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510(k) Data Aggregation

    K Number
    K013123
    Date Cleared
    2002-03-14

    (176 days)

    Product Code
    Regulation Number
    868.1840
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    For use with pulmonary function testing. To filter air between the patient's exhaled air and the testing equipment. Single patient use.

    Device Description

    The EMS PFT Filter is acompact, electrostatic filter with various end-fitting adaptable to various pulmonary function testing circuits. It has 75 ml deadspace and resistance of 07. cm H2O at 720 Ipm per ATS spirometry or 0.5 cm I-120 @ 60 lpm. There are various connectors to allow connection to various PFT equipment. Single patient use.

    AI/ML Overview

    The provided text describes a Premarket Notification 510(k) for the EMS PFT Filter. This type of submission is for demonstrating substantial equivalence to a predicate device, not typically for reporting on a study that establishes performance against predefined acceptance criteria for a novel device.

    However, the document does list performance attributes for the EMS PFT Filter and compares them to those of a predicate device (PDS KoKo K934475), which can be interpreted as demonstrating that the EMS device meets performance levels comparable to a legally marketed device.

    Here's an attempt to structure the information according to your request, with the understanding that this is a 510(k) submission, and the "study" is more of a comparison against a predicate, rather than a de novo clinical trial with specific acceptance criteria.


    1. Table of Acceptance Criteria and Reported Device Performance

    Given this is a 510(k) for substantial equivalence, the "acceptance criteria" are derived from the performance of the predicate device. The EMS PFT Filter is considered acceptable if its performance is comparable to or better than the predicate's.

    AttributeAcceptance Criteria (Predicate Device K934475)Reported Device Performance (EMS PFT Filter Model #5813)
    Intended useFor use with pulmonary function testing. To filter air between the patient's exhaled air and the testing equipment.Same
    Intended for single patientYesYes
    PrescriptionYesYes
    Intended populationAny patientSame
    Intended Environment of UseHospital, sub-acuteSame
    Can be used with several different PFT machinesYesYes
    Design Features - Compact housingYesYes
    Design Features - Various end-fittingsYesYes
    Dead Space (ml)60 ml75 ml
    Resistance to flow at 720 lpm (per ATS standard for spirometry)<1.5 cm H2O0.7 cm H2O
    Resistance to flow at 60 lpm<1.5 cm H2O0.5 cm H2O
    Bacterial filtration99.99+%99.9999%
    Viral filtration99.99+%99.999+%
    Housing materialPolystyrenePolystyrenc
    Filter mediaElectrostatic polypropyleneElectrostatic polypropylene

    Note on Differences: The dead space of the EMS PFT Filter (75 ml) is higher than that of the predicate (60 ml). However, the resistance to flow (0.7 cm H2O at 720 lpm and 0.5 cm H2O at 60 lpm) is better (lower) than the predicate's criteria of <1.5 cm H2O. The bacterial and viral filtration efficiencies are also better (higher) for the EMS filter. The document states, "There are no significant differences between the intended device and the predicates." This implies that the differences observed (like dead space, which is only slightly higher, and improved filtration/resistance) are not considered clinically significant enough to preclude substantial equivalence.

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

    The document does not describe a traditional "test set" in the context of a clinical trial or algorithm validation. The performance data presented (e.g., dead space, resistance, filtration efficiency) are typically derived from laboratory testing of the device itself.

    • Sample size: Not specified. It would usually involve testing a certain number of manufactured units to ensure consistency, but this is not detailed in the summary.
    • Data provenance: The data would originate from bench testing performed by the manufacturer, Engineered Medical Systems, Inc. The country of origin is implied to be the USA (Indianapolis, IN). The data is prospective in the sense that it's generated for the device being submitted, but not from a prospective patient study.

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

    Not applicable. For a medical device like a PFT filter, "ground truth" for its physical performance (like filtration efficacy or resistance) is established through standardized engineering and microbiological testing methods, not by expert consensus on clinical data.

    4. Adjudication Method for the Test Set

    Not applicable. As described in point 3, this type of device performance is measured objectively through specified tests, not through expert adjudication of images or clinical outcomes.

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

    No. An MRMC study is relevant for diagnostic imaging or AI algorithms where human readers interpret cases. This device is a passive filter; its performance is measured mechanistically, not through human interpretation.

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

    Not applicable. This device is a physical filter, not an algorithm or AI system.

    7. The Type of Ground Truth Used

    The "ground truth" for the performance metrics (e.g., bacterial/viral filtration, resistance, dead space) is established by standardized laboratory testing methods against established industry or regulatory standards (e.g., ATS spirometry standards mentioned for resistance). These are objective physical measurements.

    8. The Sample Size for the Training Set

    Not applicable. There is no "training set" as this is not an AI/machine learning device.

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

    Not applicable. There is no training set.

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