(90 days)
This device is capable of connecting to one or more bedside monitors via a network. The device allows the user to monitor the patients connected to these monitors at a central location. The monitoring ability of the device is determined by the bedside monitors. In addition, this device can provide interpretive diagnostic statements and reports when connected to a bedside monitor with ECG monitoring capability.
This device is intended for use with adults and pediatrics in an environment where patient care is provided by Healthcare Professionals, i.e. Physicians, Nurses, and Technicians, who will determine when use of the device is indicated, based upon their professional assessment of the patient's medical condition.
The Siemens MultiView (SC3000) WorkStation™ enhanced with Diagnostic Statements (Rest ECG) is a modified version of the MultiView (SC3000) WorkStation granted clearance under 510(k) # K955059. This enhancement enables the MultiView WorkStation to interpret diagnostic statements (Rest ECG) and reports of multi-lead ST deviations.
The Siemens MultiView WorkStation™ Enhanced with Diagnostic Statements (Rest ECG) is a modified version of the MultiView (SC3000) WorkStation, which was previously cleared under 510(k) # K955059. This enhancement allows the MultiView WorkStation to interpret diagnostic statements (Rest ECG) and reports of multi-lead ST deviations. The device collects preprocessed ECG data from SC9000/SC9015 bedside monitors, analyzes it, and produces reports and potential patient diagnoses for physician review.
Here's an analysis of the acceptance criteria and the study that proves the device meets them:
1. A table of acceptance criteria and the reported device performance
The provided document does not explicitly state specific quantifiable acceptance criteria for the diagnostic statements and reports. Instead, it relies on demonstrating equivalence to a predicate device and testing against a standard clinical database as per AAMI recommendations.
| Acceptance Criterion (Implicit) | Reported Device Performance |
|---|---|
| Equivalence to Predicate Device: The device should perform comparably to the Siemens MEGACART™ (K915225) in terms of ECG processing, ST segment analysis, interpretation, and reporting for resting ECGs. This includes analyzing data and providing output with interpretation. | The device is a modified version of a previously cleared device (K955059) and is enhanced to interpret diagnostic statements (Rest ECG) and reports of multi-lead ST deviations. The table of similarities and differences highlights that the new device shares the same intended use (analyzing data and providing output with interpretation for resting ECGs), intended population, intended environment, ST analysis capabilities (up to 12 ST complexes, performed on all available leads at 500 s/s), ECG processing algorithm (Megacart Algorithm), number of leads (up to 12), and reporting features (12 leads ST measurements, interpretation, proposed diagnosis, resting ECG, annotations) as the predicate device. The primary difference noted is that ST segment data is processed in the bedside monitor, not the MVWS itself, indicating a system integration rather than a fundamental change in ST analysis methodology. |
| Performance Qualified by Testing vs. Standard Clinical Database: The device's performance for diagnostic statements and reports (Rest ECG) should be qualified by testing against a standard clinical database. | "Performance was qualified by testing versus a standard clinical database per AAMI recommendations." |
2. Sample size used for the test set and the data provenance
The document states, "Performance was qualified by testing versus a standard clinical database per AAMI recommendations." However, it does not provide specific details regarding the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature of the data).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not provide information on the number of experts used or their qualifications for establishing ground truth for the clinical database.
4. Adjudication method for the test set
The document does not describe any adjudication method (e.g., 2+1, 3+1, none) used for the test set.
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
The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study. The focus is on demonstrating the device's ability to provide interpretive diagnostic statements and reports, and its equivalence to a predicate device, rather than on quantifying human reader improvement with AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The entire premise of the device – "The device is suitable for use in resting ECGs and is capable of analyzing the data and providing output with interpretation" and "produce reports and possible patient diagnosis for review by the physician" – indicates that the algorithm does perform in a standalone capacity by generating interpretive diagnostic statements and reports before physician review. The qualification "Performance was qualified by testing versus a standard clinical database per AAMI recommendations" would inherently relate to the standalone performance of the algorithm in interpreting the ECG data.
7. The type of ground truth used
The ground truth for the performance qualification was established through a "standard clinical database per AAMI recommendations." While the exact nature of this ground truth (e.g., expert consensus, pathology, outcomes data) is not explicitly detailed, "standard clinical database" suggests a collection of cases with established diagnoses or interpretations, likely based on expert consensus or established clinical practice/guidelines that the AAMI standard would dictate.
8. The sample size for the training set
The document does not provide information on the sample size used for the training set. It primarily discusses performance qualification rather than the development or training of the underlying ECG interpretation algorithm. Given the K980623 filing in 1998, and the use of the "Megacart Algorithm" which is also present in the 1991 predicate device (K915225), it's highly probable that the core algorithm was developed and trained much earlier.
9. How the ground truth for the training set was established
The document does not provide information on how the ground truth for the training set was established. As mentioned, the core "Megacart Algorithm" predates this submission, so details regarding its original training and ground truth establishment would not be expected in this 510(k) summary.
§ 870.1025 Arrhythmia detector and alarm (including ST-segment measurement and alarm).
(a)
Identification. The arrhythmia detector and alarm device monitors an electrocardiogram and is designed to produce a visible or audible signal or alarm when atrial or ventricular arrhythmia, such as premature contraction or ventricular fibrillation, occurs.(b)
Classification. Class II (special controls). The guidance document entitled “Class II Special Controls Guidance Document: Arrhythmia Detector and Alarm” will serve as the special control. See § 870.1 for the availability of this guidance document.