleaning procedures were performed by trained CSSD personnel with ≥ 2 years of experience, following institutional protocols to minimize operator-dependent variability and ensure consistent execution across procedures.
Cleaning Method for the Control Group
The recovered implant instrument sets were first categorized and disassembled into their smallest components, followed by rinsing under running water for 2–3 min (flow rate ~2 L·min-1) to remove visible contaminants. All manual cleaning steps were performed according to standardized operating procedures by trained personnel to ensure consistency across operators. The instruments were then manually brushed using a soft nylon brush (diameter 2–5 mm depending on lumen size) to remove residual debris like blood stains and rust. This was followed by immersion in a multi-enzyme cleaning solution (3.75 mL·1000 mL-1; temperature: 35–40 °C) and brushing for 6 min (timed using a calibrated timer). Enzymatic cleaning was followed by intensive rinsing using a high-pressure water gun (0.2–0.3 MPa; 2–3 min) to remove chemical residues. A final rinse with purified water was performed for ≥ 1 min. This was followed by wet heat disinfection at 93 °C for 2.5 min. Finally, the instruments were dried in a drying cabinet (70–80 °C) and transferred to the inspection and packaging area.
Cleaning Method for the Experimental Group
The recovered implant instrument sets were first categorized and disassembled into their smallest components and rinsed under running water (2–3 min) to remove visible contaminants. The instruments were then subjected to primary cleaning using a negative-pressure cleaning and disinfection device for 58 min based on vacuum-assisted cavitation, pulse flushing, and perfusion mechanisms to enhance cleaning of internal lumens and complex geometries (standardized cycle including vacuum ultrasonic cleaning, pulse flushing, vacuum perfusion, and vacuum drying). Operational parameters were as follows: Vacuum level: -0.08 to -0.095 MPa; Temperature: 48–62 °C, and Ultrasonic frequency: 40 kHz, which were selected to optimize cavitation intensity, fluid penetration, and contaminant removal efficiency under reduced-pressure conditions. Instruments that failed to meet the required cleanliness standards after the initial cycle underwent secondary cleaning using the same negative-pressure cleaning and disinfection procedure, followed by routine inspection. If the instruments still did not meet the qualification standards after secondary cleaning, a tertiary cleaning cycle was performed using the same method, and this process was repeated until all instruments complied with the established quality standards, ensuring consistent cleaning performance across repeated cycles under controlled pressure-assisted conditions.
Observation Indicators
The cleaning efficiency indicator is cleaning time measured in minutes using calibrated digital timers and recorded for each cleaning stage, including manual cleaning time for the first cleaning, total cleaning time for the first cleaning, manual cleaning time for the secondary cleaning, total cleaning time for the secondary cleaning, manual cleaning time for fully qualified cleaning, and total cleaning time for fully qualified cleaning.
Cleaning time was recorded using calibrated digital timers. Manual cleaning time was defined as the duration from initiation of manual handling to completion of manual cleaning steps. Total cleaning time was defined as the duration from initial rinsing to completion of drying. For instruments requiring repeated cleaning cycles, time was recorded cumulatively until qualification criteria were achieved.
Cleaning quality was evaluated using visual observation, five-fold magnification lens detection, residual blood testing, and ATP fluorescence testing using predefined and standardized thresholds for cleanliness assessment to ensure objective and reproducible evaluation15. The cleaning quality indicators are the qualification rate expressed as percentages of instrument sets meeting predefined criteria, including the qualification rate for the first cleaning and the qualification rate for the secondary cleaning. Visual observation is performed using a magnifying lens with light to check for visible blood stains, dirt, water scale, and rust on the surface of the instruments; those without such visible contaminants are considered qualified. Instruments were inspected under standardized lighting conditions (≥ 1000 lux (measured using a calibrated lux meter to ensure standardized inspection conditions)) at a distance of approximately 30 cm. ATP fluorescence testing was performed by swabbing predefined instrument surfaces and lumens, followed by measurement using an ATP luminometer. Results were obtained within 30 s, and values ≤ 45 RLU were considered qualified.
Complete qualification was defined as an instrument passing all four assessment methods simultaneously: visual observation, 5× magnification visual observation, residual blood detection, and ATP fluorescence detection. Instruments failing any one of these criteria were classified as not completely qualified.
