(241 days)
The KardiaMobile System is intended to record, store and transfer single-channel electrocardiogram (ECG) rhythms. The KardiaMobile System also displays ECG rhythms and output of ECG analysis from AliveCor's KardiaAl platform including detecting the presence of normal sinus rhythm, atrial fibrillation, bradycardia, and others. The KardiaMobile System is intended for use by healthcare professionals, patients with known or suspected heart conditions and health conscious individuals. The device has not been tested and is not intended for pediatric use.
The KardiaMobile System is a trans-telephonic (transmission by telephone) ECG (electrocardiogram) event recorder that records, stores and transfers single-channel electrocardiogram rhythms. The device utilizes the computing power of Apple iOS- and Google Android-based smartphones to obtain and analyze single-channel ECG. These smartphones are termed Mobile Computing Platforms (MCPs). The device consists of the hardware (that has the electrodes), and the Kardia phone app (installed on an MCP). The same software is implemented in the iOS and Android MCP. In either configuration, the same hardware is used to sense the ECG. The KardiaMobile Hardware transmits the ECG signal from the electrode to the Kardia phone app on the MCP to be analyzed and presented to the user. All ECGs are synced with the user's account.
The provided text describes the acceptance criteria and the study conducted for the KardiaMobile System, primarily focusing on proving that the device meets special controls for Electrocardiograph Software for Over-the-Counter Use, especially after the removal of a "clinician overread" function.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not provide a direct table of numerical "acceptance criteria" (e.g., minimum sensitivity/specificity percentages) and corresponding "reported device performance" values for the AI algorithm suite (KardiaAI SaMD). Instead, it states that the performance characteristics (sensitivity and specificity) were "tested to meet the system requirements" against ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases.
However, the "Special Control" table implicitly functions as acceptance criteria for different aspects of the device's performance and the "Summary of Conformance" column indicates the reported performance/compliance.
Acceptance Criteria (Implicit from Special Controls) and Reported Device Performance (Summary of Conformance):
| Acceptance Criteria (Special Control) | Reported Device Performance (Summary of Conformance) |
|---|---|
| 1. Clinical performance testing under anticipated conditions of use must demonstrate: | |
| (a) The ability to obtain an ECG of sufficient quality for display and analysis; and | The KardiaMobile device has demonstrated its ability to obtain ECGs of sufficient quality for display and analysis through both bench and clinical performance testing. (Long history of real-world use and real-world use data supports that representative users can record ECG of equivalent quality to 12-lead ECG). |
| (b) The performance characteristics of the detection algorithm as reported by sensitivity and either specificity or positive predictive value. | The KardiaMobile System leverages the KardiaAI SaMD (K181823) for ECG analysis. KardiaAI algorithm suite ECG detection algorithm outputs of Atrial Fibrillation, Normal, Bradycardia, Tachycardia, and Noise as well as the heart rate calculations were tested to meet the system requirements for sensitivity and specificity. Testing was conducted to ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases. |
| 2. Software verification, validation, and hazard analysis must be performed. Documentation must include a characterization of the technical specifications of the software, including the detection algorithm and its inputs and outputs. | Software documentation for the KardiaMobile software was prepared and provided in accordance with FDA's Guidance titled, Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (May 11, 2015). (Further specifically stated that software V&V was done per FDA's "General Principles of Software Validation," Jan 11, 2002.) |
| 3. Non-clinical performance testing must validate detection algorithm performance using a previously adjudicated data set. | KardiaAI algorithm suite ECG detection algorithm outputs of Atrial Fibrillation, Normal, Bradycardia, Tachycardia, and Noise as well as the heart rate calculations were tested to meet the system requirements for sensitivity and specificity. Testing was conducted to ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases. These validation datasets are representative of the patient population of the proposed device. |
| 4. Human factors and usability testing must demonstrate the following: | |
| (a) The user can correctly use the device based solely on reading the device labeling; and | |
| (b) The user can correctly interpret the device output and understand when to seek medical care. | Human factors evaluation was performed in accordance with recommendations in IEC62366-1:2015 and FDA's Guidance Document; Applying Human Factors and Usability Engineering to Medical Devices. |
| The study found that the user can correctly use the device solely based on on-screen guidance and the users understand the device output. The study also found that users understand when to seek care regardless of the output of the device. (Specifically tested addressing the removal of "unlock overread" function). | |
| Labeling must include specific information (hardware/OS requirements, performance limitations, clinical performance summary, device measures/outputs, guidance on interpretation). | Provided within applicable sections of the KardiaMobile Instructions for Use and User Manual documents and within on-screen instructions to the user within the software. |
2. Sample Sizes Used for the Test Set and Data Provenance
- Sample Size for Algorithmic Performance (KardiaAI SaMD): The document states that the KardiaAI SaMD (K181823), leveraged by the KardiaMobile System for ECG analysis, was validated using "ANSI/AAMI EC57:2012 databases and AliveCor's proprietary databases." It also notes that these "validation datasets are representative of the patient population of the proposed device."
