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AUDICOR CA300/CC100 Analyzer with SDB is a software-only system intended to be used to analyze recordings from AUDICOR-compatible recording devices.

AUDICOR CA300/CC100 Analyzer with SDB is capable of analyzing, editing, storing and reporting ECG, heart sound, sleep-disordered breathing (SDB), snoring detection, body position and activity level. An interpretation of the analysis results is produced in an integrated report for consideration by physicians.

The AUDICOR CA300/CC100 Analyzer with SDB software is intended for use on adults 18 years of age and older. The SDB analysis and reporting is intended for use on adult patients as a screening device for obstructive or mixed apnea to determine the need for evaluation by polysomnography based on the patient's screened for SDB should have periods of sleep of at least 4 hours duration.

AUDICOR CA300/CC100 Analyzer with SDB is intended to be used by trained operators under the direct supervision of a physician in a hospital or clinic environment.

AUDICOR CA300/CC100 Analyzer is a software-only system for the analysis of physiologic signals acquired through AUDICOR-compatible recording devices. Analysis results from ECG, heart sound, sleep-disordered breathing, snoring sounds, body position and activity levels are automatically interpreted. The AUDICOR CA300/CC100 software system allows for the review, edit, and storage of the analysis results. Reporting of analysis results is provided, together with patient data and notable events for review by the clinician.

The AUDICOR Analyzer software analyzes and reports the following parameters:

• Heart rate including bradycardia and tachycardia events .
• Atrial fibrillation ●
• ECG beat classification and morphology grouping with user-editing ●
• Heart rate variability ●
• Snoring detection ●
• Sleep disordered breathing events
• Sleep disordered breathing score
• Activity level ●
• Body Position
• Heart sound and combined ECG/heart sound measurements
• Heart rate distributions of heart sound parameters ●

Here's a breakdown of the acceptance criteria and study information for the AUDICOR CA300/CC100 Analyzer with SDB, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical "acceptance criteria" for the device's performance in a table format. Instead, it describes capabilities and then broadly concludes that non-clinical and clinical testing demonstrate the device's functionality and performance are comparable (for non-clinical) and statistically equivalent (for clinical, regarding a specific new feature) to the predicate device.

However, based on the narrative, the implicit acceptance criterion for the clinical study was statistical equivalence between the subject device's new aggregation method and the predicate device's aggregation method.

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

• Sample Size for Test Set: 252 subjects
• Data Provenance: Retrospective analysis of AUDICOR AM data. The country of origin is not specified, but the submission is to the U.S. FDA, implying the data might be from the US or a region with similar clinical practices.

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

The document does not explicitly state the number of experts or their qualifications used to establish ground truth for the test set in the clinical study. It mentions the study subjects included a cohort "clinically diagnosed with heart failure" and a cohort "determined to be negative for heart failure." This suggests that the clinical diagnoses used as ground truth were established by medical professionals in a clinical setting, but the specifics of who and how many made these diagnoses for the purpose of this study's ground truth are not detailed.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for establishing ground truth for the test set. It mentions cohorts "clinically diagnosed" or "determined to be negative" for heart failure, implying standard clinical diagnostic processes were followed, rather than a specific adjudication protocol by a panel for the study.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned. The clinical testing focused on the statistical equivalence of the device's aggregation method compared to the predicate's aggregation method for heart sound measurements, not on human reader improvement with or without AI assistance.

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

Yes, the clinical testing described is primarily a standalone (algorithm only) performance study. It evaluated the device's "new capability of aggregating periodically sampled heart sound measurements" by comparing its statistical output to that of the predicate device. This assessment does not appear to involve human readers interpreting the output in a loop, but rather directly comparing the analytical results of the algorithms.

7. Type of Ground Truth Used

The ground truth for the clinical study was based on clinical diagnosis (subjects "clinically diagnosed with heart failure" and "determined to be negative for heart failure"). This is a form of patient outcome/diagnosis data.

8. Sample Size for the Training Set

The document does not mention a separate "training set" or its sample size. The clinical study described refers to a "total study population of 252 subjects" used for retrospective analysis, which appears to be the evaluation (test) set for the clinical performance claim. It is possible that the algorithm was trained on other data not described in this summary or that it was an update to an existing algorithm.

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

Since a training set is not explicitly mentioned or described, the method for establishing its ground truth is also not provided in this document.

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