Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K201644
    Device Name
    QardioCore
    Manufacturer
    Date Cleared
    2021-02-28

    (256 days)

    Product Code
    Regulation Number
    870.2800
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    QardioCore

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

    The QardioCore ECG ambulatory monitoring device is intended to capture, store, transmit, and display ECG information for recording periods of up to 24-hours in a single session. It is indicated for use on adult patients who may be asymptomatic or who meet clinical indications to perform an ECG-Holter monitor exam.

    The QardioCore ECG monitor is a prescription-only device, and the reported information is provided for review by a physician who will render a diagnosis based on clinical judgment and experience.

    Device Description

    The QardioCore ECG ambulatory monitoring device is intended to capture, store, transmit, and display ECG information for recording periods of up to 24-hours in a single session. It is indicated for use on adult patients who may be asymptomatic or who meet clinical indications to perform an ECG-Holter monitor exam.

    The QardioCore ECG monitor is a prescription-only device, and the reported information is provided for review by a physician who will render a diagnosis based on clinical judgment and experience.

    The QardioCore ECG Monitor is composed of six main components: i) the QardioCore sensor with Bluetooth technology, ii) a chest strap that allows fitting of OardioCore sensor, iii) a USB charging cable, iv) the Qardio App (can be downloaded and installed from the respective App store) and runs on any iOS device with iOS version 10.0 or later, v) the cloud based server where the Qardio App stores and retrieves data, and vi) the ECG Viewer which provides a web interface to the doctor to view the data sent by the iPhone application.

    The QardioCore device is a wearable device that captures information through a single-channel ECG. The data is then encrypted and transmitted via Bluetooth Low Energy to the Qardio App, installed on a compatible mobile platform. The OardioCore is supplied with chest straps accommodating chest sizes ranging from 27-5 to 43 inches. An optional XL chest strap is available from 41.7 to 59.8 inches. The device is provided with a USB Type-A cable to charge the device.

    The Qardio App (which can be installed from the user's respective app store), can transmit the data, via Wi-Fi or standard data mobile telephony, to Qardio cloud based server for storage processing and transmission to an expert medical professional.

    The ECG Viewer application provides a web interface to the doctor to view the ECG data collected from the iPhone Application. All data that a patient accumulates using the QardioCore device is stored in the central server. The ECG Viewer provides the doctor with ECG data and Heart Rate (BPM), which a doctor can use as additional information for forming a medical diagnosis. The doctor is able to see both the ECG data and Heart Rate (BPM) as soon as the data becomes available in the central server provided that the patient accepts the doctor's request for access. The device does not include automated analysis except for heart rate calculation. QardioCore is not suitable for physicians who need to perform ECG diagnoses such as myocardial ischemia, left ventricular hypertrophy or specific bundle branch blocks that require multiple and precise electrode placement and consistent wave amplitude.

    AI/ML Overview

    The provided text describes the QardioCore ECG ambulatory monitoring device and its substantial equivalence determination by the FDA. Here's a breakdown of the requested information, specifically focusing on the clinical testing to establish acceptance criteria and prove its performance:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document explicitly states that the purpose of the clinical study was to demonstrate the non-inferiority of the QardioCore ECG Monitor in terms of signal quality compared to a conventional, FDA-cleared, 3-channel ECG-Holter monitor device over a 24-hour recording time with continuous recording. While specific numerical acceptance criteria for "non-inferiority" are not listed, the general acceptance can be inferred from the conclusion that the device "demonstrated the substantial equivalence with the predicate device."

    Acceptance Criteria (Implied)Reported Device Performance
    Non-inferiority in ECG signal quality compared to a standard 3-channel Holter monitor over 24 hours."The data provided demonstrated the substantial equivalence with the predicate device." The study measured various qualitative and quantitative metrics, including signal quality, relevant ECG waveform amplitude and intervals, artifact burden.

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

    • Sample Size for Test Set: Not explicitly stated in the provided text. The document mentions "a population consistent with the device indications for use," but does not give a numerical count of participants in the clinical study.
    • Data Provenance: The study was a prospective clinical study conducted to demonstrate the accuracy of the QardioCore. The country of origin of the data is not specified beyond the device being from a US-based company (San Francisco, California).

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

    • Number of Experts: Not explicitly stated.
    • Qualifications of Experts: Not explicitly stated. The text mentions that ECGs from both devices "were collected and analyzed in a blinded fashion," implying expert review, but does not detail their numbers or qualifications.

    4. Adjudication Method for the Test Set

    • Adjudication Method: Not explicitly stated. The text mentions that ECGs "were collected and analyzed in a blinded fashion," which is a common practice in clinical studies, but gives no specifics on how disagreements among experts (if multiple were used) were resolved.

    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

    • This document describes a device for capturing, storing, transmitting, and displaying ECG information. It specifically states: "The device does not include automated analysis except for heart rate calculation." Therefore, a comparative effectiveness study involving human readers improving with AI assistance would not be applicable, as the device's primary function is data acquisition and display for physician review, not AI-driven interpretation.

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

    • No, a standalone algorithm-only performance study was not done. The device's current functionality, as described, is for presenting data to a physician for review, with only heart rate calculation being automated. The "reported information is provided for review by a physician who will render a diagnosis based on clinical judgment and experience."

    7. The Type of Ground Truth Used

    • The ground truth was established by comparison with a reference device, specifically the ELA Medical, Inc., Spiderview Holter ECG recorder (K032466), which is an FDA-cleared 3-channel ECG-Holter monitor. The study aimed to demonstrate non-inferiority in signal quality against this established medical device.

    8. The Sample Size for the Training Set

    • Not applicable. The document describes a medical device for data acquisition and display, not a machine learning model that requires a training set in the conventional sense. The "training" in this context would refer to the development and testing of the device's hardware and software according to recognized standards.

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

    • Not applicable, as there is no mention of a machine learning training set for this device.
    Ask a Question

    Ask a specific question about this device

    Page 1 of 1