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510(k) Data Aggregation

    Why did this record match?
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The MedStar System is indicated for Out-of-Hospital Use with any patient requiring Out-of-Hospital monitoring. The associated Collection Server is intended for use in a Disease Management Center, Hospital or Hospital-Type facility, Medical Clinic or Physician's Office.

    Device Description

    The MedStar Monitoring System II comprises the MedStar Unit and the associated Collection Server. The MedStar Unit is a portable, battery-operated unit for controlling the transmission of data from a range of compatible patient monitors or measurement devices to a remote monitoring center. Data is transmitted via telephone lines to the associated data collection server at the remote site. The MedStar Unit is contained in a small plastic enclosure with an LCD screen mounted into the top of the case. The case is made of a strong impact resistant plastic material. A User push button control is located adjacent to the display. Four serial communication ports are located at the side of the unit for connection to the serial data ports of specific patient monitors. Two standard phone jacks are also located at the side of the unit for connection to standard phone outlets. Two recessed programming buttons are included on the opposite side of the enclosure to the phone jacks. The Collection Server comprises a Personal Computer-type Processor Unit incorporating an additional electronics board to control phone line transmission to and from the MedStar Unit.

    AI/ML Overview

    The provided text lacks the detailed study information required to complete the table and answer all questions comprehensively. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than presenting a detailed performance study with acceptance criteria and specific statistical results.

    Here's an attempt to extract the available information and highlight what is missing:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance CriteriaReported Device Performance
    Specific performance criteria for data transfer accuracy, reliability, or speed are not provided in the document.The document states that "bench testing was conducted to establish the MedStar System II's accuracy and performance to specification." However, the specific specifications or results are not detailed. It also states the device is "substantially equivalent" to predicate devices, implying similar performance.

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

    • Test Set Sample Size: Not specified.
    • Data Provenance: Not specified, but the "bench testing" mentioned suggests internal testing, not necessarily human patient data.

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

    • Not applicable. The device's function is data transfer, not diagnostic interpretation requiring expert ground truth.

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

    • Not applicable. The device's function is data transfer, not diagnostic interpretation.

    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. The MedStar System II is a data transfer device, not an AI-powered diagnostic tool used by human readers.

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

    • Yes, implicitly. The "bench testing" mentioned would be a standalone evaluation of the device's technical performance (e.g., successful data transmission, accuracy of data transfer) without human intervention in its core function. However, specific results are not provided.

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

    • For a data transfer device, the 'ground truth' would likely involve verifying the integrity and accuracy of the transmitted data against the original source data (e.g., verifying that a blood glucose reading of 'X' from the monitor is correctly received as 'X' by the server). The document does not specify the method used for this verification.

    8. The sample size for the training set:

    • Not applicable. This device is not described as using machine learning or AI that would require a training set.

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

    • Not applicable, as there's no mention of a training set.
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