Definitions and Descriptions of Various Observation Methods
Visual Observation: Visual inspection was performed using the naked eye to detect visible contaminants such as blood stains, dirt, water scale, and rust on instrument surfaces16.
Inspection was performed using a 5× magnifying lens to detect smaller contaminants on instrument surfaces and within lumens17.
For residual blood detection method, a sterile swab was used to sample the instrument surface (~2 cm2), followed by application of detection solution according to the manufacturer’s instructions. A color change within 30 s was considered a positive result, while absence of color change was considered qualified.
A sterile swab was applied to predefined instrument surfaces and lumens and inserted into an ATP detector to measure Relative Light Units (RLU)18. This method evaluates cleaning effectiveness by measuring ATP content, as all living cells contain a constant amount of ATP, and ATP is released when bacterial cells lyse19,20. An RLU value ≤ 45 was considered qualified21.
Process Checkpoints
After each cleaning cycle, instruments were evaluated using visual and instrumental methods. Instruments failing any criterion were subjected to subsequent cleaning cycles until qualification standards were met.
Reproducibility Consideration
All procedures were conducted under controlled CSSD conditions using standardized workflows and predefined equipment parameters to ensure reproducibility across repeated trials, including minimized operator-dependent variation through standardized training and protocol adherence.
Safety Considerations
All contaminated instruments were handled using appropriate personal protective equipment, including gloves, masks, and protective eyewear. High-pressure rinsing procedures were performed with splash protection to minimize occupational exposure.
Waste Disposal
Used cleaning solutions and contaminated materials were disposed of in accordance with institutional biomedical waste management protocols and local regulatory requirements.
Statistical Methods
Statistical analysis of the data was performed using SPSS software. Categorical data were expressed as frequency and composition ratio (%), and group comparisons were conducted using the χ2 test or Fisher’s exact probability test. Continuous data were expressed as mean ± standard deviation (x̄ ± s), and group comparisons were made using independent sample t-tests (after confirming normality of data distribution using the Shapiro–Wilk test). Homogeneity of variance was assessed using Levene’s test prior to application of the t-test. The significance level was set at α = 0.05, with two-tailed testing. A p-value < 0.05 was considered statistically significant. All materials and equipment used in this study are listed in the Table of Materials.
Results
Comparison of Cleaning Quality Between the Two Groups
In visual observation, the qualification rate of the control group was 94%, while the qualification rate of the experimental group was 99% (Table 1; Figure 1). The difference between the two groups was not statistically significant (χ2 = 1.546, p = 0.214). In the 5x magnification visual observation, the qualification rate was significantly higher in the experimental group compared with the control group (χ2 = 8.791, p = 0.003). In the residual blood detection method, the qualification rate was significantly higher in the experimental group (χ2 = 11.971, p = 0.001). In the ATP fluorescence detection method, the qualification rate was higher in the experimental group (χ2 = 3.191, p = 0.074). Regarding the complete qualification rate (defined as the instrument sets that passed all four assessment methods), the experimental group demonstrated a markedly higher qualification rate compared with the control group (χ2 = 19.908, p < 0.001)
Post hoc power analysis (G*Power 3.1.9.7, χ2 contingency table test, α = 0.05) revealed that the current sample size (n = 200) achieved a power of 0.84 for 5x magnification inspection (Cohen w = 0.210), a power of 0.93 for residual blood testing (Cohen w = 0.245), and a power of 0.99 for overall qualification (Cohen w = 0.316), while the powers for visual observation and ATP-bioluminescence comparisons were 0.25 and 0.54, respectively (Supplementary Table 1). These findings indicate improved detection sensitivity and reliability in the experimental group.
Figure 1: Cleaning quality assessment across detection methods in control and experimental groups (n = 200). The figure shows the distribution of instrument sets meeting qualification criteria across four detection methods: visual observation, 5× magnification inspection, residual blood detection, and ATP (adenosine triphosphate) fluorescence detection. The x-axis represents the number of instrument sets (n), and the y-axis represents detection methods. The lower panel illustrates intersection analysis of combined qualification outcomes, where connected dots indicate simultaneous satisfaction of multiple criteria. The experimental group demonstrates higher rates of combined qualification across detection methods compared to the control group. Please click here to view a larger version of this figure.
