K Number
K974193
Date Cleared
1998-01-28

(82 days)

Product Code
Regulation Number
868.5160
Panel
AN
Reference & Predicate Devices
Predicate For
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Narkomed Ultrasonic Flow Sensor is indicated for measuring the respiratory flow rate of gas through the patient breathing circuit. Federal law restricts this device to sale by or on the order of a physician.

Device Description

The Narkomed Ultrasonic Flow Sensor mounts to the expiratory valve fitting on Narkomed Anesthesia Systems and ultrasonically measures respiratory flow rate.

AI/ML Overview

The provided text is a U.S. FDA 510(k) summary for the Narkomed Ultrasonic Flow Sensor. It establishes substantial equivalence to a predicate device and includes information on device description, intended use, and general regulatory compliance.

However, the document does not contain specific details regarding acceptance criteria, a detailed study proving device performance against those criteria, sample sizes for test sets or training sets, ground truth establishment methods, or information about expert involvement (number, qualifications, adjudication) that would typically be found in a performance study report.

The summary states: "Qualification of the Narkomed Ultrasonic Flow Sensor included a hazard analysis, functional and communication testing, environmental testing, and electromagnetic compatibility testing." This indicates testing was performed, but the results of these tests and the acceptance criteria established for them are not described in the provided text.

Therefore, I cannot populate the requested table and answer many of the specific questions.

Here's a breakdown of what can be extracted or inferred based on the provided text, and what is missing:


1. Table of Acceptance Criteria and Reported Device Performance

Acceptance CriteriaReported Device Performance
Not specified in the document"Qualification of the Narkomed Ultrasonic Flow Sensor included a hazard analysis, functional and communication testing, environmental testing, and electromagnetic compatibility testing." (Specific performance metrics and results are not provided.)

2. Sample size used for the test set and the data provenance

  • Sample size for test set: Not specified.
  • Data provenance: Not specified (e.g., country of origin, retrospective or prospective). The document only mentions "functional and communication testing, environmental testing, and electromagnetic compatibility testing," implying laboratory or engineering tests rather than clinical data in the usual sense for an AI/ML context.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

  • Not applicable/Not specified. This device is a flow sensor, not a diagnostic imaging device typically requiring expert interpretation for ground truth in the context of this 510(k) summary. The testing mentioned appears to be engineering/hardware qualification.

4. Adjudication method for the test set

  • Not applicable/Not specified.

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

  • No. This is not an AI/ML device, and no MRMC study is mentioned or relevant for this type of medical device's 510(k) submission as described.

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

  • Not applicable. This is a physical sensor, not an algorithm in the AI/ML sense. The "functional testing" would represent its standalone performance, but details are not provided.

7. The type of ground truth used

  • Not explicitly stated, but for a flow sensor, ground truth would likely be established using highly accurate reference flow meters and calibrated gas mixtures under various controlled conditions to verify the sensor's accuracy, precision, and linearity across its intended operating range.

8. The sample size for the training set

  • Not applicable/Not specified. This is a physical sensor, not an AI/ML algorithm that requires a training set in the conventional sense.

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

  • Not applicable/Not specified.

§ 868.5160 Gas machine for anesthesia or analgesia.

(a)
Gas machine for anesthesia —(1)Identification. A gas machine for anesthesia is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation. The device may include a gas flowmeter, vaporizer, ventilator, breathing circuit with bag, and emergency air supply.(2)
Classification. Class II (performance standards).(b)
Gas machine for analgesia —(1)Identification. A gas machine for analgesia is a device used to administer to a patient an analgesic agent, such as a nitrous oxide-oxygen mixture (maximum concentration of 70 percent nitrous oxide).(2)
Classification. Class II (performance standards).