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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 arrhythmias. It is also indicated for patients who have been previously diagnosed with atrial fibrillation or who are susceptible to developing atrial fibrillation.

The Confirm RxTM ICM has not been specifically tested for pediatric use.

The Confirm Rx™ Insertable Cardiac Monitor (ICM) Model DM3500 is intended as a minimally invasive, implantable diagnostic monitoring device, with subcutaneous electrodes, looping memory, and automatic as well as patient-activated EGM storage capability, which help physicians monitor, diagnose, and document patients who are susceptible to cardiac arrhythmias. It has a two-year longevity, MR conditional labeling, sensing and detection algorithms, and Bluetooth communication. Specific features include:

• Patient-initiated triggering of EGM storage using the myMerlin™™ Patient App for mobile devices. This includes capability for the patient to identify symptoms, which are stored with the EGM for physician review.
• Automated triggering of EGM storage when tachycardia, bradycardia, or pauses are detected; with physician-programmable values for pause duration, bradycardia rate, tachycardia rate, and number of tachycardia intervals.
• Automated triggering of EGM storage when atrial fibrillation (AF) is detected, with physician programmable values for AF duration.
• The ability to identify EGM anomalies as a consequence of noise or vigorous activity and inhibit EGM storage as applicable.
• Remote care monitoring.

The provided document is a 510(k) premarket notification for the Abbott Confirm Rx™ Insertable Cardiac Monitor (ICM) System, Model DM3500, with updated firmware. The purpose of this submission is to demonstrate substantial equivalence to a predicate device (K182981).

The document details the device description, technological characteristics, and the testing conducted to support the substantial equivalence claim. However, it does NOT contain a detailed study proving the device meets specific acceptance criteria for AI/algorithm performance as would be typically found for new AI-driven diagnostic devices. Instead, the focus is on demonstrating that the updated firmware, particularly its detection algorithms, functions as intended without raising new issues of safety and effectiveness compared to the predicate device.

Specifically, the acceptance criteria and performance data are described in terms of verification and validation activities showing the device meets its "predetermined design and performance specifications" and "functions in accordance with product specifications." The changes in the firmware relate to "detection algorithms for the diagnosis of bradycardia, asystole (pause), and atrial fibrillation (AF)," including "second pass undersensing discriminators" and a "P-wave detection discriminator."

Given the information provided, it's not possible to present a table of acceptance criteria and reported device performance in the context of an AI study as you described.

However, I can extract the relevant information regarding the firmware update validation and
address the closest approximations to your questions for this type of medical device submission.

Analysis of the Provided Document Regarding Acceptance Criteria and Study:

The document describes an update to the firmware of an existing, already cleared device. The "study" here is the validation of the firmware update to ensure it doesn't negatively impact safety or effectiveness and that the new algorithms perform as intended.

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

The document states that the "Completion of all verification and validation activities demonstrated that the device with updated firmware meets its predetermined design and performance specifications and that the product is substantially equivalent to the predicate Confirm Rx™ ICM device (K182981)." It also states, "The results of the testing show that the candidate Confirm RxTM ICM performs as intended and is safe for its intended use."

The updated firmware includes changes to detection algorithms for bradycardia, asystole (pause), and atrial fibrillation (AF). The acceptance criteria would inherently be related to the accuracy and reliability of these detections compared to established benchmarks or the predicate device, although specific numerical performance metrics (e.g., sensitivity, specificity, accuracy percentages) are not detailed in this summary.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document does not specify the sample size (number of patients, number of EGM recordings) used for the verification and validation (V&V) testing. It also does not specify the data provenance (country of origin, retrospective/prospective). This type of detail is typically found in the full testing report, not usually summarized in this section of a 510(k) summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

The document does not specify the number or qualifications of experts used to establish ground truth. For embedded device algorithm testing, ground truth might often be established through simulated signals, pre-recorded clinical data with confirmed diagnoses, or expert review of EGMs, but this detail is not provided.

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

The document does not specify any adjudication method for ground truth establishment.

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, an MRMC comparative effectiveness study was not conducted or described. This is a device firmware update, not a new AI-assisted diagnostic tool where human reader performance would be compared. The focus is on the device's internal algorithm performance.

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

Yes, the testing described appears to be a standalone validation of the algorithm's performance within the device, given the context of "Software/Firmware Verification and System Verification" and "Design Validation." The purpose is to confirm the algorithm's internal logic and detection capabilities. The document states:

• "Second pass undersensing discriminators added to the Asystole and Bradycardia detection algorithms to reject false Pause and Bradycardia detections."
• "Second pass P-wave detection discriminator to reject false AF detections."

This implies that the algorithm itself was tested for its ability to correctly identify and reject false detections, which is a standalone performance metric.

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

The type of ground truth is not explicitly stated. For cardiac rhythm detection algorithms, ground truth typically involves a highly accurate reference ECG/EGM interpretation, which could be established via:

• Expert Consensus: Review by multiple cardiologists or electrophysiologists.
• Manual Annotation: Beat-by-beat or episode-by-episode annotation of EGM data by trained personnel, often adhering to specific criteria.
• Validation against high-fidelity recordings: Comparing device output to a gold-standard recording from a different, validated system.

Given the focus on "reject[ing] false detections," it implies that there was a reference against which the algorithm's detection (true positive/false positive) was measured.

8. The sample size for the training set

The document does not provide any information about a training set size. This indicates that this submission is about validating a firmware update for an already cleared device, not seeking de novo clearance for a new machine learning algorithm that typically requires a distinct training phase. While the algorithms were likely "trained" or designed using data at some point in their development, that information is not part of this 510(k) summary for a firmware update.