Statistical Comparison of Cleaning Performance Between Groups
Effect sizes for key cleaning quality indicators are presented in Table 2 and Figure 2, including 5× magnification inspection, residual blood detection, and complete qualification rate. Time-related outcomes and corresponding effect sizes are summarized in Table 2.
Figure 2: Effect size analysis of cleaning quality and efficiency outcomes. (A) Effect sizes (Cohen’s d) for cleaning quality indicators, including visual observation, 5× magnification inspection, residual blood detection, ATP fluorescence detection, and complete qualification rate. The x-axis represents outcome variables, and the y-axis represents effect size. (B) Effect sizes for time-related efficiency outcomes, including manual and total cleaning time for first and complete cleaning cycles. Dashed lines indicate standard thresholds for effect size interpretation. Larger effect sizes indicate greater differences between groups. Please click here to view a larger version of this figure.
Comparison of Cleaning Efficiency Between the Two Groups
In terms of cleaning time, the manual cleaning time during the first cleaning cycle was significantly lower in the experimental group compared with the control group (28.94 ± 2.57 min vs. 6.48 ± 2.78 min) (Table 3; t = 59.25, p < 0.001). For the total time of the first cleaning, the experimental group required a significantly longer duration than the control group (31.44 ± 2.57 min vs. 64.48 ± 2.78 min) (t = -87.16, p < 0.001). Regarding complete cleaning, the manual cleaning time remained significantly lower in the experimental group (40.07 ± 15.73 min vs. 6.69 ± 2.79 min), whereas total processing time was significantly higher (43.65 ± 17.18 min vs. 68.17 ± 14.65 min) (Table 3; p < 0.001).
Post-hoc power analysis (G*Power 3.1.9.7, independent t-test, α = 0.05) showed that the achieved power for all four-time comparisons exceeded 99.9% (Supplementary Table 2). The experimental group demonstrated a statistically significant reduction in manual cleaning time.
Comparison of Cleaning Workflow Between the Two Groups
The procedural steps involved in traditional manual cleaning and manual pre-treatment combined with negative-pressure cleaning are summarized in Table 4 and Figure 3. The control group relied primarily on manual brushing, enzymatic soaking, and water-gun rinsing, whereas the experimental group incorporated automated vacuum ultrasonic cleaning, pulse flushing, vacuum perfusion, and vacuum drying.
Figure 3: Workflow comparison between traditional manual cleaning and manual pre-treatment combined with negative-pressure cleaning. (A) Control group workflow, including manual brushing, enzymatic soaking, ultrasonic cleaning, rinsing, disinfection, and drying. (B) Experimental group workflow, including manual pre-treatment followed by automated vacuum ultrasonic cleaning, pulse flushing, vacuum perfusion, and vacuum drying. Please click here to view a larger version of this figure.
Comparison of Operational Characteristics Between Cleaning Methods
A comparative summary of the operational characteristics of the two cleaning methods is presented in Table 5. Differences were observed in manual labour requirements, cleaning standardization, staff workload, and equipment dependency. Variations were also noted in total processing time and equipment investment requirements between the two methods.
Overall, the experimental group demonstrated higher qualification rates across multiple detection methods and a statistically significant reduction in manual cleaning time compared to the control group.
| Detection Method | Control Group | Experimental Group | χ² Value | P Value | ||
| Number of Qualified Samples | Qualification Rate (%) | Number of Qualified Samples | Qualification Rate (%) | |||
| Visual Observation | 94 | 94 | 99 | 99 | 1.546 | 0.214 |
| 5x Magnification Inspection | 85 | 85 | 97 | 97 | 8.791 | 0.003 |
| Residual Blood Detection | 82 | 82 | 97 | 97 | 11.971 | 0.001 |
| ATP Fluorescence Detection | 88 | 88 | 97 | 97 | 3.191 | 0.074 |
| Complete Qualification | 68 | 68 | 93 | 93 | 19.908 | ＜0.001 |
| Note: Complete qualification refers to samples that passed all of the following methods: visual observation, 5x magnification visual observation, residual blood detection, and ATP fluorescence detection. | ||||||
Table 1: Comparison of qualification rates between control and experimental groups across four detection methods. Data is presented as number and percentage of qualified instrument sets. Statistical comparisons were performed using the chi-square (χ2) test.
