K Number
K973984
Date Cleared
1998-01-16

(88 days)

Product Code
Regulation Number
868.1400
Panel
AN
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The RAC 2A adds modularity to the Marquette Eagle configured product line. It is used to house the module [SAM (Smart Anesthesia Multi-gas) module] and provides an interface to the Eagle display. The module's patient information may be displayed on the Marquette Eagle monitor. This device is intended to be used by personnel trained in the use of the equipment. It is intended to be used within the hospital/facility environment.

Device Description

This device is viewed as a component of a system. The RAC 2A adds modularity to Marquette's Eagle configured product line. It is used to house the module [SAM (Smart Anesthesia Multi-gas) module] and provides an interface to the Eagle display. The RAC 2A is intended to allow the module's patient information to be displayed on the Eagle monitor display.

AI/ML Overview

The provided 510(k) summary (K973984) is for a medical device called the "RAC 2A," which is a module housing designed to interface a Smart Anesthesia Multi-gas (SAM) module with Marquette's Eagle display system. The device acts as a component within a larger system.

After reviewing the document, it is not possible to provide a detailed description of acceptance criteria and a study that proves the device meets them in the format requested. The document does not contain the level of detail necessary for such a response.

Here's why and what information is available:

1. A table of acceptance criteria and the reported device performance:

  • Not provided in the document. The summary states, "Various reliability and software testing was performed on the product, and the results indicated that the RAC 2A met the requirements of its intended use." However, it does not specify what those requirements (acceptance criteria) were or present the detailed performance results in any measurable format.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

  • Not provided in the document. There is no mention of sample sizes for any testing, nor information about data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):

  • Not applicable/Not provided. This device is a module housing, not a diagnostic or AI-driven system that requires expert interpretation to establish ground truth for a test set. The document focuses on the device's functional and safety performance as an interface.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

  • Not applicable/Not provided. As above, this type of adjudication is typically for diagnostic interpretation studies, which is not relevant to this 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:

  • Not applicable/Not provided. This is not an AI-assisted diagnostic device, so an MRMC comparative effectiveness study would not be performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

  • Not applicable/Not provided. This device is a hardware component. There is no "algorithm only" performance to evaluate in this context.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

  • Not applicable/Not provided. Ground truth, in the sense of a definitive diagnostic label, is not relevant for a module housing component. Testing would likely involve functional verification against engineering specifications and safety standards.

8. The sample size for the training set:

  • Not applicable/Not provided. There is no indication that this device uses a training set, as it is a hardware component and not an AI/ML algorithm.

9. How the ground truth for the training set was established:

  • Not applicable/Not provided. As above, there is no training set mentioned or implied.

Summary of available relevant information from the document:

  • Device Name: RAC 2A (module housing)
  • Intended Use: To house a SAM (Smart Anesthesia Multi-gas) module and provide an interface to the Eagle display, allowing the module's patient information to be displayed on the monitor.
  • Testing Performed: "Various reliability and software testing was performed."
  • Conclusion of Testing: "The results indicated that the RAC 2A met the requirements of its intended use. Marquette Medical Systems has demonstrated that use of the RAC 2A is as safe and effective, and performs substantially equivalent its predicate devices."
  • Predicate Devices: Eagle patient monitors (K960272, K960418, K961139), Tram-rac (K900598), Tram-rac / SAM module (K943977, K950581).
  • Classification: Class II (Product Code: 73 CCK)

The document is a 510(k) summary for a hardware component where the primary focus is on demonstrating substantial equivalence to predicate devices through functional and reliability testing, rather than an AI/ML or diagnostic device that would require detailed clinical study results with ground truth establishment.

§ 868.1400 Carbon dioxide gas analyzer.

(a)
Identification. A carbon dioxide gas analyzer is a device intended to measure the concentration of carbon dioxide in a gas mixture to aid in determining the patient's ventilatory, circulatory, and metabolic status. The device may use techniques such as chemical titration, absorption of infrared radiation, gas chromatography, or mass spectrometry.(b)
Classification. Class II (performance standards).