(58 days)
Use the Attest 1292 RRBI to monitor: 1. 250°F (121°C) gravity steam sterilization cycles. 2. 270°F (132°C) vacuum assisted steam sterilization cycles.
The 3M™ Attest™ 1292 Rapid Readout Biological Indicator, RRBI, is a dual readout biological indicator system specifically designed for rapid and reliable monitoring of steam sterilization process when used in conjunction with the 3M™ Attest™ 190/290 Auto-readers. The Attest 1292 RRBI detects the presence of Geobacillus stearothermophilus, (formerly known as Bacillus stearothermophilus), by detecting the activity of alpha-glucosidase, an enzyme present within the organism. The presence of the enzyme is detected by reading fluorescence produced by the enzymatic breakdown of a non-fluorescent substrate. This creates a fluorescence change, which is detected by the Attest 290 Autoreader. A fluorescence change indicates a steam sterilization process failure, The Attest 1292 RRBI also detects the presence of G. stearothermophilus organisms by a visual color change reaction. Biochemical activity of the G. stearothermophilus organism produces acid by-products that cause the media to change color from purple to yellow. A visual pH color change also indicates a steam sterilization process failure. The 3M™ Attest™ Rapid Read-Out Biological Indicator is identical in design and performance specifications (with exception of the calculation of survival/kill) to the predicate device.
The provided text does not contain detailed information regarding the acceptance criteria, specific study results, sample sizes, expert qualifications, or adjudication methods typically found in a clinical or performance study report for an AI/ML medical device. The document is a 510(k) summary for a biological indicator (3M Attest Rapid Read-Out Biological Indicator #1292), which is a device used to monitor sterilization processes, not an AI/ML algorithm.
Therefore, most of the requested information regarding acceptance criteria and study details for an AI/ML device cannot be extracted from this document.
However, I can provide what little information is available from the document about the device and its claimed performance, even though it's not in the context of AI/ML evaluation.
Here's a response based only on the provided text, heavily indicating the lack of information for AI/ML specific questions:
1. Table of Acceptance Criteria and Reported Device Performance
The document describes the device's function and a modification. It does not provide explicit "acceptance criteria" in the format typically seen for AI/ML performance, nor detailed performance metrics beyond its intended use.
| Acceptance Criteria (Implied) | Reported Device Performance (Implied) |
|---|---|
| Detect presence of Geobacillus stearothermophilus via alpha-glucosidase activity | Detects enzyme activity by reading fluorescence produced by enzymatic breakdown of a non-fluorescent substrate. A fluorescence change indicates failure. |
| Detect presence of G. stearothermophilus via visual color change reaction | Biochemical activity produces acid by-products, causing media to change color from purple to yellow. A visual pH color change indicates failure. |
| Functionality with 3M™ Attest™ 190/290 Auto-readers | Specifically designed for use with these auto-readers. |
| Monitoring 250°F (121°C) gravity steam sterilization cycles | Indicated for this use. |
| Monitoring 270°F (132°C) vacuum assisted steam sterilization cycles | Indicated for this use. |
| Performance identical to predicate device (K926364) | Claims to be identical in design and performance specifications (with exception of the calculation of survival/kill). |
| Ability to calculate survival/kill on a lot-by-lot basis (modification) | The purpose of the 510(k) filing is to move to this calculated method. |
2. Sample size used for the test set and the data provenance
This information is not provided in the 510(k) summary. The document is for a biological indicator, not an AI/ML device where "test set" and "data provenance" are typically discussed in the context of training and validation of a model. The modification described is related to the method of calculating survival/kill for the biological indicator.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not applicable and not provided in the 510(k) summary for this type of device. There is no mention of expert review or ground truth establishment in the context of diagnostic interpretation by AI/ML.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable and not provided in the 510(k) summary for this type of device.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
This information is not applicable and not provided. The device is a biological indicator for sterilization, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable. The device is a biological indicator; it does not involve algorithms or human-in-the-loop performance in the AI/ML sense. It interacts with an auto-reader, but this is a chemical-biological sensor system, not an AI system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For a biological indicator, the "ground truth" would typically be defined by established microbiological standards for sterilization efficacy (e.g., complete kill of Geobacillus stearothermophilus after a specific sterilization cycle). The document implies this by stating the device detects the presence of the organism and indicates sterilization failure. However, the specific methodology for establishing this "ground truth" in their testing is not detailed.
8. The sample size for the training set
This information is not applicable and not provided. The device is not an AI/ML model that undergoes "training."
9. How the ground truth for the training set was established
This information is not applicable. As stated, the device is not an AI/ML model and therefore does not have a "training set" in that context.
§ 880.2800 Sterilization process indicator.
(a)
Biological sterilization process indicator —(1)Identification. A biological sterilization process indicator is a device intended for use by a health care provider to accompany products being sterilized through a sterilization procedure and to monitor adequacy of sterilization. The device consists of a known number of microorganisms, of known resistance to the mode of sterilization, in or on a carrier and enclosed in a protective package. Subsequent growth or failure of the microorganisms to grow under suitable conditions indicates the adequacy of sterilization.(2)
Classification. Class II (performance standards).(b)
Physical/chemical sterilization process indicator —(1)Identification. A physical/chemical sterilization process indicator is a device intended for use by a health care provider to accompany products being sterilized through a sterilization procedure and to monitor one or more parameters of the sterilization process. The adequacy of the sterilization conditions as measured by these parameters is indicated by a visible change in the device.(2)
Classification. Class II (performance standards).