| Outcome Variable | Statistical Test | Effect Size | Achieved Power | Interpretation |
| Visual observation qualification | χ² test | Small | Low | Limited sensitivity |
| 5× magnification qualification | χ² test | Moderate | High | Significant difference |
| Residual blood detection | χ² test | Moderate–large | High | Strong difference |
| ATP fluorescence detection | χ² test | Small–moderate | Moderate | Trend toward improvement |
| Complete qualification rate | χ² test | Large | Very high | Clinically meaningful |
| Manual time (first cleaning) | t-test | Very large | >99% | Major labor reduction |
| Total time (first cleaning) | t-test | Very large | >99% | Automation-driven increase |
| Manual time (complete cleaning) | t-test | Large | >99% | Sustained efficiency gain |
Table 2: Statistical comparison of cleaning quality and efficiency outcomes between groups. Effect sizes are reported as Cohen’s d (continuous variables) and Cohen’s w (categorical variables). Post hoc statistical power is also presented for each outcome.
| Control Group (n=100) | Experimental Group (n=100) | t | p-value | |
| Manual Cleaning Time for the First Cleaning | 28.94±2.57 | 6.48±2.78 | 59.25 | ＜0.001 |
| Total Time for the First Cleaning | 31.44±2.57 | 64.48±2.78 | -87.16 | ＜0.001 |
| Manual Cleaning Time for Complete Cleaning | 40.07±15.73 | 6.69±2.79 | 20.898 | ＜0.001 |
| Total Time for Complete Cleaning | 43.65±17.18 | 68.17±14.65 | -10.863 | ＜0.001 |
Table 3: Comparison of cleaning time between control and experimental groups. Data are presented as mean ± standard deviation (min). Statistical comparisons were performed using independent sample t-tests.
| Cleaning Stage | Control Group (Traditional Manual Cleaning) | Experimental Group (Manual + Negative-Pressure Cleaning) |
| Initial rinsing | Running water rinse | Running water rinse |
| Manual brushing | Extensive manual brushing | Minimal manual pre-treatment |
| Enzymatic soaking | Required | Integrated within device cycle |
| Ultrasonic action | Separate ultrasonic cleaning | Vacuum ultrasonic cleaning |
| Lumen cleaning | Manual or water gun | Vacuum perfusion and pulse flushing |
| Disinfection | Wet heat disinfection | Integrated cleaning and disinfection |
| Drying | Drying cabinet | Vacuum drying |
| Repeat cycles | Manual repetition | Automated repeat cycles |
| Staff involvement | High | Limited supervision |
Table 4: Stepwise comparison of cleaning workflows between traditional manual cleaning and manual pre-treatment combined with negative-pressure cleaning.
| Aspect | Traditional Manual Cleaning | Manual Pre-treatment Combined with Negative-Pressure Cleaning |
| Manual labor intensity | High | Low |
| Cleaning consistency | Operator-dependent | Highly standardized |
| Effectiveness for fine lumens and complex structures | Limited | Superior |
| Total processing time | Shorter | Longer |
| Manual operation time | Long | Significantly reduced |
| Staff workload | High | Reduced |
| Risk of occupational fatigue | Higher | Lower |
| Equipment investment cost | Low | Higher |
Table 5: Comparison of operational characteristics between cleaning methods, including labor intensity, standardization, cleaning effectiveness, processing time, and equipment requirements.
Supplementary Table 1: Post hoc power analysis (χ2 test) of inter-group qualification rate differences under different detection methods. Statistical power was calculated using G*Power 3.1.9.7 with α = 0.05. Please click here to download this file.
Supplementary Table 2: Post hoc power analysis (independent samples t-test) of cleaning time differences between the two groups. Statistical power was calculated using G*Power 3.1.9.7 with α = 0.05. Please click here to download this file.