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

Since there is no mention of a training set in this document, there is no information on how its ground truth was established.

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The Confirm RxIM ICM is indicated for the monitoring and diagnostic evaluation of patients who experience wersplained symptoms such as: dizziness, palpitations, chest pain, syncope, and shortness of breath, as well as patients who are at risk for cardiac arrhythmias. It is also indicated for patients who have been previously diagnosed with atrial fibrillation or who are susceptible to developing atrial fibrillation.

The Confirm RxIM ICM has not been specifically tested for pediatric use.

The ICM is intended as a minimally invasive, implantable diagnostic monitoring device, with subcutaneous electrodes, looping memory, and automatic as well as patient-activated EGM storage capability, which help physicians monitor, diagnose, and document patients who are susceptible to cardiac arrhythmias. It has a two-year longevity, MR conditional labeling, sensing and detection algorithms, and Bluetooth communication. Specific features include:

• Patient-initiated triggering of EGM storage using the myMerlin™™ Patient App for o mobile devices. This includes capability for the patient to identify symptoms, which are stored with the EGM for physician review.
• Automated triggering of EGM storage when tachycardia, bradycardia, or pauses are o detected; with physician-programmable values for pause duration, bradycardia rate, tachycardia rate, and number of tachycardia intervals.
• Automated triggering of EGM storage when atrial fibrillation (AF) is detected, with O physician programmable values for AF duration.
• The ability to identify EGM anomalies as a consequence of noise or vigorous activity o and inhibit EGM storage as applicable.
• Remote care monitoring. o

Here's an analysis of the provided text regarding the Abbott Confirm Rx Insertable Cardiac Monitor (ICM) System, Model DM3500, focusing on acceptance criteria and the supporting study:

Important Note: The provided document is a 510(k) clearance letter and related submission materials. It primarily focuses on demonstrating "substantial equivalence" to a predicate device rather than presenting a detailed standalone performance study with comprehensive acceptance criteria and results for the new device. Therefore, some of the requested information (like specific performance metrics and their ranges) is not explicitly listed as "acceptance criteria" and "reported device performance" in the way one might expect for a de novo device clearance. The document emphasizes that the fundamental technological characteristics are not changing, and the focus is on minor firmware updates and a manufacturing material change.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned, the document doesn't explicitly define a table of new acceptance criteria with numerical performance targets and reported results for the DM3500 in the way a clinical study report would. Instead, it states that the device "meets its predetermined design and performance specifications" and "performs as intended and is safe for its intended use."

The "acceptance criteria" are implied by the verification and validation activities conducted to ensure the device with the minor changes:

• Functions in accordance with product specifications.
• Performs as intended.
• Is safe for its intended use.
• Is substantially equivalent to the predicate (K163407).

The reported device performance is therefore that these criteria were met, specifically through:

• Firmware Verification and System Validation: This would ensure the updated firmware functions correctly and that the overall system operates as specified.
• Mechanical Performance Testing: This would verify the mechanical integrity and function of the device with the new UV Cure material.

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

The document does not specify a "test set" sample size in terms of patient data or clinical cases. The testing conducted was primarily bench testing and system validation for the firmware and mechanical changes. No clinical study on human subjects is mentioned for this particular 510(k) submission.

• Sample Size: Not applicable in the context of human clinical data. For engineering verification and validation, it would refer to the number of devices or test units, which is not stated.
• Data Provenance: Not applicable for clinical data. The testing described is internal engineering and validation testing.

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

Not applicable. This submission is for a device modification (firmware update and material change) and relies on engineering verification and validation, not on expert adjudication of diagnostic performance on a test set of clinical cases. The "ground truth" here would be the predefined functional and performance specifications of the device.

4. Adjudication Method for the Test Set

Not applicable. As no clinical test set requiring human adjudication is described, there is no adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC study was done and none is described. This device is an insertable cardiac monitor, and its capabilities are assessed through its detection algorithms and hardware performance, not through human interpretation of its outputs in a comparative effectiveness study involving reader performance improvement with AI.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The device's core function is automatic detection of cardiac events (tachycardia, bradycardia, pauses, AF). The document states:

• "Automated triggering of EGM storage when tachycardia, bradycardia, or pauses are detected"
• "Automated triggering of EGM storage when atrial fibrillation (AF) is detected"
• "The ability to identify EGM anomalies as a consequence of noise or vigorous activity and inhibit EGM storage as applicable."

The "Firmware Verification and System Validation" would have evaluated the performance of these algorithms in a standalone manner (without human intervention) against known inputs. However, no specific metrics (e.g., sensitivity, specificity for AF detection) from such a study are provided in this regulatory document. The statement implies that the existing algorithms (from the predicate) have been verified with the updated firmware.

7. Type of Ground Truth Used

For the Firmware Verification and System Validation, the ground truth would be:

• Predefined system specifications: The expected behavior and output of the device's firmware and algorithms under various conditions.
• Known input signals: Simulated or recorded ECG/EGM data with precisely defined events (e.g., specific heart rates, AF episodes, pauses) to test the detection algorithms.
• Mechanical engineering standards: For the mechanical performance testing.

8. Sample Size for the Training Set

Not applicable. The document does not describe the development of new AI algorithms that require a "training set." The firmware updates are described as "minor changes" to an existing ERI detection algorithm and magnet response, implying fine-tuning or bug fixes rather than a re-training of a predictive model.

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

Not applicable, as no training set for new AI algorithms is described.

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