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The iCare App is intended for use in the home and clinical settings as and their healthcare professionals to view test results which are measured by iHealth devices to better manage user's health and get feedback from their professional care team.

The iCare App can also connect to medical devices and or non-medical devices and get data from devices during measurement or from the data stored in memory of the device for enhanced data managements. Data can be transmitted, displayed, and stored in the App.

The iCare APP is a mobile application on both Android and iOS platforms.iCare allows users to better manage their own health by enabling them to measure their vital signs, access their results and relevant health information with just their smart device and internet connection, and receive feedback from their professional care team.

iCare includes a patient darshboard featuring the Home, Health, Plus, Education, and Profile tabs. Accessory devices can be connected to the system to allow for collection of blood sugar, blood pressure, blood oxygen, and/or weight measurements. The patient darshboard functionality includes the ability to start measuring, allows users to view and track measurements, and export testing schedules for blood sugar, blood pressure, blood oxygen, and weight measurements; send messages to their professional care team; view previous appointment history information; view medication instructions; add entries to the food diary and review feedback from their registered dietician; set timers; and access articles and videos about health knowledge.

The provided text is a 510(k) Summary for the iCare App, focusing on its substantial equivalence to a predicate device. It primarily details regulatory information, device description, and non-clinical test summaries. It does not contain information about a study that proves the device meets specific performance acceptance criteria for a medical diagnostic or screening function.

The iCare App is classified as a "Medical Device Data System" (MDDS) that transmits, displays, and stores data from connected medical devices. Its function is to aid users and healthcare professionals in viewing test results for health management. It explicitly states: "Both devices make no interpretation, evaluation, medical judgments, or recommendations for treatment." This means the app itself doesn't perform diagnostic functions that would require specific performance metrics like sensitivity, specificity, or AUC against a ground truth.

Therefore, many of the requested criteria, such as acceptance criteria for diagnostic performance, a test set, expert ground truth establishment, MRMC studies, or standalone algorithm performance, are not applicable or not provided in this document because the device is a data management system, not a diagnostic algorithm.

Here's a breakdown of the applicable information based on the provided text:

1. A table of acceptance criteria and the reported device performance

The document does not present a table of quantitative performance acceptance criteria for diagnostic accuracy, sensitivity, or specificity, because the iCare App is an MDDS for data management, not a diagnostic tool. Instead, acceptance criteria are implied through the successful completion of non-clinical tests that demonstrate the basic functionality, safety, and effectiveness for its intended use as a data display and storage system.

2. Sample sized used for the test set and the data provenance

• Sample Size for Test Set: Not applicable for diagnostic performance as the device is not a diagnostic algorithm. The document mentions non-clinical testing (software, wireless, cybersecurity, usability) but does not specify "test set" sizes in the context of clinical data for diagnostic performance.
• Data Provenance: Not applicable in the context of clinical diagnostic data. The document focuses on the technical aspects of the software.

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

• Number of Experts: Not applicable, as the device does not perform diagnostic interpretations requiring expert-established ground truth for clinical cases.
• Qualifications of Experts: Not applicable.

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

• Adjudication Method: Not applicable, as there is no clinical test set requiring ground truth adjudication for diagnostic performance.

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

• MRMC Study: No, an MRMC study was not done. The iCare App is an MDDS and does not involve AI assistance for human readers in a diagnostic capacity. It makes "no interpretation, evaluation, medical judgments, or recommendations for treatment."
• Effect Size: Not applicable.

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

• Standalone Performance: No, a standalone performance study in the context of diagnostic accuracy was not done. The device's function is data transmission, display, and storage, not diagnostic algorithm performance.

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

• Type of Ground Truth: Not applicable for clinical diagnostic performance. For the software verification and validation, the "ground truth" would be the successful execution against specified requirements and accepted software engineering practices and FDA guidance.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This document does not describe a machine learning model that was trained on a dataset. The iCare App is a software application for data management, not an AI/ML algorithm requiring a training set of clinical data for diagnostic purposes.

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

• Ground Truth Establishment for Training Set: Not applicable, as there is no mention of a training set for an AI/ML algorithm.

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The iHealth COVID-19 Antigen Rapid Test is a visually read lateral flow immunoassay device intended for the rapid, qualitative detection of SARS-CoV-2 virus nucleocapsid protein antigen directly in anterior nasal swab specimens from individuals with signs and symptoms of COVID-19 within the first 6 days of symptom onset. This test is for nonprescription home use by individuals aged 15 years or older testing themselves, or adults testing individuals aged 2 years or older.

The iHealth COVID-19 Antigen Rapid Test does not differentiate between SARS-CoV-2.

All negative results are presumptive. Symptomatic individuals with an initial negative test result must be re-tested once between 48 and 72 hours after the first test using either an antigen test or a molecular test for SARS-CoV-2. Negative results do not preclude SARS-CoV-2 infections or other pathogens and should not be used as for treatment. Positive results do not rule out co-infection with other respiratory pathogens.

This test is not a substitute for visits to a healthcare provider or appropriate follow-up and should not be used to determine any treatments without provider supervision. Individuals who test negative and experience continued or worsening COVID-19 like symptoms, such as fever, cough and/or shortness of breath, should seek follow up care from their healthcare provider.

