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510(k) Data Aggregation
(269 days)
VitalRhythm is a cloud-based software application for continuous and automatic analysis of cardiac arrhythmias. VitalRhythm is compatible with the "Vista Solution" platform, which includes the VitalPatch biosensor and VistaCenter web application. VitalRhythm is intended to be used for outpatient cardiac telemetry and patient monitoring in non-critical healthcare settings for non-urgent clinical decision-making. VitalRhythm provides analysis of cardiac arrhythmias using ECG data and RR-interval from the VitalPatch in patients who are 18 years of age or older. Results of the VitalRhythm are displayed within the VistaCenter web application to be reviewed and confirmed by qualified healthcare professionals and/or cardiac technicians. VitalRhythm is not intended for use in life-supporting or sustaining systems or for critical care monitoring. The arrhythmia analysis results are not intended to be the sole means of diagnosis and are offered on an advisory basis only, in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.
VitalRhythm is a cloud-based, arrhythmia detection software application that is compatible and intended to be used with the VitalConnect "Vista Solution" platform. The Vista Solution Platform consists of the VitalPatch biosensor, a phone (VistaPhone) or tablet (VistaTablet) relay device preloaded with the VistaPoint software application, VC Cloud and the cloud-based VistaCenter user interface.
VitalRhythm is intended to be used for outpatient cardiac telemetry and patient monitoring in non-critical healthcare settings for non-urgent clinical decision-making.
VitalRhythm analyzes ECG data and RR-interval from the VitalPatch biosensor for reporting of cardiac arrhythmias to be reviewed and adjudicated by qualified healthcare professionals and/or cardiac technicians.
The cloud-based VitalRhythm software application supports the analysis of ECG data and RR-interval using a proprietary algorithm developed using deep learning techniques. The application works in the following way:
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VitalRhythm accepts ECG and RR-interval data transmitted from the VitalPatch via a secure, cloud-based API (Application Programming Interface).
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ECG and RR-interval data are analyzed by VitalRhythm using a proprietary algorithm, which detects the following cardiac rhythms:
- Atrial fibrillation/atrial flutter
- AV Block (2nd degree, Type I and II)
- Pause
- Paroxysmal supraventricular tachycardia (PSVT)
- Ventricular tachycardia/run
- Sinus bradycardia
- Sinus tachycardia
- Normal sinus rhythm
- Others (inconclusive)
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For use with Mobile Cardiac Telemetry (MCT), i.e., outpatient cardiac telemetry: any of the above listed arrhythmias that are detected by the software algorithm are displayed in VistaCenter to be reviewed and analyzed by a qualified cardiac technician in the 24/7 attended Cardiac Monitoring Center, prior to transmitting a notifiable event consistent with the prescribed notification criteria to the prescribing physician during the monitoring period. An event report is generated by VistaCenter as a result of the analysis.
For use with patient monitoring in non-critical healthcare settings: any of the above listed arrhythmias that are detected by the software algorithm are displayed and notified in VistaCenter, in accordance with the notification criteria, during the monitoring period to be reviewed by the prescribing healthcare professional for non-urgent clinical decision-making.
The features, operating procedures, and mitigations in place for the compatible devices ensure continuous data collection and transmission to support the VitalRhythm application for the intended use. Further information is provided in the VitalRhythm Instructions for Use document.