Discussion
Cleaning dental implant instruments presents significant challenges due to their complex structures, multiple components, and lumen-containing designs22. It demands high professional standards from personnel, equipment, and facilities, and increases the risk of infection for surgical patients. This has long been a key issue in hospital infection control and the improvement of cleaning efficiency23,24. The combination of manual pre-treatment and a negative‑pressure cleaning and disinfection device uses composite cleaning technologies, including vacuum ultrasonic cleaning, multi-stage pulse cleaning, vacuum perfusion cleaning, and vacuum drying, to achieve optimal cleaning results for implant instruments25. Specifically, this study proposes a combined manual pre-treatment and negative-pressure-assisted cleaning workflow as a standardized and efficient alternative to conventional manual cleaning for dental implant instrument reprocessing. Through statistical analysis, the combination of manual pre-treatment and negative‑pressure cleaning and disinfection devices was associated with significantly reduced cleaning time, improved work efficiency, and increased qualification rates.
These findings are consistent with international infection control guidance emphasizing effective cleaning as a prerequisite for successful disinfection and sterilization, particularly for complex instruments26. Inadequate cleaning can compromise sterilization effectiveness and increase infection risk, as widely reported11,27. Beyond operational improvements, these findings contribute to the broader field of sterilization science and support the integration of automated and pressure-assisted cleaning technologies into instrument reprocessing protocols, particularly for complex, lumen-containing devices. This may inform the development of standardized cleaning guidelines and optimization of pre-sterilization workflows in CSSDs and is consistent with recent international studies on automated cleaning systems. Importantly, this study provides one of the first comprehensive evaluations of negative-pressure-assisted cleaning specifically for dental implant instrument sets using multiple objective quality indicators and efficiency metrics. Automated and semi-automated cleaning systems have been increasingly recommended to address the limitations of manual cleaning, especially for reusable medical devices used in high-risk procedures28. Compared with conventional automated cleaning systems, such as ultrasonic cleaning devices and washer–disinfector units, which primarily rely on standard-pressure fluid dynamics and mechanical agitation, the negative-pressure cleaning approach used in this study enhances fluid penetration and cavitation effects under reduced-pressure conditions. This may improve the removal of contaminants from complex instrument geometries and narrow lumens, where conventional systems may have limited effectiveness. These observations are consistent with previous studies reporting limitations of standard automated cleaning systems in effectively cleaning complex and lumen-containing instruments10,29.
In traditional manual cleaning methods, staff members need to spend a significant amount of time meticulously scrubbing dental implant instruments to remove stains and residues from the instrument surfaces30. The enhanced cleaning performance is attributed to vacuum-assisted fluid penetration, ultrasonic cavitation, and pulse-driven flushing, which together improve contaminant removal from complex geometries and lumens.
By reducing the pressure within the cleaning chamber, air in the cleaning solution is rapidly removed, making the solution denser. Under vacuum conditions, ultrasonic waves generate tiny bubbles in the cleaning solution. When these bubbles collapse on instrument surfaces or within gaps, high-pressure shockwaves are produced, effectively removing contaminants. When these bubbles collapse on the instrument surfaces or in gaps, high-pressure shockwaves are produced, effectively removing stains from the surface and crevices of the instruments. The “cavitation” effect of the ultrasound generates instantaneous high pressure to peel off the stains. The cleaning solution in the chamber does not need to reach high temperatures under normal pressure to cause boiling. With multi-stage pulse cleaning under reduced pressure in the cleaning chamber, the cleaning solution reaches a rolling boil at 48–62 °C, quickly detaching most stains adhered to the instrument surfaces or inside the lumens. Additionally, the reduction of pressure within the cleaning chamber generates steam within the lumens, forming voids. Pulsed negative pressure is then applied to release gas from the cleaning solution, allowing external atmospheric pressure to enter the chamber, causing the steam within the instrument lumens to flow rapidly, generating flushing force on the internal walls. Furthermore, the negative‑pressure pulse liquid input causes the cleaning solution in the chamber to roll and scrub the instrument surfaces from bottom to top. After the vacuum ultrasonic and multi-stage pulse cleaning, the stains on the interior walls of the lumens are either removed or loosened. Any remaining stains not completely detached are flushed out using vacuum perfusion, quickly removing the remaining debris from the lumens. This results in rapid and effective cleaning. This technique not only reduces labor requirements but also significantly expedites manual cleaning processes, standardizes, and simplifies the cleaning procedure. The standardized cleaning process not only saves time spent on cleaning but also offers consistent quality in the cleaning process11,23. Moreover, negative pressure cleaning and disinfection devices can change the cleaning parameters according to real requirements, including cleaning time, cleaning intensity, and cleaning solution concentration, and can further optimize cleaning effectiveness across various types of dental implant toolkits with different levels of complexity.