The performance characteristics for SARS-CoV-2 were established from October 2022 to June 2023 when the COVID-19 variant Omicron was dominant. Test accuracy may change as new SARS-CoV-2 viruses emerge. Additional testing with a lab-based molecular test (e.g., PCR) should be considered in situations where a new virus or variant is suspected.

The iHealth COVID-19 Antigen Rapid Test employs lateral flow immunoassay technology. Using this test allows for the rapid detection of nucleocapsid protein from SARS-CoV-2.

To begin the test, a self-collected anterior nares swab sample in individuals aged 15 and older or individuals between the age of 2 to 14 with a swab collected by a parent or quardian is inserted into a tube that has been pre-filled with reagent. The reagent in the tube interacts with the specimen and facilitates exposure of the appropriate viral antigens to the antibodies used in the test. The liguid in the tube, now containing the specimen, is added to the Sample Port of the COVID-19 Test Card.

If the extracted specimen contains SARS-CoV-2 antigens, a pink-to-purple T Line, along with a pink-to-purple C Line will appear on the COVID-19 Test Card indicating a positive result. If SARS-CoV-2 antigens are not present at very low levels, only a pinkto-purple C Line will appear.

Acceptance Criteria and Study to Prove Device Meets Criteria: iHealth COVID-19 Antigen Rapid Test

The iHealth COVID-19 Antigen Rapid Test is a visually read lateral flow immunoassay device intended for the rapid, qualitative detection of SARS-CoV-2 virus nucleocapsid protein antigen directly in anterior nasal swab specimens from individuals with signs and symptoms of COVID-19 within the first 6 days of symptom onset. This test is for nonprescription home use by individuals aged 15 years or older testing themselves, or adults testing individuals aged 2 years or older.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: 915 individuals.
• Data Provenance:
  • Country of Origin: United States (investigational sites throughout the U.S.).
  • Retrospective or Prospective: Prospective. The clinical performance characteristics were evaluated in a study where subjects with signs and symptoms of COVID-19 were enrolled, collected samples, and the test was performed. Data was collected between October 2022 to June 2023.

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

The document does not explicitly state the number of "experts" used for ground truth or their specific qualifications for the clinical study.

• Ground Truth Method: The iHealth COVID-19 Antigen Rapid Test results were compared to a highly sensitive molecular FDA EUA Authorized SARS-CoV-2 assays (RT-PCR) to determine test performance. This molecular test is considered the gold standard for SARS-CoV-2 detection, establishing the definitive ground truth for the presence or absence of the virus.

4. Adjudication Method for the Test Set

The document indicates that for discordant results (false positives or false negatives against the initial comparator method), a "second FDA EUA high sensitivity molecular SARS-CoV-2 assay" was used. This suggests a form of 2+1 adjudication where the initial comparator result is one "read," the iHealth test result is the other, and a second molecular assay acts as the tie-breaker or confirmatory truth.

• Specifically:
  • Of 13 false negative samples (iHealth negative, comparator positive), 1 was confirmed negative by a second molecular assay, and 12 were confirmed positive.
  • Of 1 false positive sample (iHealth positive, comparator negative), it was confirmed positive by a second molecular assay.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No, an MRMC comparative effectiveness study was not explicitly done in the context of comparing human readers with and without AI assistance, as this is an antigen rapid test that is visually read by lay users. The study evaluated the standalone performance of the test as interpreted by lay users (self-testers or adult testers for children).

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

For the clinical performance evaluation, the test was performed by lay users (individuals aged 15+ testing themselves, or adults testing individuals aged 2-14). Therefore, the clinical performance data presented (PPA, NPA) represents the device's performance with human-in-the-loop interpretation by the intended user. It is not a purely "algorithm-only" or "standalone" performance without any human involvement in interpreting the visual result. However, the device itself is a diagnostic test, not an AI/algorithm for image interpretation. The "algorithm" here (lateral flow immunoassay) is inherent to the device's physical mechanism.

Other analytical studies (precision, LoD, cross-reactivity, etc.) represent technical performance without human interpretation error as these are typically performed in a controlled lab setting by trained personnel.

7. The Type of Ground Truth Used

The primary ground truth for the clinical study (testing individuals) was established using a highly sensitive molecular FDA EUA Authorized SARS-CoV-2 assay (RT-PCR). For discordant results, a second molecular assay was used for confirmation.

8. The Sample Size for the Training Set

This document describes a premarket notification for a medical device (an antigen rapid test). It does not explicitly mention a "training set" in the context of machine learning. The term "training set" is typically used for AI/ML models. If the underlying assay development involved any statistical modeling or calibration, the data used for that would precede this type of submission. However, for a lateral flow immunoassay, the "training" involves optimizing the biochemical reagents and visual readout.

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

Given that this is a lateral flow immunoassay device and not an AI/ML diagnostic, the concept of a "training set" with established ground truth as commonly understood in AI/ML is not directly applicable. The "ground truth" during the development and optimization phases would involve rigorous analytical validation using known positive and negative samples, purified viral cultures, and clinical samples characterized by gold standard molecular tests (like RT-PCR), similar to the analytical studies detailed (e.g., LoD, inclusivity, cross-reactivity) but performed during product development before clinical trials.

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