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The Reveal LINQ ICM is an insertable automatically-activated monitoring system that records subcutaneous ECG and is indicated in the following cases:

· Patients with clinical syndromes or situations at increased risk of cardiac arrhythmias

· Patients who experience transient symptoms such as dizziness, palpitation, syncope, and chest pain that may suggest a cardiac arrhythmia

The device has not been tested specifically for pediatric use.

The Reveal LINQ Model LNQ11 Insertable Cardiac Monitors (ICM) is designed to automatically record the occurrence of arrhythmias in a patient. Arrhythmia may be classified as atrial tachyarrhythmia/atrial fibrillation (AT/AF), bradyarrhythmia, pause, or (fast) ventricular tachyarrhythmia. The Reveal LINO ICM provides storage of ECG and Marker Channel during patient-activated and automatically-detected (auto-activated) events. Auto activation may help to detect abnormal heart rhythms in patients who may not activate/trigger the ICM.

The Reveal LINQ ICM Model LNQ11 is a small, leadless device that is typically implanted under the skin, in the chest. Two electrodes on the body of the device continuously monitor the patient's subcutaneous ECG.

The provided text describes a 510(k) premarket notification for the Medtronic Reveal LINQ Insertable Cardiac Monitor (Model LNQ11). The submission details minor firmware changes to enhance atrial and ventricular arrhythmia detection algorithms. The primary purpose of this document is to demonstrate substantial equivalence to a predicate device.

Here's an analysis of the provided information regarding acceptance criteria and the study that proves the device meets them:

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

The document broadly states that "The results of the above testing met the specified acceptance criteria and did not raise new safety or performance issues." However, specific quantitative acceptance criteria and corresponding reported device performance metrics are NOT provided in a table format, or explicitly stated otherwise. The text refers to meeting "established performance criteria" and adhering to the ANSI/AAMI EC57:1998 standard for testing cardiac rhythm algorithms, but the actual performance numbers against defined thresholds are not given for direct comparison.

It only mentions the addition of "three rules to reduce false positive detections":

• Atrial Algorithms Adaptive P-sense rule
• Dual Sense Brady rejection rule
• Dual Sense Asystole rejection rule

This indicates an improvement aim, but the metrics of that improvement (e.g., how much false positives were reduced, or what the new sensitivity/specificity values are) are not detailed.

2. Sample size used for the test set and the data provenance:

The document mentions "Firmware regression testing, design verification, system verification, and system design validation testing." It specifically states that "The validation for the changes to enhance the atrial and ventricular algorithms of the Reveal LINQ ICM firmware was based on the ANSI/AAMI EC57:1998 standard for Testing and Reporting Performance Results of Cardiac Rhythm and ST Segment Measurement Algorithms."

The specific sample sizes (number of patients or ECG recordings) used for the test set for these validations are NOT explicitly stated.

Data provenance (country of origin, retrospective/prospective) is NOT provided. The ANSI/AAMI EC57:1998 standard generally uses standardized ECG databases or collected patient recordings, but the origin of the data used in this specific study is not specified in the provided text.

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

This information is NOT consistently present in the provided text. The document describes a device that automatically detects arrhythmias, and its validation against a standard (ANSI/AAMI EC57:1998). This standard often involves the use of meticulously annotated ECG datasets where ground truth is established by clinical experts. However, the exact number and qualifications of experts involved in establishing the ground truth for the specific test set used by Medtronic for this submission are not detailed.

4. Adjudication method for the test set:

The adjudication method is NOT explicitly stated. If ground truth was established by experts, an adjudication process (e.g., 2+1 majority voting, consensus) would typically be employed, but the document does not describe it.

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:

No MRMC comparative effectiveness study involving human readers is described. The device is an "Insertable Cardiac Monitor" that automatically detects arrhythmias. The study focuses on the device's algorithmic performance against established standards, not on human interpretation or improvement with AI assistance.

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

Yes, a standalone (algorithm only) performance assessment was done. The entire focus of the "Summary of Testing" section is on the performance of the modified firmware (algorithm) in detecting arrhythmias automatically. This includes "Firmware regression testing," "Firmware design verification," and "System level testing" which "ensured that the proposed modifications did not impact the existing system level design inputs" and "confirmed through a combination of test and analysis that the stakeholder needs and intended use continued to be met." The validation was explicitly "based on the ANSI/AAMI EC57:1998 standard for Testing and Reporting Performance Results of Cardiac Rhythm and ST Segment Measurement Algorithms," which is a standard for standalone algorithm performance.

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

While not explicitly stated for this specific study, the ANSI/AAMI EC57:1998 standard typically relies on expert-annotated ECG recordings where ground truth for cardiac rhythm events (e.g., AT/AF, bradyarrhythmia, pause, ventricular tachyarrhythmia) is established. Given the nature of cardiac arrhythmia detection, the ground truth would be based on the precise identification and classification of ECG events.

8. The sample size for the training set:

The sample size for the training set is NOT provided. The submission focuses on changes to existing algorithms and their validation, not on the details of the initial algorithm development and training data.

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

This information is NOT provided. Similar to the training set size, the document does not describe how the ground truth for the training data (if any re-training was performed, or for the original algorithm development) was established.

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