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510(k) Data Aggregation

    K Number
    K190022
    Date Cleared
    2019-09-25

    (264 days)

    Product Code
    Regulation Number
    868.5260
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    MD Diagnostics Limited

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    To filter possible bacteria and viruses from the patient exhalation, for use with carbon monoxide monitors. For use by healthcare professionals only.

    Device Description

    The SafeBreath Filter mouthpiece is a single patient contacting mouthpiece consisting of a 22mm diameter cardboard tube with a filter for the filtration of possible bacteria and viruses from the patient exhaled breath into the breath monitor device to prevent cross contamination.

    The SafeBreath mouthpieces connect directly to the carbon monoxide monitors, such as CO Check Pro and CO Screen (K171129).

    AI/ML Overview

    The provided text is a 510(k) Summary for the SafeBreath Filter Mouthpiece (K190022). It primarily focuses on demonstrating substantial equivalence to a predicate device through performance testing related to biocompatibility and filtration efficiency.

    However, the provided text does not describe a study involving an AI/Machine Learning device that utilizes a test set, expert ground truth, multi-reader multi-case studies, or addresses improved human reader performance with AI assistance. The device in question is a physical filter mouthpiece, not a software algorithm.

    Therefore, many of the requested criteria related to AI/ML device performance evaluation cannot be answered from the provided document. I will extract the information that is present concerning the device's acceptance criteria and the studies conducted.

    Here's an analysis based only on the provided text for the SafeBreath Filter Mouthpiece:

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

    Performance TestPurposeAcceptance CriteriaReported Device Performance
    ISO10993-5 In-vitro cytotoxicity(Implied: To assess cytotoxicity)Results less than Grade 2Grade 0 - Non cytotoxic
    ISO10993-10:2010 Skin Sensitization Study in Guinea Pigs (Maximization Test)To assess skin sensitization potential of polar and non-polar extracts of the test item SafeBreath filtered mouthpiece in Guinea pigs by Maximization test.Score 2 or lessScore 0 - Non sensitizing
    ISO10993 - 10:2010 Intracutaneous Reactivity in New Zealand White Rabbits (Irritation)To assess the possible irritation likely to arise from intracutaneous injection of polar and non-polar extracts of the test item SafeBreath filtered mouthpiece.Score 2 or lessScore 0 - Non irritant
    Public Health England Report 19/018 (Filtration Efficiencies)To evaluate Filtration Efficiencies Against Bacterial and Viral Aerosol Challenges of Aged 4-year-old SafeBreath mouthpieces at 11 litres/min at a relative humidity of 95%.Not applicable (criteria implicit in the purpose of proving efficiency)Bacterial efficacy: 98.50%
    Viral efficacy: 99.40%

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

    • Biocompatibility Tests: The exact sample sizes for the in-vitro cytotoxicity study are not specified. For the in-vivo studies:
      • Skin Sensitization (Guinea Pigs): Sample size not explicitly stated, but standard animal study protocols would involve a sufficient group size.
      • Intracutaneous Reactivity (New Zealand White Rabbits): Sample size not explicitly stated, but the test involved "single administration at five sites" in rabbits, implying multiple rabbits.
    • Filtration Efficiency Test (Public Health England Report 19/018): The sample size for the filters tested is not explicitly stated, but it refers to "Aged 4 year old SafeBreath mouthpieces."
    • Data Provenance: The studies appear to be laboratory-based performance tests, likely conducted in a controlled environment by specific testing organizations (e.g., Public Health England). The data provenance is not described in terms of "country of origin" from a clinical dataset or whether it's retrospective/prospective, as these are material/device performance tests not clinical data studies.

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

    • This question is not applicable to the provided document. The "ground truth" for this device is established through objective laboratory testing against established standards (ISO 10993 for biocompatibility) and direct measurement for filtration efficiency, not through expert interpretation of data like in an AI/ML context.

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

    • This question is not applicable. As these are objective laboratory tests, there is no need for expert adjudication of results in the way it's done for clinical image interpretation.

    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 question is not applicable. This device is a physical filter, not an AI-powered diagnostic tool, so no MRMC study or AI assistance evaluation was performed or is relevant here.

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

    • This question is not applicable. This is a physical device, not an algorithm.

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

    • The "ground truth" for the performance claims are based on:
      • Biocompatibility Standards: Compliance with ISO 10993 series through laboratory tests measuring specific biological responses (cytotoxicity, sensitization, irritation).
      • Direct Measurement: For filtration efficiency, the ground truth is the directly measured percentage of bacterial and viral particles filtered under controlled laboratory conditions.

