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510(k) Data Aggregation

    K Number
    K000685
    Date Cleared
    2000-08-15

    (168 days)

    Product Code
    Regulation Number
    880.5440
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Applicant Name (Manufacturer) :

    CHARTER MEDICAL, LTD.

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use
    Device Description
    AI/ML Overview
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    K Number
    K990310
    Date Cleared
    1999-08-30

    (210 days)

    Product Code
    Regulation Number
    880.5440
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    CHARTER MEDICAL, LTD.

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

    Single use device for the removal of microaggregate and particulate debris from whole blood and red blood cells (RBCs) during infusion.

    Device Description

    40 micron filter offered both as a stand alone device and as an integral component of a Y-Blood Administration Set.

    AI/ML Overview

    The provided text describes the 510(k) submission for the Charter Medical, Ltd. 40 Micron Filter (Code MP450). It details the comparison of the new device to a predicate device to establish substantial equivalence.

    Based on the provided information, here's a breakdown of the acceptance criteria and the study details:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategorySpecific CriteriaReported Device Performance
    Substantial EquivalenceThe device is substantially equivalent (as defined in Section 360c(l)(1)(A)(ii) of the Federal Food, Drug and Cosmetic Act) in performance to the predicate device. This is determined by flow rate, effect of filtration on blood constituents, and hold-up volume.The device was determined by FDA to be substantially equivalent to the PALL Biomedical Products Company's SQ™40S 40-Micron Screen Filter (K811985). This determination was based on comparative studies assessing flow rate, effect of filtration on blood constituents (white blood count, red blood count, hemoglobin, and hematocrit), and hold-up volume.
    Material BiocompatibilityMaterials used to manufacture the device were assessed in respect to biocompatibility using methods specified in ISO Standard 10993-1.Materials were found to be acceptable for intended use based on assessment using ISO Standard 10993-1.
    Physical TestingHousing integrity, media integrity, filter cleanliness, removal characteristics (microaggregates and particulate debris), and security of attachments.Physical testing supported that the device is suitable for its intended use, covering aspects like housing integrity, media integrity, filter cleanliness, removal characteristics, and security of attachments.

    Study Details:

    The information provided describes a comparative study to demonstrate substantial equivalence to a predicate device. It is not a clinical study involving patients or a study with human readers assessing AI performance in a diagnostic context.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Sample Size for Test Set: Not explicitly stated. The document refers to "comparative studies" and "physical testing" but does not provide specific sample sizes for these tests.
    • Data Provenance: Not explicitly stated. It's implied these are laboratory or bench testing results conducted by Charter Medical, Ltd. (USA), but the specific location of the tests or if any external data was used is not mentioned. They are likely prospective tests conducted for the submission.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Number of Experts: Not applicable. The ground truth for this device approval revolves around objective measurements of performance characteristics (flow rate, blood constituent impact, hold-up volume, biocompatibility, physical integrity) against a predicate device and established standards. It does not involve expert interpretation or consensus on a diagnostic outcome.

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

    • Adjudication Method: Not applicable. This is not an image-based or diagnostic study requiring adjudication of expert opinions. The assessment relies on direct measurement and comparison of physical and performance characteristics.

    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

    • MRMC Comparative Effectiveness Study: No. This is a medical device (filter) submission, not an AI-based diagnostic tool. Therefore, an MRMC study assessing human reader performance with or without AI assistance is not relevant and was not conducted.

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

    • Standalone Performance: Not applicable in the context of an AI algorithm. The "standalone performance" of the device in this case refers to its functional characteristics (filtration, flow rate, biocompatibility) as measured in the comparative studies and physical tests. These are inherent to the device itself, without human intervention as part of its primary function, other than its proper installation and operation.

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

    • Type of Ground Truth: The ground truth is primarily based on:
      • Objective measurements: Of device characteristics like flow rate, hold-up volume, white blood count, red blood count, hemoglobin, hematocrit.
      • Established standards: ISO Standard 10993-1 for biocompatibility.
      • Comparison to a predicate device: The performance of the predicate device (PALL Biomedical Products Company SQ™40S 40-Micron Screen Filter) serves as a benchmark for substantial equivalence.

    8. The sample size for the training set

    • Sample Size for Training Set: Not applicable. This is a medical device (filter) submission, not a machine learning model. There is no concept of a "training set" in this context.

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

    • How Ground Truth for Training Set was Established: Not applicable, as there is no training set for this type of device submission.
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