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510(k) Data Aggregation

    K Number
    K160745
    Date Cleared
    2016-12-12

    (269 days)

    Product Code
    Regulation Number
    880.5700
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    neoBLUE compact LED Phototherapy System

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

    The neoBLUE compact LED Phototherapy System is intended for the treatment of neonatal hyperbilirubinemia. The light can be used for infants in a bassinet, incubator, open bed, or radiant warmer.

    Device Description

    The neoBLUE compact LED Phototherapy System utilizes a portable phototherapy light that delivers a narrow band of high-intensity blue light emitting diodes (LEDs) to provide treatment for neonatal hyperbilirubinemia.

    The neoBLUE compact LED Phototherapy System light consists of a lightweight plastic light enclosure which can be used independently by placing directly on top of an incubator, or with the arm, or with the arm and roll stand together. The arm can be attached to the pole mount accessory on most incubators and radiant warmers. The arm, when attached to the roll stand, can be used for infants in a bassinet, incubator, open bed, or radiant warmer.

    The neoBLUE compact LED Phototherapy System light is equipped with a treatment timer to track the total number of treatment hours per patient, a device timer to track the total number of operating hours for the blue LEDs, and an exam light.

    AI/ML Overview

    The provided text describes the neoBLUE Compact LED Phototherapy System and its substantial equivalence to predicate devices, not a study evaluating its performance against specific acceptance criteria in a clinical setting. Therefore, many of the requested categories for a study are "Not Applicable" or "Not Provided" in this document.

    Here's an analysis based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not present a table of specific quantitative acceptance criteria for clinical performance or a clinical study to prove the device meets them. Instead, it focuses on demonstrating substantial equivalence to predicate devices through technical characteristics and compliance with safety standards.

    Feature/Test CategoryAcceptance Criteria (Implied from Predicate/Standards)Reported Device Performance (neoBLUE compact LED Phototherapy System)
    Intended UseTreatment of neonatal hyperbilirubinemiaTreatment of neonatal hyperbilirubinemia
    Treatment MethodOverhead phototherapyOverhead phototherapy
    UserHealthcare professionals in a clinical settingHealthcare professionals in a clinical setting
    Sites of UseBassinet, incubator, open bed, radiant warmerBassinet, incubator, open bed, radiant warmer
    Patient PopulationNeonatesNeonates
    Light SourceLEDs (blue)Blue and white Light Emitting Diodes (LEDs)
    WavelengthPeak @ 440-470 nm (combined range of predicates)Peak @ 450 to 470 nm
    IntensityRange overlapping with predicates (>20 to 50 μW/cm²/nm @ 40cm, 40-49 μW/cm²/nm @ 30-40cm)10 – 55 μW/cm²/nm @ 35 cm
    Intensity Settings1 or 3 settings (from predicates)2 settings (high, low)
    Effective Treatment AreaRange overlapping with predicates (660 to 800 cm² @ 40cm)700 cm² @ 35 cm height
    Exam LightPresent on one predicate, absent on otherWhite Light Emitting Diodes (LEDs) (present)
    Electrical SafetyCompliance with IEC 60601-1, IEC 60601-1-2Compliance with IEC 60601-1, IEC 60601-1-2
    Thermal SafetyFan to cool, thermal protection circuitFan to cool circuitry, Thermal protection circuit
    Radiation SafetyMinimal UV/IR lightLED light source produces minimal UV and IR light
    Software VerificationVerifiedPerformed
    Design Verification & ValidationPerformedPerformed (includes device power, electrical safety, indicators, LED performance, intensity levels, intensity range, effective treatment area, usability)
    Hazard AnalysisPerformedPerformed
    Human Factors Validation TestingPerformedPerformed

    Note: The "acceptance criteria" here are implied from the comparison to predicate devices and the mention of standards compliance for safety and performance testing. There are no explicit, quantifiable clinical efficacy acceptance criteria provided within this document for a clinical study.

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

    • Sample Size for Test Set: Not Applicable. This document describes a premarket notification (510(k)) seeking substantial equivalence, not a clinical trial with a patient test set. Performance testing mentioned (electrical safety, LED performance, etc.) would be conducted on units of the device, not a patient sample.
    • Data Provenance: Not Applicable. No patient data or clinical data is mentioned for a test set.

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

    • Not Applicable. No clinical ground truth or expert adjudication for patient data is mentioned.

    4. Adjudication method for the test set

    • Not Applicable. No patient test set or adjudication process is described.

    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. This device is a phototherapy system, not an AI-assisted diagnostic or interpretative tool for human readers. No MRMC study was conducted or is relevant.

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

    • Not Applicable. This is a medical device (phototherapy system), not a standalone algorithm.

    7. The type of ground truth used

    • Not Applicable. For the technical performance aspects, the "ground truth" would be established by reference standards, engineering specifications, and validated measurement methods, rather than clinical ground truth (pathology, expert consensus, outcomes data).

    8. The sample size for the training set

    • Not Applicable. This is not an AI/machine learning device that requires a training set.

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

    • Not Applicable. This is not an AI/machine learning device.
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