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The STERIS Amsco Reliance Family of Washer / Disinfectors are indicated for use in the cleaning and low-level disinfection of soiled reusable utensils, trays, glassware, bedpans and urinals, rubber and plastic goods, simple hard-surfaced rigid instruments such as forceps and clamp, and other similar and related articles found in healthcare facilities.

The Amsco Reliance Family of Washer/Disinfectors are mechanical, computercontrolled Washer/Disinfectors. They are designed with pre-programmed cycles intended specifically for surgical instruments, delicate instrumentation (gentle cycle), utensils, glassware, plastic goods, anesthesia/respiratory goods and equipment decontamination. Additional cycles are available for customized programming to meet specific operating requirements.

Essentially, the Amsco Reliance Family of Washer/Disinfectors operate as follows: the load items are placed in the chamber where they are exposed to pressurized fluids delivered through a circulation system driven by a pump and controlled by a programmable computer. Injection pumps allow the automatic delivery of the selected chemicals in the sump water. Available configurations include steam or electrical heating of the sump water; and the drying option (electrically heated on some models. steam heated on others). The cabinet, chamber, and circulation system (including the pump) are primarily constructed of stainless steel.

The available cycle phases can be summarized as follows:

• 1. cold tap water pre-wash for the removal of gross soil;
• soaking in an enzymatic solution to break down proteinaceous materials; 2.
• 3. detergent wash to complete the soil removal:
• sonic cleaning to remove fine debris in crevices:
• hot tap water rinse to remove detergent and soil residues:
• thermal rinse to disinfect the load items;
• 7. pure water rinse and instrument lubrication:
• 8. drvina.

Note: Phases 2 and 4 are not offered on all models. Phases 2, 4, 7 and 8 are optional features.

The available accessories include a variety of single and multi-level loading racks, and transfer carts. Some models offer conveyor systems used to automate the loading of racks into the chamber, to initiate the proper cycle by reading a bar code tag located on the loading rack, and to provide queuing capacity.

Here's an analysis of the acceptance criteria and the study presented in the provided text for the Amsco® Reliance® Family of Washer/Disinfectors, structured to address your specific points:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document focuses on performance tests for cleaning, residue removal, thermal low-level disinfection, equipment decontamination, and instrument lubrication. The most detailed acceptance criteria and results are given for residue testing.

¹Results obtained with the Amsco Reliance 444 Single-Chamber Washer/Disinfector, considered representative for the family.

2. Sample Size Used for the Test Set and Data Provenance

• Cleaning: The document mentions "covering test items with blood a representative soil" and "colling of Washer/Disinfectors provided soil." It does not specify the exact number of test items or repetitions.
• Residues: The table lists items by category (e.g., "Surgical Instruments," "Micro Surgery Instruments," "Suction Tips," "Respiratory Equipment," "Rigid MIS Instruments"). It does not specify the precise number of individual items tested within each category. The results are presented as single values for each category, suggesting either an average or a single worst-case measurement.
• Thermal Low-Level Disinfection: A "sample test" was conducted using "vials containing known concentrations of microorganisms." No specific number of vials or repetitions is provided. It notes testing was done with the "MIS rack," implying a specific configuration was used.
• Equipment Decontamination: Testing involved "operating the Washer/Disinfector with various loading racks for 3 consecutive weeks" and "swabbing the surfaces of critical areas...on a weekly basis." It does not specify the number of swab samples or types of racks.
• Instrument Lubrication: Testing involved "inoculating hinged instruments with bacterial spores." No specific number of instruments is given.

Data Provenance: The studies were conducted either in STERIS facilities or subcontracted, in keeping with applicable quality systems regulations (Good Laboratory Practice, 21CFR §58). This indicates a controlled laboratory setting. The data is prospective as it involves controlled testing to demonstrate the device's performance. The country of origin for the studies is not explicitly stated beyond being linked to STERIS Corporation (located in Ohio, USA) and adhering to US regulations.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts

The document does not mention the use of human experts to establish ground truth for the test set. The ground truth was established through objective measurements and scientific protocols rather than expert consensus on subjective observations. For example:

• Cleaning: Visual inspection for residual soil (an objective assessment against a "no visible residual soil" criterion).
• Residues: Conductivity measurements and enzyme activity assays.
• Thermal Low-Level Disinfection: Measuring logarithmic reductions of known concentrations of microorganisms.
• Equipment Decontamination: Culturing swabs for biofilm or microbial growth.
• Instrument Lubrication: Sterility testing for bacterial growth.

4. Adjudication Method for the Test Set

Not applicable. As noted in point 3, the ground truth was established through objective laboratory testing and measurements, not subjective evaluations requiring expert adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically used for diagnostic devices that involve human interpretation of images or other data, where AI provides assistance to human readers. The Amsco Reliance Washer/Disinfector is a cleaning and disinfection device, not a diagnostic tool requiring human-in-the-loop interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, the studies conducted were standalone performance evaluations. The device's cleaning, disinfection, and residue removal capabilities were assessed directly without human intervention in the operational cycle or in the interpretation of the primary performance metrics (e.g., amount of residue, log reduction of microbes). The "computer-controlled" nature of the device inherently means its core operation is algorithmic.

7. Type of Ground Truth Used

The ground truth used in these studies was primarily objective laboratory measurements and scientific principles, including:

• Chemical assays: For residue levels (conductivity increase, enzyme activity to relieve color).
• Microbiological testing: For disinfection efficacy (logarithmic reduction of test organisms) and equipment decontamination (culturing for microbial growth/biofilm).
• Visual inspection: For cleanliness (absence of visible soil).
• Sterility testing: For lubricated instruments (absence of bacterial growth).

These are empirical measures against established scientific and safety standards.

8. Sample Size for the Training Set

Not applicable. This device is a mechanical, computer-controlled washer/disinfector, not an AI or machine learning algorithm that requires a "training set" in the conventional sense (i.e., data for machine learning model development). The "pre-programmed cycles" are based on engineering design and validated protocols, not adaptive learning from a dataset.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no "training set" in the context of an AI/ML model for this device. The operational parameters and control logic for the device's cycles were established through engineering design, scientific principles, and validation testing (the performance tests detailed in the document), rather than through a machine learning training process.

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