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510(k) Data Aggregation

    K Number
    K042745
    Device Name
    LIFESCREEN APNEA
    Date Cleared
    2005-01-19

    (107 days)

    Product Code
    Regulation Number
    868.2375
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    LIFESCREEN APNEA

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

    The device is intended for use on adult patients only as a screening device to determine the need for clinical diagnosis and evaluation by polysomnography based on the patient's score. The ECG recording may be obtained at any location specified by a physician including home, hospital or clinic. Subjects screened for sleep apnea should have periods of sleep of at least 4 hours duration during which the ECG is predominantly sinus rhythm in nature.

    Device Description

    Lifescreen Apnea is a software option for the LifeScreen ECG Holter scanning software. The Lifescreen Apnea option is a software addition only - no hardware changes are involved.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and the study details for the Lifescreen Apnea device, based on the provided FDA 510(k) summary:

    1. Acceptance Criteria and Reported Device Performance

    The acceptance criteria for the Lifescreen Apnea device are implicit in the performance metrics reported, aiming to demonstrate its ability to accurately classify sleep-disordered breathing (SDB) events on a per-minute basis. While explicit numerical "acceptance criteria" are not given in this document, the reported performance serves as the basis for the FDA's substantial equivalence determination.

    MetricAcceptance Criteria (Implicit)Reported Device Performance (Per-minute statistics)
    AccuracyHigh, comparable to predicate89.1% (95% C.I.: 88.58-89.52)
    SensitivityHigh, comparable to predicate87.0% (95% C.I.: 86.19-87.82)
    SpecificityHigh, comparable to predicate90.3% (95% C.I.: 89.74-90.88)
    Positive PredictivityHigh, comparable to predicate84.9%

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

    • Test Set Size: The provided 2x2 confusion matrix (Nn, Np, Pn, Pp) sums to 16,975 classifications (9449 + 845 + 1012 + 5669). This represents the total number of "minutes" or individual classifications made by the algorithm and the expert for the test set. The document does not explicitly state the number of unique patients or recordings, only the aggregate "per-minute" data.
    • Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. It only mentions "Lifescreen Apnea has been extensively tested in a clinical trial."

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

    • Number of Experts: The document refers to "Expert" classification in the confusion matrix. It uses the singular "Expert," implying that a single expert or a consensus derived from a group was used to establish the ground truth. The exact number of experts is not specified.
    • Qualifications of Experts: The qualifications of the expert(s) are not specified in the document.

    4. Adjudication Method for the Test Set

    The document does not describe the adjudication method used to establish the ground truth for the test set. It only mentions "expert classification" as the reference standard.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

    No, a multi-reader multi-case (MRMC) comparative effectiveness study explicitly comparing human readers with AI assistance versus without AI assistance is not mentioned or described in this document. The study described focuses on the standalone performance of the algorithm against an expert-established ground truth.

    6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study was Done

    Yes, a standalone study (algorithm only, without human-in-the-loop performance) was done. The reported "per-minute statistics" directly reflect the algorithm's performance in classifying SDB events compared to expert classifications.

    7. The Type of Ground Truth Used

    The ground truth used was expert classification for Sleep Disordered Breathing (SDB) events, as indicated by the "Expert" row/column in the confusion matrix and the reference to "expert classification."

    8. The Sample Size for the Training Set

    The document states: "The diagnostic criteria have also been established with a separate training group. Diagnostic criteria were established using a separate training group." However, the sample size for this training set is not provided in the document.

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

    The document states that "Diagnostic criteria were established using a separate training group." While it explicitly mentions a separate training group, it does not specify how the ground truth for this training set was established. It's implied that "expert classification" or similar gold standard methods would have been used, but this is not detailed.

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