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510(k) Data Aggregation
(42 days)
The Nuvon Vitals Charting System is an accessory to the Nuvon VEGA System (K103125) and is intended to display patient information and surveillance of monitored patients at the point of care location and at a remote supplementary care location through wide area networking technology. The Nuvon Vitals Charting System is only intended to display physiologic and other patient information and intended for use by clinicians as a diagnostic aid, and not as a replacement for direct viewing of any of the monitored devices from which it obtains its data. The Nuvon Vitals Charting System is not intended for monitoring purposes, nor is it intended to control any of the biomedical devices and information systems with which it interconnects.
The Nuvon Vitals Charting System is a software only system that permits the display of data from biomedical, patient care devices, and ancillary hospital systems (e.g.: laboratory and hospital admission, discharge and transfer systems). The system can be used to review and validate the data for transfer to existing hospital information technology and electronic medical record systems. Additionally, the system can be used for patient surveillance to evaluate trends in patient data.
The Nuvon Vitals Charting System is a software-only system designed to display data from various biomedical, patient care devices, and hospital information systems. It's intended for use by clinicians as a diagnostic aid for patient information display and surveillance, but not as a replacement for direct viewing of monitored devices or for direct patient monitoring.
Here's an analysis of the acceptance criteria and the study proving the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Criteria | Reported Device Performance |
|---|---|---|
| Functional Performance | Unit Testing: Functions verified for valid operation per requirements and design. | "Results of verification and validation activities have shown that the Nuvon Vitals Charting System displays biomedical device data communicated from the source devices through the system in a manner consistent with the expected performance." |
| Integration and System Testing: Functions operate within the scope of the larger VEGA System. | "Results of verification and validation activities have shown that the Nuvon Vitals Charting System displays biomedical device data communicated from the source devices through the system in a manner consistent with the expected performance." | |
| Non-Functional Performance | Performance/Non-functional testing: Support for multiple simultaneous users and demonstration of key functional performance over time to illustrate scalability without appreciable degradation. | "Results of verification and validation activities have shown that the Nuvon Vitals Charting System displays biomedical device data communicated from the source devices through the system in a manner consistent with the expected performance." |
| Overall Equivalence | Substantial Equivalence to predicate devices (VISICU ARGUS, K012171 and Airstrip Remote Patient Monitoring Viewing System, K121871) in intended uses, indications, technological characteristics, and principles of operation. Minor technological differences raise no new issues of safety or effectiveness. | "The Nuvon Vitals Charting System has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate devices. The minor technological differences between the Nuvon Vitals Charting System and its predicate devices raise no new issues of safety or effectiveness. Performance data demonstrate that the Nuvon Vitals Charting System meets its specifications and intended use, and thus is substantially equivalent performance to the VISICU ARGUS System and the Airstrip Patient Monitoring System." |
2. Sample size used for the test set and the data provenance
The provided text does not specify a numerical sample size for any test sets used.
The data provenance (e.g., country of origin, retrospective or prospective) is not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not mention the use of experts or a ground truth established by experts for the test set. The validation seems to rely on the system's ability to accurately display data consistent with expected performance and its functional requirements.
4. Adjudication method for the test set
The document does not describe any adjudication method like 2+1, 3+1 for establishing ground truth, as ground truth is not explicitly mentioned in the context of expert review.
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
A multi-reader multi-case (MRMC) comparative effectiveness study was not performed or reported. This device is described as a "display system" and "diagnostic aid," not an AI algorithm intended to assist human readers in interpretation or diagnosis in the way an imaging AI might. There's no mention of AI assistance for "human readers" or an "effect size" of such assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is a standalone software system (algorithm only in a sense that it's a software displaying data), but the "standalone performance" referred to in AI/ML contexts (where an algorithm makes a diagnostic decision without human input) is not applicable here. The system's function is to display data, and its performance centers on accurate data transfer and display, not on making independent diagnostic decisions. The stated intended use is as a "diagnostic aid," with clinicians using it, not as a replacement for direct viewing.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The term "ground truth" in the strict sense of a reference standard established by experts or confirmed by pathology/outcomes data is not explicitly used or described in the context of device performance validation. The validation focused on whether the system "displays biomedical device data communicated from the source devices through the system in a manner consistent with the expected performance" and "meets its specifications and intended use." This implies that the "truth" for this system is the accurate representation of the data generated by the source biomedical devices, validated against the expected output based on functional requirements and system integration.