Here's a detailed breakdown of the VitalRhythm device's acceptance criteria and the study that proves it meets those criteria, based on the provided FDA 510(k) clearance letter:
Acceptance Criteria and Device Performance
| Rhythm Type | Acceptance Criteria (Sensitivity, Specificity, PPV, NPV, Accuracy) | Reported Device Performance |
|---|---|---|
| Atrial fibrillation/flutter | ≥ 95% | Sensitivity: 99.9%, Specificity: 99.9%, PPV: 99.8%, NPV: 99.9%, Accuracy: 99.9% |
| AV block (2nd degree, Type I and II) | ≥ 95% | Sensitivity: 98.7%, Specificity: 100.0%, PPV: 99.9%, NPV: 99.9%, Accuracy: 99.9% |
| Paroxysmal supraventricular tachycardia | ≥ 95% | Sensitivity: 98.6%, Specificity: 99.9%, PPV: 99.4%, NPV: 99.9%, Accuracy: 99.9% |
| Ventricular tachycardia/run | ≥ 95% | Sensitivity: 99.3%, Specificity: 99.9%, PPV: 99.4%, NPV: 99.9%, Accuracy: 99.9% |
| Pause | ≥ 95% | Sensitivity: 99.7%, Specificity: 100.0%, PPV: 99.9%, NPV: 100.0%, Accuracy: 100.0% |
| Others (inconclusive) | ≥ 95% | Sensitivity: 98.9%, Specificity: 99.9%, PPV: 99.2%, NPV: 99.9%, Accuracy: 99.9% |
| Normal sinus rhythm | ≥ 90% | Sensitivity: 98.9%, Specificity: 99.1%, PPV: 99.1%, NPV: 98.9%, Accuracy: 99.0% |
| Sinus bradycardia | ≥ 90% | Sensitivity: 97.0%, Specificity: 99.8%, PPV: 98.9%, NPV: 99.6%, Accuracy: 99.5% |
| Sinus tachycardia | ≥ 90% | Sensitivity: 99.4%, Specificity: 99.5%, PPV: 97.7%, NPV: 99.8%, Accuracy: 99.5% |
| Sinus (overall category) | No explicit numeric criteria listed but implies acceptable performance based on individual sinus rhythms. | Sensitivity: 99.8%, Specificity: 99.9%, PPV: 99.8%, NPV: 99.9%, Accuracy: 99.8% |
Study Details
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Sample Size Used for the Test Set and Data Provenance:
- Patient count: 3,309 patients (18 years of age or older).
- Dataset count: 7,553 datasets.
- Annotated arrhythmia episodes: 22,034.
- Data Provenance: Retrospective, de-identified ECG and RR-interval data obtained from patients prescribed the VitalPatch biosensor across 7 clinical sites in the United States (US).
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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 or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish the ground truth for the test set. However, it indicates that the results are "to be reviewed and confirmed by qualified healthcare professionals and/or cardiac technicians" in the context of device usage and implies that annotation for ground truth would follow a similar expert-driven process. -
Adjudication Method for the Test Set:
The document does not explicitly state the adjudication method (e.g., 2+1, 3+1, none) used for establishing the ground truth of the test set. It only states that the generated "event report is generated by VistaCenter as a result of the analysis" and is "to be reviewed and analyzed by a qualified cardiac technician in the 24/7 attended Cardiac Monitoring Center, prior to transmitting a notifiable event consistent with the prescribed notification criteria to the prescribing physician during the monitoring period." This describes post-processing of algorithm results by human readers, not the method for establishing the ground truth used for algorithm validation. -
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it provide an effect size of how much human readers improve with AI vs without AI assistance. The study described focuses on the standalone performance of the algorithm. -
Standalone Performance (Algorithm Only Without Human-in-the-Loop Performance):
Yes, a standalone performance study was conducted. The performance metrics (Sensitivity, Specificity, PPV, NPV, Accuracy) presented in the table are explicitly for the VitalRhythm algorithm "when assessed using the independent test database," indicating standalone algorithm performance against a pre-established ground truth. -
Type of Ground Truth Used:
The ground truth was established through annotated arrhythmia episodes. While the specific process is not detailed, it implies expert review and labeling of ECG and RR-interval data to define the 'true' presence or absence of arrhythmias. The "results are displayed within the VistaCenter web application to be reviewed and confirmed by qualified healthcare professionals and/or cardiac technicians," suggesting human consensus or expert interpretation forms the basis of the ground truth. -
Sample Size for the Training Set:
- Patient count: 23,587 patients.
- Dataset count: 81,391 datasets.
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How the Ground Truth for the Training Set Was Established:
The document states the training database was from 354 US clinical sites, but it does not explicitly detail how the ground truth for the training set was established. It implies a process of data collection from clinical sites and subsequent processing for training the deep learning algorithm.
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