(87 days)
The IRNF is a software-only mobile medical application that is intended to be used with the Apple Watch. The feature analyzes pulse rate data to identify episodes of irregular heart rhythms suggestive of atrial fibrillation (AFib) and provides a notification to the user. The feature is intended for over-the-counter (OTC) use. It is not intended to provide a notification on every episode of irregular rhythm suggestive of AFib and the absence of a notification is not intended to indicate no disease process is present; rather the feature is intended to opportunistically surface a notification of possible AFib when sufficient data are available for analysis. These data are only captured when the user is still. Along with the user's risk factors the feature can be used to supplement the decision for AFib screening. The feature is not intended to replace traditional methods of diagnosis or treatment.
The feature has not been tested for and is not intended for use in people under 22 years of age. It is also not intended for use in individuals previously diagnosed with AFib.
IRNF 2.0 is comprised of a pair of mobile medical apps - One on Apple Watch and the other on the iPhone.
IRNE 2.0 is intended to analyze pulse rate data collected by the Apple Watch PPG sensor on Apple Watch Series 3-8, Series SE, and Apple Watch Ultra to identify episodes of irregular heart rhythms consistent with AFib and provides a notification to the user. It is a background screening tool and there is no way for a user to initiate analysis of pulse rate data. IRNF 2.0 iPhone App is part of the Health App, which allows users to store, manage, and share health and fitness data, and comes pre-installed on every iPhone.
IRNF 2.0 Watch App refers to the tachogram classification algorithm, confirmation cycle algorithm, and the AF notification generation. If an irreqular heart rhythm consistent with AFib is identified, IRNF 2.0 Watch App will transfer the AFib notification to IRNF 2.0 iPhone App through HealthKit sync. In addition to indicating the finding of signs of AFib, the notification will encourage the user to seek medical care.
IRNF 2.0 iPhone App contains the on-boarding and educational materials that a user must review prior to enabling AFib notifications. IRNF 2.0 iPhone App is designed to work in combination with IRNF 2.0 Watch App and will display a history of all prior AFib notifications. The user is also able to view a list of times when each of the irregular tachograms contributing to the notification was generated.
The provided text describes the Irregular Rhythm Notification Feature (IRNF) 2.0. However, the document provided is a 510(k) summary and clearance letter for a Predetermined Change Control Plan (PCCP) for IRNF 2.0, rather than a standalone study proving the device meets acceptance criteria for initial clearance.
The document indicates that the subject device (IRNF 2.0) is identical to its predicate device (also IRNF 2.0, K212516), with the only difference being the implementation of a PCCP. This PCCP outlines anticipated modifications to the software and the methods for implementing those changes. Therefore, the acceptance criteria and study data for the initial clearance of IRNF 2.0 (K212516) would be the most relevant information, which is not entirely detailed in this document.
However, the PCCP does specify test methods and acceptance criteria that will be used to demonstrate substantial equivalence for future modifications made under the plan. I will extract information primarily related to these future modification criteria and the study that would be performed to meet them.
Here's a breakdown based on the provided text, focusing on the PCCP and what it implies for future studies:
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria described here are for future modifications to the algorithm under the PCCP, showing substantial equivalence to the performance of the existing IRNF 2.0. The document does not provide the absolute performance of IRNF 2.0 itself in this section, but rather the performance target for modified algorithms relative to IRNF 2.0.
| Category of Change | Acceptance Criteria | Reported Device Performance (as described for future modifications) |
|---|---|---|
| Modifications to Tachogram Classification Algorithm | Substantial equivalence in sensitivity and specificity when compared to the performance of IRNF 2.0 | To be demonstrated in future validation activities under the PCCP, by meeting the specified substantial equivalence in sensitivity and specificity criteria. |
| Modifications to Confirmation Cycle Algorithm | Substantial equivalence in positive predictive value relative to IRNF 2.0 | To be demonstrated in future validation activities under the PCCP, by meeting the specified substantial equivalence in positive predictive value criteria. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document states that for future modifications under the PCCP, "each will meet minimum demographic requirements for age, sex, race, and skin tone derived from the demographics of the United States." It does not specify an exact numerical sample size for the test set.
- Data Provenance: The document implies that validation test datasets will be "representative of the intended use population" and mentions "demographics of the United States." This suggests the data will primarily be from the United States. It does not explicitly state whether the data will be retrospective or prospective for these future validation activities.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
The document does not specify the number of experts or their qualifications for establishing ground truth, either for the initial clearance of IRNF 2.0 or for the future modifications under the PCCP.
4. Adjudication Method for the Test Set
The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for the test set, either for the initial clearance of IRNF 2.0 or for the future modifications under the PCCP.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The IRNF is described as a "software-only mobile medical application" providing notifications to the user, not a tool for human readers to interpret.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, the document implies that standalone performance studies were done (or will be done for future modifications). The device is described as "software-only" and "analyzes pulse rate data... and provides a notification to the user." The acceptance criteria for future modifications explicitly refer to the algorithm's sensitivity, specificity, and positive predictive value, which are metrics of standalone algorithm performance.
7. The Type of Ground Truth Used
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). In the context of "irregular heart rhythms suggestive of atrial fibrillation (AFib)," the ground truth would typically be established by a gold standard method such as a 12-lead ECG interpreted by a cardiologist, or a continuous ECG monitor.
8. The Sample Size for the Training Set
The document states that for future modifications to the tachogram classification algorithm, the plan is to "retrain algorithm with additional datasets." It does not specify the sample size for the training set, either for the original IRNF 2.0 or for the "additional datasets" mentioned for future retraining.
9. How the Ground Truth for the Training Set Was Established
The document does not specify how the ground truth for the training set was established, either for the original IRNF 2.0 or for future retraining datasets.
§ 870.2790 Photoplethysmograph analysis software for over-the-counter use.
(a)
Identification. A photoplethysmograph analysis software device for over-the-counter use analyzes photoplethysmograph data and provides information for identifying irregular heart rhythms. This device is not intended to provide a diagnosis.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Clinical performance testing must demonstrate the performance characteristics of the detection algorithm under anticipated conditions of use.
(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.
(3) Non-clinical performance testing must demonstrate the ability of the device to detect adequate photoplethysmograph signal quality.
(4) Human factors and usability testing must demonstrate the following:
(i) The user can correctly use the device based solely on reading the device labeling; and
(ii) The user can correctly interpret the device output and understand when to seek medical care.
(5) Labeling must include:
(i) Hardware platform and operating system requirements;
(ii) Situations in which the device may not operate at an expected performance level;
(iii) A summary of the clinical performance testing conducted with the device;
(iv) A description of what the device measures and outputs to the user; and
(v) Guidance on interpretation of any results.