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510(k) Data Aggregation

    K Number
    K090759
    Date Cleared
    2009-04-01

    (9 days)

    Product Code
    Regulation Number
    878.4780
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K080845, K012991

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

    The BioDrain STREAMWAY™ Fluid Management System (FMS) is intended to be used in areas such as Operating Rooms, Intensive Care Units, Pathology Suites, Emergency Rooms, Surgical Centers and Doctors' Offices to collect and dispose of fluid waste.

    Device Description

    The BioDrain STREAMWAY™ FMS system has been designed to safely remove surgical fluid waste during a surgical procedure. The device is wall mounted in the room in which the procedure is being conducted. It is connected to the hospital/clinic vacuum line system, the hospital/clinic drain system, and electrical power. The device removes waste via a disposable suction tube (not provided with system) from the patient and surrounding area, measures the volume of fluid collected, and disposes of the waste into the hospital drainage system. The device has a self cleaning cycle to clean the internal mechanism of the device. The cleaning solution container and the suction tube to the operative field are disposable. The cleaning solution adapter is reusable.

    AI/ML Overview

    The provided text describes the BioDrain STREAMWAY™ Fluid Management System (FMS) and its substantial equivalence to predicate devices, but it does not contain information about specific acceptance criteria or a study proving that the device meets such criteria.

    The document is a 510(k) summary for a medical device (a fluid management system, essentially a powered suction pump). The FDA's 510(k) pathway is for devices that are "substantially equivalent" to already legally marketed devices (predicates), meaning they have the same intended use and technological characteristics as the predicate, or have different technological characteristics but do not raise new questions of safety and effectiveness.

    Here's what can be inferred from the document based on the request:

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

    • Acceptance Criteria: Not explicitly stated in terms of quantitative performance metrics for the device. The "acceptance criteria" in a 510(k) context generally revolve around demonstrating substantial equivalence to a predicate device.
    • Reported Device Performance: The document states "Bench testing was performed to support a determination of substantial equivalence and consisted of packaging, electrical safety testing and all testing identified in the FDA's Guidance for Powered Suction Pumps, September 30, 1998 and Premarket Submissions for Software Contained in Medical Devices."
      • Specific performance results (e.g., flow rate, vacuum strength, volume measurement accuracy) are NOT provided in this summary. It only states that testing was performed and results provide assurance of conformance.
    Acceptance Criteria (Implied from 510(k) process)Reported Device Performance (Summary)
    Conformance to FDA Guidance for Powered Suction Pumps (Sept 30, 1998)Bench testing performed, results provide assurance of conformance to requirements for intended use.
    Conformance to Premarket Submissions for Software Contained in Medical DevicesRisk analysis of the system and its software performed, testing conducted to validate overall operations.
    Electrical SafetyBench testing performed.
    Packaging IntegrityBench testing performed.
    Biocompatibility (if applicable)Declared "not applicable" as the device has no direct patient contact.

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

    • Sample Size: Not specified. The document only mentions "bench testing."
    • Data Provenance: Not specified. Bench testing typically occurs in a lab setting rather than using patient data from a specific country or being retrospective/prospective.

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

    • Not applicable. This information is typically relevant for studies involving human interpretation (e.g., imaging studies, AI diagnostics). The study described here is bench testing of a physical device.

    4. Adjudication method for the test set:

    • Not applicable. Adjudication methods are relevant for studies where human expert consensus is needed to establish ground truth.

    5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

    • No. This type of study (MRMC) is for assessing the impact of a device (often AI) on human reader performance, typically in diagnostic imaging. The BioDrain STREAMWAY™ FMS is a fluid management system, and no such study is mentioned or relevant here.

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

    • Not applicable in the typical sense of AI algorithms. While the device itself operates "standalone" in its function, "standalone performance" usually refers to the performance of an AI algorithm independent of human intervention in a diagnostic context. The FMS is a physical piece of medical equipment. The "software" mentioned in the testing implies some control logic, but no "algorithm-only" performance metrics are provided.

    7. The type of ground truth used:

    • For physical performance aspects (e.g., vacuum, flow, electrical safety), the "ground truth" would be established by engineering specifications, industry standards, and regulatory guidance documents. The device's performance is measured against these established parameters.
    • The document implies that testing was done to assure conformance to the requirements of its intended use, based on FDA guidance and internal design specifications.

    8. The sample size for the training set:

    • Not applicable. This device is hardware with some embedded software, not a machine learning model that requires a "training set" of data in the AI sense.

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

    • Not applicable. (See point 8).
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