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510(k) Data Aggregation

    K Number
    K132662
    Date Cleared
    2014-08-01

    (340 days)

    Regulation Number
    870.1025
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    SHENZHEN MINDRAY BIOMEDICAL ELECTRONICS CO. LTD

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

    The Passport Series Patient Monitors, including Passport 8 and Passport 12, are intended to be used for monitoring, displaying, reviewing, storing and alarming of multiple physiological parameters including ECG (3-lead, or 5-lead, or 12-lead selectable), arrhythmia detection and ST Segment analysis, heart rate (HR), respiration (Resp), temperature (Temp), pulse oxygen saturation (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), cardiac output (C.O.), carbon dioxide (CO2), and anesthetic gas (AG).

    All the parameters can be applied to single adult, pediatric and neonatal patients with the exception of the following:

    • · C.O. monitoring is restricted to adult patients only;
    • · PAWP monitoring is not intended for neonatal patients;
    • · The Mortara ECG Algorithm arrhythmia detection and ST Segment analysis is intended for adult and pediatric patients. The Mindray ECG Algorithm arrhythmia detection is intended for adult and pediatric patients, and the Mindray ECG Algorithm ST Segment analysis is intended for adult patients only.
    • · 12-lead monitoring and AG monitoring are available for Passport 12 Patient Monitors only.

    The monitors are to be used in healthcare facilities by clinical physicians or appropriate medical staff under the direction of physicians.

    Device Description

    The Passport Series Patient Monitors (including Passport 12) are the developed new series based on the technical platform of the iPM Series patient monitors.

    Comparing with the cleared iPM Series Patient Monitors, the WiFi function is added on the subject patient monitors.

    AI/ML Overview

    Based on the provided text, here's an analysis of the acceptance criteria and study information for the Passport Series Patient Monitors:

    The document primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and performance study outcomes for each specific function. However, general statements about fulfilling safety and performance standards are made.

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly list a table of acceptance criteria with corresponding device performance metrics for individual parameters (e.g., specific accuracy for SpO2, heart rate detection sensitivity). Instead, it states that the device "comply[s] with the recognized safety, performance and electromagnetic compatibility standards" and that "The results of all testing demonstrate that the Passport Series Patient Monitors are as safe, as effective, and perform as well as the predicate devices."

    The "Test Summary" section mentions the following types of testing conducted to ensure compliance:

    • Requirements specification review
    • Hardware and Software testing
    • Code design and code reviews
    • Environmental EMC testing
    • Safety testing
    • Performance testing
    • Hardware and Software validation

    Without specific quantifiable acceptance criteria and performance results, a detailed table cannot be constructed from this text. The underlying assumption is that if it performs "as well as the predicate devices," it meets the established performance criteria for those predicates.

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

    The document does not specify the sample size used for clinical or performance testing, nor does it provide details about data provenance (e.g., country of origin, retrospective or prospective nature). The testing mentioned appears to be primarily related to hardware, software, and regulatory compliance rather than a clinical study with a defined patient cohort.

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

    This information is not provided in the document. The text does not describe a clinical study involving human experts to establish ground truth for a test set.

    4. Adjudication Method for the Test Set

    This information is not provided. No adjudication method is mentioned as there's no description of a clinical test set requiring expert adjudication.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

    No MRMC comparative effectiveness study is mentioned. The document focuses on demonstrating substantial equivalence to predicate devices through technical comparisons and compliance with standards, not on demonstrating an improvement in human reader performance with AI assistance.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    While "Hardware and Software testing" and "Performance testing" are mentioned, the document does not explicitly detail a standalone algorithm-only performance study in the context of clinical accuracy or diagnostic capability, particularly for functions like arrhythmia detection or ST segment analysis. It implies that the algorithms for these functions are the same as or equivalent to those in the predicate devices.

    7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

    The document does not specify the type of ground truth used for performance testing. Given the nature of the device (patient monitor displaying physiological parameters), ground truth would likely involve highly accurate reference devices or direct physiological measurements, but this is not explicitly stated. For functions like arrhythmia detection, ground truth would typically be established by expert cardiologists reviewing ECG recordings, but this is not detailed here.

    8. The Sample Size for the Training Set

    No information about a training set or its sample size is provided. This document describes a medical device seeking 510(k) clearance, which typically relies on demonstrating substantial equivalence to existing devices rather than de novo development requiring extensive machine learning model training details.

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

    Since no training set is mentioned (see point 8), there is no information on how its ground truth might have been established.

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