8. The sample size for the training set
The document does not mention a training set or any machine learning/AI model training. This device is described as a charting and display system, not a system that uses machine learning in a way that requires a distinct training and test set in the typical AI/ML validation paradigm.
9. How the ground truth for the training set was established
As no training set or machine learning components are mentioned, the concept of establishing ground truth for a training set is not applicable to this submission.
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(85 days)
The Vector Event Grid Architecture System is intended for use in data collection from bedside and point of care biomedical devices and clinical information management systems either directly or through networks with independent bedside devices. The Vector Event Grid Architecture System is not intended for monitoring purposes, nor is it intended to control any of the biomedical devices and information systems with which it interconnects.
The VEGA System permits the transfer of data from biomedical and patient care devices to existing hospital information technology and electronic medical record systems. The VEGA System connects directly to biomedical devices and aggregates the data from multiple biomedical devices for transmission to electronic medical record systems. The VEGA System may also translate native biomedical device data into the HL7 standard as necessary.
The provided text is a 510(k) summary for the Nuvon, Inc. Vector Event Grid Architecture (VEGA) System, a device for collecting data from biomedical devices and clinical information management systems. It is not a detailed study report with specific acceptance criteria and performance metrics for a diagnostic or AI-driven device in the typical sense.
Therefore, much of the requested information cannot be extracted directly from this document. The document describes a data retrieval system rather than a device with diagnostic or analytical performance claims that would typically involve sensitivity, specificity, or other statistical measures.
However, I can extract the following information:
1. A table of acceptance criteria and the reported device performance:
The document does not provide a table of quantitative acceptance criteria or statistical performance metrics (e.g., sensitivity, specificity, AUC) because it's a data collection and transmission system, not a diagnostic one. Instead, it states qualitative performance outcomes.
| Acceptance Criterion (Implicit) | Reported Device Performance |
|---|---|
| Communication of biomedical device data from source devices | "Results of verification and validation activities have shown that the VEGA System biomedical device data are communicated from the source devices through the system in a manner consistent with the expected performance." |
| Functionality as intended | "In all instances the VEGA System functioned as intended..." |
| Fidelity of results | "...and the fidelity of the results observed was as expected." |
| Equivalence to predicate device for safety and effectiveness | "The minor technological differences between the VEGA System and its predicate devices raise no new issues of safety or effectiveness." |
| Substantially equivalent performance to predicate device | "Performance data demonstrate that the VEGA System has substantially equivalent performance to the Data Captor System." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
This information is not provided in the document. The document refers to "verification and validation activities" but does not specify the sample size, type of data used (e.g., specific biomedical device models, patient data), or its provenance.
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):
This information is not applicable/not provided. The device is a data retrieval system, not one that makes clinical diagnoses requiring expert ground truth for its performance evaluation in the traditional sense. Its evaluation would focus on data integrity, transmission accuracy, and interoperability.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
This information is not applicable/not provided. Adjudication methods are typically used for establishing ground truth in diagnostic studies, which is not the primary purpose of this device's performance evaluation as described.
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:
This information is not applicable/not provided. The VEGA System is a data retrieval and transmission system, not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance would not be relevant to its function.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The document describes the VEGA System as functioning independently to collect and transmit data. The performance section implies a standalone evaluation of the system's ability to communicate data accurately from source devices. However, the term "standalone" in the context of an "algorithm" is more typically associated with AI-driven diagnostic tools. Here, the device's function as a data intermediary is evaluated.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
The concept of "ground truth" in the diagnostic sense (e.g., pathology, expert consensus) is not applicable to this device. For this type of system, the "ground truth" would likely be the actual data generated by the biomedical devices, and the performance would be validated by comparing the transmitted data to the source data for accuracy, completeness, and fidelity. The document states "the fidelity of the results observed was as expected," implying such a comparison.
8. The sample size for the training set:
This information is not applicable/not provided. The VEGA system is described as a data retrieval architecture, not a machine learning or AI algorithm that would typically require a "training set" in the context of supervised learning.
9. How the ground truth for the training set was established:
This information is not applicable/not provided for the same reasons as point 8.
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