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510(k) Data Aggregation
(29 days)
myMerlin(TM) Mobile Application Model APP1001
The Confirm Rx™ ICM is indicated for the monitoring and diagnostic evaluation of patients who experience unexplained symptoms such as: dizziness, palpitations, chest pain, syncope, and shortness of breath, as well as patients who are at risk for cardiac arthythmias. It is also indicated for patients who have been previously diagnosed with atrial fibrillation or who are susceptible to developing atrial fibrillation.
The myMerlin™ mobile application Model APP1001 is an application for patients who are implanted with the Confirm Rx™ Insertable Cardiac Monitor (ICM) Model DM3500 (K163407). The mobile application is used by patients to initiate recording of the heart's electrical activity by the Confirm Rx™ ICM device, read the information about the heart's activity from the Confirm Rx™ ICM device, and send this information to a clinician for remote monitoring. The myMerlin™ mobile application Model APP1001 is to be installed on a patient's mobile device with the iOS operating system which meets the specified minimum criteria for compatibility with the myMerlin™ mobile application.
This is a response to the question regarding the acceptance criteria and study proving the device meets the criteria. Based on the provided FDA 510(k) summary for the myMerlin™ Mobile Application, Model APP1001, here's an analysis of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state specific numerical acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) or detailed performance metrics for the myMerlin™ Mobile Application, Model APP1001. Instead, the document focuses on demonstrating substantial equivalence to a predicate device (myMerlin™ Mobile Application Model APP1000).
The "performance" is implicitly defined by the device fulfilling its intended functions, which are:
- Initiating recording of the heart's electrical activity by the Confirm Rx™ ICM device.
- Reading information about the heart's activity from the Confirm Rx™ ICM device.
- Sending this information to a clinician for remote monitoring.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Device functions in accordance with product specifications. | "The results of the verification and validation tests and the risk analysis have demonstrated the myMerlin™ mobile application Model APP1001 functions in accordance with product specifications." |
| All hazards identified and risks mitigated to an acceptable level. | "The risk analysis method used to assess the impact of the modification of the myMerlin™ mobile application Model APP1001 documents the investigation of hazards and mitigation of risks associated with its use and reports the result of the investigation. The risk analysis method used to assess the impact of the modifications was a Failure Mode and Effects Analysis (FMEA/FMECA). It was determined that the overall risk is acceptable." |
| Substantially equivalent to predicate device (APP1000). | "Completion of all verification and validation activities demonstrated that the candidate device meets its predetermined design and performance specifications and that the product is substantially equivalent to the predicate device (Model APP1000, K163407)." and "Thus, the myMerlin™ mobile application Model APP1001 to be substantially equivalent to the predicate myMerlin™ mobile application (APP1000, K163407, cleared on September 29, 2017)." |
| No impact on existing Indications for Use. | "The indications for use are not impacted by the inclusion of the myMerlin™ mobile application Model APP1001." |
| Fundamental technological characteristics are the same. | "The fundamental technological characteristics of the myMerlin™ mobile application Model APP1001 are the same as the predicate myMerlin™ mobile application Model APP1000 (K163407)." (The primary difference being the operating system: iOS vs. Android). |
2. Sample Size Used for the Test Set and the Data Provenance
The document does not explicitly state a "test set" in the context of clinical data or patient samples. The evaluation appears to be based on non-clinical testing, specifically verification and validation (V&V) activities and risk analysis (FMEA/FMECA) related to software functionality and safety. Therefore, information about data provenance (e.g., country of origin, retrospective/prospective) for a test set of patient data is not provided as it doesn't appear to be a clinical study.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
Since the document describes non-clinical software V&V and risk analysis, there is no mention of "experts" establishing ground truth in the context of medical image interpretation or diagnosis. The "ground truth" for V&V would be the predefined functional and performance specifications.
4. Adjudication Method for the Test Set
Not applicable, as there is no mention of a "test set" requiring adjudication in a clinical context.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed or described in this 510(k) summary. The device is a mobile application for data transmission and initiation of recording, not a diagnostic algorithm requiring human interpretation of its output.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
The evaluation described is essentially a standalone assessment of the software's functionality and safety (V&V, FMEA). However, it's not an "algorithm-only" performance in the sense of a diagnostic algorithm because its primary function is data acquisition and transmission, not independent diagnosis. Its performance is validated against its specifications for these functions.
7. Type of Ground Truth Used
For the non-clinical testing (verification and validation), the "ground truth" would be the predefined design specifications and functional requirements of the software, as well as established software engineering best practices and regulatory standards for medical device software. For the risk analysis (FMEA/FMECA), the ground truth is the identification of potential failure modes and their associated risks, evaluated against acceptable risk levels.
8. Sample Size for the Training Set
Not applicable. This device is a mobile application for data management and transmission, not an AI/ML algorithm that requires a "training set" of data for learning or pattern recognition.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no training set mentioned for this device.
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