These findings are supported by the workflow comparison (Figure 3) and efficiency data (Table 3), which demonstrate reduced manual handling and improved standardization. The nature of operations indicates the decreased work intensity, enhanced standardization, and reduced occupational fatigue related to negative pressure cleaning. In addition, statistical analysis with effect size and power demonstrates that the identified improvements in the quality of cleaning and reduction of manual time are strong and operationally significant28.
Furthermore, the combination of manual pre-treatment and negative‑pressure cleaning and disinfection devices can significantly increase the qualification rate of cleaning dental implant instruments. Compared to traditional manual cleaning methods, which may result in poor cleaning outcomes or fluctuating qualification rates for dental implant toolkits, the negative‑pressure cleaning and disinfection device ensures consistency and stability throughout the cleaning process by precisely controlling the cleaning parameters and procedures. Cleaning effectiveness is influenced by instrument design characteristics, including geometry and material properties, particularly the presence of narrow lumens, joints, and complex surface geometries, which can hinder fluid penetration and contaminant removal in conventional cleaning methods. The improved performance observed in this study suggests that negative-pressure-assisted cleaning may provide enhanced penetration and cleaning efficiency in such complex instrument structures. These factors are particularly relevant for dental implant instruments, which often consist of mixed materials and intricate geometries, potentially contributing to the higher qualification rates observed in the experimental group. Although the device primarily enhances cleaning, its role in improving pre-sterilization conditions may indirectly support sterilization efficacy, and may also facilitate simultaneous cleaning and disinfection processes, thereby enhancing the qualification rate of the cleaning process. Besides efficacy and qualification rate, there are other benefits associated with manual pre-treatment, as well as negative pressure cleaning and disinfection devices. As an illustration, traditional manual cleaning techniques require employees to engage in long-term repetitive scrubbing motions, which may cause bodily exhaustion and hand strain or injury. Contrarily, the negative pressure cleaning and disinfection device automates the process, thus significantly decreasing the intensity of labor and physical stress on the workers.
Other past occupational health research has indicated that repetitive manual activities in CSSD settings are associated with musculoskeletal disorders1,31. In addition, these findings highlight the potential of automation to improve occupational safety and workforce sustainability in healthcare sterilization environments. The improvement in workforce safety and operational efficiency through automation further supports the practical benefits of the current study.
The toolkit comes into contact with saliva, blood, and other body fluids of the patient during the dental implant process. Failure to clean it properly may cause cross-contamination. In this study, the experimental group showed a significant improvement in the qualification rate of cleaning across several fine detection indicators, especially with residual blood and ATP detection qualification rates reaching 97%. This improvement suggests enhanced removal of organic and biological contaminants, which is critical for ensuring effective downstream sterilization and reducing cross-contamination risks. These findings have direct clinical relevance for improving infection control practices in CSSDs and enhancing patient safety during surgical procedures.
ATP fluorescence monitoring is becoming established as a sensitive and fast means of measuring the effectiveness of cleaning and identifying organic contaminants that cannot be seen by visual inspection alone27. The experimental group had higher ATP qualification rates, indicating that bioburden was better removed before sterilization, which enhances the overall infection prevention measures. Alternative approaches to evaluate cleaning effectiveness could include randomized multicenter trials, microbiological culture-based validation, or protein residue quantification methods. Additionally, comparative studies involving other automated cleaning systems or different negative-pressure parameters could further validate and optimize the proposed method. These alternative study designs would strengthen external validity and provide deeper insight into mechanistic performance differences.
Key limitations include single-center design, which may limit generalizability across clinical settings and instrument types; absence of microbiological culture-based validation to confirm sterilization effectiveness; lack of formal cost–benefit analysis, limiting assessment of implementation feasibility; and potential workflow-related variability due to routine CSSD operational conditions. Although outcome assessment was performed by trained personnel, full blinding may not have been achievable at all stages, which could introduce observational bias. Furthermore, the findings are based on a specific negative-pressure cleaning device, and device-specific characteristics may limit generalizability. The study did not evaluate long-term outcomes (e.g., recontamination risk and durability across repeated use cycles) or perform subgroup analysis based on instrument complexity, which may influence cleaning effectiveness and warrants further investigation.