    8. The sample size for the training set

    • This question is not applicable. There is no "training set" as this is not a machine learning device.

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

    • This question is not applicable. There is no "training set" for this physical device.
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    K Number
    K171129
    Date Cleared
    2018-03-02

    (319 days)

    Product Code
    Regulation Number
    868.1430
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    MD Diagnostics Limited

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    For monitoring of carbon monoxide in adult exhaled breath. They are in smoking cessation programs and can be used for the screening of CO poisoning and smoke inhalation. Also can be used for ambient air monitoring. For use by healthcare professionals only in professional healthcare facilities.

    Device Description

    The Carbon monoxide monitors (CO Check Pro & CO Screen) are hand held, battery powered, carbon monoxide analyzers, used for monitoring the concentration of carbon monoxide in adult exhaled breath, typically for use in smoking cessation programs and for the screening of CO poisoning.

    The devices are controlled via a two button kevpad with the measured parameters displayed on a simple LCD with coloured lights and an accompanying buzzer sound in response to the CO level.

    Electrochemical sensor technology is utilized to sample the gas and a microprocessor converts the output from the sensor into a meaningful displayed result, either as carbon monoxide in parts per million (CO) or the percentage of carboxyhaemoglobin in the blood (%COHb).

    The breath sampling system that attaches directly to the carbon monoxide monitors, comprises of a non-patient contacting mouthpiece adapter incorporating a one way valve to prevent cross contamination and a single use, patient contacting cardboard mouthpiece. The mouthpiece adapter maybe replaced or reused as required.

    The Carbon monoxide monitors are supplied non sterile for use by healthcare professionals only and can also be used for ambient air monitoring.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study information for the Carbon Monoxide monitors (CO Check Pro & CO Screen) as described in the provided 510(k) summary:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Performance MetricDeviceAcceptance CriteriaReported Device Performance
    CO Measurement RangeCO Check Pro0 to 99 ppm0 to 99 ppm
    CO Measurement RangeCO Screen0 to 375 ppm0 to 375 ppm
    Accuracy (Gas Performance Testing)CO Check Pro+/- 2ppm or 5%, whichever is greaterWithin +/- 2ppm for each measurement point (20ppm, 50ppm, 100ppm, 375ppm – CO Screen only)
    Accuracy (Gas Performance Testing)CO Screen+/- 3%Within +/- 2ppm for each measurement point (20ppm, 50ppm, 100ppm, 375ppm – CO Screen only)
    Operating Temperature RangeBoth devicesDevice operates successfully across the environment operating temperature rangeDevice operates successfully across the environment operating temperature range
    Robustness (Packaging Testing)Both devicesDevice housing demonstrates robustness via drop tests and functions as intended thereafterDevice housing demonstrates robustness via drop tests and functions as intended thereafter

    Note: The reported device performance for accuracy is stated as "within +/- 2ppm for each measurement point" for both devices, even though the CO Screen has an acceptance criterion of +/-3%. This implies that the CO Screen also met the stricter +/-2ppm criteria during testing.

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

    The document does not explicitly state the sample size for the test set used in the performance testing.
    The data provenance is retrospective, as it refers to performance testing conducted by the manufacturer to support the 510(k) submission. The country of origin for the data is not explicitly stated for the performance testing itself, but the manufacturer is based in the United Kingdom.

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

    This information is not applicable in this context. The "ground truth" for the performance testing was established using known calibrated gases rather than expert interpretation of patient data.

    4. Adjudication Method for the Test Set:

    This information is not applicable. The ground truth was based on objective measurements from calibrated gases.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size:

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was NOT done. This type of study is typically performed for AI-powered diagnostic devices where human readers interpret medical images or data. This device is a direct measurement instrument, not an AI interpretation system.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

    Yes, a standalone performance evaluation was done. The performance testing described (gas performance testing, temperature testing, packaging testing) assesses the device's accuracy and functionality independently of human interaction for interpretation purposes. The device directly measures CO levels.

    7. The Type of Ground Truth Used:

    The type of ground truth used was objective measurements from known calibrated gases for assessing accuracy. For temperature and packaging testing, the ground truth was the expected functional performance under specific environmental and physical stress conditions.

    8. The Sample Size for the Training Set:

    This information is not applicable. This device is a hardware-based carbon monoxide monitor using electrochemical sensor technology and a microprocessor for conversion. It is not an AI/machine learning algorithm that requires a "training set" in the traditional sense.

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

    This information is not applicable as there is no "training set" for this type of device. The device's operation is based on its sensor and programmed algorithms, not on learning from a dataset.

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