- Specific sample sizes are NOT provided for these databases.
- Data Provenance: Not explicitly stated regarding country of origin. The use of "ANSI/AAMI EC57:2012 databases" suggests a standardized, likely diverse, source, while "AliveCor's proprietary databases" could be from various global or specific regions. The document does not specify if the data was retrospective or prospective for the algorithmic validation, but typically such databases are compiled retrospectively.
- Sample Size for Human Factors and Usability Testing: Not explicitly stated, but it refers to "representative users."
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
- For Algorithmic Performance (KardiaAI SaMD): The document states that the detection algorithm performance was validated using a "previously adjudicated data set" (Special Control 3) and mentions that for the primary predicate, the "overread unlock" mechanism involved review by a "board-certified cardiologist." However, it does not explicitly state the number or specific qualifications (e.g., years of experience) of experts used to establish the ground truth for the test sets used for the KardiaAI algorithm validation. Adjudicated data implies expert review, but details are absent.
4. Adjudication Method for the Test Set
- For Algorithmic Performance (KardiaAI SaMD): The document mentions "previously adjudicated data set." No specific adjudication method (e.g., 2+1, 3+1) is detailed.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- No MRMC comparative effectiveness study, comparing human readers with AI vs. without AI assistance, is mentioned. The focus of the changes and testing described is on the device's standalone performance and human factors/usability for over-the-counter use after removing the "overread" requirement.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
- Yes. The document explicitly states: "The KardiaMobile System leverages the KardiaAI SaMD (K181823) for ECG analysis. KardiaAI algorithm suite ECG detection algorithm outputs of Atrial Fibrillation, Normal, Bradycardia, Tachycardia, and Noise as well as the heart rate calculations were tested to meet the system requirements for sensitivity and specificity." This indicates that the core AI algorithm's performance was evaluated independently (without human-in-the-loop for its direct analytical output).
7. The Type of Ground Truth Used
- For Algorithmic Performance (KardiaAI SaMD): "Previously adjudicated data set." This typically implies expert consensus (e.g., cardiologists reviewing ECGs). It does not mention pathology or outcomes data as the ground truth directly for the AI algorithm's performance.
8. The Sample Size for the Training Set
- Not specified. The document focuses on the validation/test sets (ANSI/AAMI EC57:2012 and AliveCor's proprietary databases) for the KardiaAI algorithm. Information regarding the training set's size is not provided.
9. How the Ground Truth for the Training Set Was Established
- Not specified. As the training set size itself is not mentioned, neither is the method for establishing its ground truth.
§ 870.2920 Telephone electrocardiograph transmitter and receiver.
(a)
Identification. A telephone electrocardiograph transmitter and receiver is a device used to condition an electrocardiograph signal so that it can be transmitted via a telephone line to another location. This device also includes a receiver that reconditions the received signal into its original format so that it can be displayed. The device includes devices used to transmit and receive pacemaker signals.(b)
Classification. Class II (performance standards).