Nevertheless, the disinfection device may also present certain practical limitations. To begin with, the price of the device is quite high and requires hospitals to invest considerable amounts of money to purchase and maintain it. Additionally, staff members need to undergo additional professional training to become proficient in operating the device. Nevertheless, the substantial reduction in manual operation time in the experimental group helps optimize human resource allocation and may yield certain economic benefits in long‑term operation. In conclusion, compared to traditional manual cleaning methods, the combination of manual pre-treatment and negative‑pressure cleaning and disinfection devices can reduce manual cleaning time, improve work efficiency, save labour costs, and decrease the opportunity for cross-contamination.
Future Directions
Future studies should include multicenter randomized trials, microbiological validation using culture-based and molecular methods, and standardized parameter optimization across different instrument types. Research exploring optimization of device parameters (e.g., pressure levels, cycle duration, and cleaning solution composition) across different instrument types would further enhance clinical translation.
Conclusion
Manual pre-treatment combined with negative-pressure cleaning improves cleaning quality and significantly reduces manual operation time, supporting its adoption as a standardized and efficient approach for dental implant instrument reprocessing.
Disclosures
The authors confirm that no artificial intelligence (AI) tools were used in the preparation of the figures. All figures are original and were created by the authors. No previously published or adapted figures have been used; therefore, no reprint permissions are required.
Acknowledgements
The authors acknowledge financial support for this work from the National Key Laboratory of Oral Disease Prevention and Treatment Research Project (SKLOD2024OF03).
Materials
| Name | Company | Catalog Number | Comments |
|---|---|---|---|
| ATP fluorescence detector | Hygiena LLC, USA / 3M Company, USA | SystemSURE Plus (ATP-100) / Clean-Trace LM1 | Used for ATP-based contamination detection |
| ATP test swabs | Hygiena LLC, USA | UltraSnap™ (US2020) | Compatible with ATP fluorescence detector |
| Cleaning indicator strips | 3M Company, USA | Clean-Trace™ Test Strips (CTS100) | Used for process validation of cleaning efficacy |
| CSSD workbench | Belimed AG, Switzerland | WD290 IQ series | Instrument processing workstation |
| Dental implant instrument toolkits | Straumann Group, Switzerland / Nobel Biocare, Switzerland | Various (kit-specific) | Retrieved after implant surgery; used as study samples |
| Drying module (integrated system) | Shinva Medical Instrument Co., Ltd., China | SQ-Z series | Integrated drying unit in automated system |
| Enzymatic detergent | Ruhof Corporation, USA | Endozime® AW Plus (345SPD) | Used for manual pre-cleaning |
| Five-fold magnifying lens (5×) | Olympus Corporation, Japan | 5× Loupe (ME-5X) | Used for magnified visual inspection |
| Negative-pressure cleaning and disinfection device | Shinva Medical Instrument Co., Ltd., China | SQ-D Series Pulsed Vacuum Washer Disinfector | Automated cleaning and disinfection system |
| Personal protective equipment (PPE) | Ansell Ltd., Australia | Microflex® 93-260 | Gloves used during manual cleaning |
| Residual blood detection reagent/test kit | Healthmark Industries, USA | HemoCheck™ (HCK100) | Used for detecting residual blood contamination |
| Running water source | Hospital CSSD water system | Not applicable | Standard CSSD rinse water supply |
| Soft cleaning brushes | Healthmark Industries, USA | BRS-100 series | Used during manual cleaning |
| Temperature monitoring probe | Testo SE & Co., Germany | Testo 110 | Used to monitor cleaning temperature (48–62 °C) |
| Timer / digital stopwatch | Casio Computer Co., Japan | HS-80TW | Used for recording cleaning duration |
| Ultrasonic cleaning machine | Branson Ultrasonics, USA | Branson 5800 | Used for ultrasonic cleaning step |
| Water quality test kit | Merck KGaA, Germany | Aquamerck® Kit | Ensures water quality for cleaning processes |
| SPSS statistical software | 21.0 software | Statistical anlysis software |