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510(k) Data Aggregation

    K Number
    K051568
    Date Cleared
    2005-11-17

    (156 days)

    Product Code
    Regulation Number
    880.5725
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    CADD-MS 3 AMBULATORY INFUSION PUMP

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

    The CADD-MS™ 3 Ambulatory Infusion Pump is designed for subcutaneous, intravenous, epidural and intrathecal infusion of medication.
    The Smiths Medical MD, Inc. 3-ml Cartridge Reservoir is designed for use with the CADD-MS™ 3 for delivering medication.

    Device Description

    The Smiths Medical MD, Inc. CADD-MS™ 3 Ambulatory Infusion Pump, a microprocessor based electronic syringe pump with a 3-ml cartridge reservoir, is designed for low volume syringe-based infusion therapy allowing continuous, automatic dose and demand dose delivery profiles for subcutaneous, intravenous, epidural and intrathecal delivery.
    The pump operates on one (1) AAA alkaline battery. The user-interface of hardware features include a backlit liquid crystal display, 4-key front keypad, separate bolus button, audible or vibratory alarm, battery cap and cartridge cap. The pump is waterproof and features a cartridge sensor and downstream occlusion sensor.
    Based on user code-entry and an internal real-time clock, a user will be able to program multiple basal (continuous), bolus (demand) dosing and automatic dosing delivery profiles within programmed maximum limits.
    The pump accommodates the Smiths Medical MD, Inc. 3ml cartridge reservoir.

    AI/ML Overview

    The provided document is a 510(k) summary for the CADD-MS™ 3 Ambulatory Infusion Pump, which is a medical device. It is not an AI/ML device, and therefore, many of the requested criteria (such as number of experts, adjudication methods, MRMC studies, standalone performance, training set details, etc.) are not applicable or typically part of the submission for this type of device.

    However, I can extract the relevant information regarding acceptance criteria and the studies performed to demonstrate equivalence to a predicate device.

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly present "acceptance criteria" in a quantitative, tabular format as one might expect for an AI/ML device's performance metrics. Instead, the "acceptance criteria" are implied by the performance characteristics of the predicate device (CADD-Micro® Ambulatory Infusion Pump) and the CADD-MS™ 3's ability to demonstrate "substantial equivalence" through functional testing and comparison. The "reported device performance" is essentially that it met these equivalence standards.

    Acceptance Criteria (Implied by Equivalence to Predicate)Reported Device Performance (CADD-MS™ 3)
    Indications for Use: Subcutaneous, intravenous, intrathecal, and epidural delivery of medication.Met: Designed for subcutaneous, intravenous, intrathecal, and epidural delivery of medication.
    Performance Features: (e.g., flow rate accuracy, alarm functions, battery life, user interface functionality, safety features like occlusion sensors, programming capabilities). These are implicitly benchmarked against the CADD-Micro®.Met: "performs to established specifications" and is "substantially equivalent... with respect to indications for use and performance features" to the CADD-Micro®. Specific functional tests were performed for software validation, verification of software-controlled programming functions, and proper pump operation. Biocompatibility testing was also performed for the 3-ml Cartridge.
    Safety: Device operates safely without causing harm to the user or patient.Met: "is safe, effective and performs to established specifications." Implied by functional testing, biocompatibility, and comparison to a legally marketed predicate device.

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

    • Test Set Sample Size: Not applicable. This device is an infusion pump, and the "test set" here refers to engineering and functional tests rather than a dataset of patient cases. The testing would involve a certain number of manufactured units, but the specific quantity is not disclosed in the summary.
    • Data Provenance: Not applicable. The testing is primarily functional and engineering-based on the device itself.

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

    • Not applicable. Ground truth as typically defined for AI/ML performance (e.g., expert consensus on medical images or diagnoses) is not relevant for this type of device submission. Performance is assessed through engineering tests and comparison to a predicate device, which would involve qualified engineers and regulatory specialists.

    4. Adjudication method for the test set

    • Not applicable. Adjudication methods are typically for resolving discrepancies in expert interpretations of data for AI/ML studies. This is not relevant for functional device testing.

    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

    • No. This is not an AI/ML device, and therefore, MRMC studies are not applicable.

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

    • Not applicable. This is a hardware medical device with embedded software, not an AI/ML algorithm. Its "standalone performance" refers to its functional operation as a pump, which was assessed through validation and verification tests, as described in "Functional Testing."

    7. The type of ground truth used

    • Engineering Specifications and Predicate Device Performance: The "ground truth" for this device's performance is established by its design specifications and by demonstrating that it performs comparably or identically to the legally marketed predicate device (CADD-Micro® Ambulatory Infusion Pump) for its intended use and performance features. This would include verifying flow rates, alarm functions, programming accuracy, and safety features against predetermined engineering standards and the known performance of the predicate.

    8. The sample size for the training set

    • Not applicable. This device does not involve a "training set" in the context of AI/ML.

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

    • Not applicable. As there is no training set, the establishment of ground truth for it is irrelevant.
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