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The OBSERVER Central Station with ST-segment measurement is a prescription device intended for use only by health care professionals. The device is used for the remote monitoring of physiological parameters, including non-invasive and invasive blood pressure; invasive hemodynamic and intracranial pressures; oxygen saturation via pulse oximetry; temperature; ECG ; and pulse/heart rate of adult, pediatric and neonatal patients. The device is located at a distance from the patient but within the same facility, including settings such as hospital and outpatient services, including general medical/surgical, critical care, intermediate/step-down care, emergency room, radiology, labor and delivery, operating and recovery room, cardiac catheterization lab, endoscopy and same-day surgery.

Arrhythmia detection and ST-segment measurement are optional ECG features limited to the adult population. ST-segment measurement is contraindicated in paced patients. The ST-segment feature of the OBSERVER Central Station provides for the measurement of the ST-segment level and slope of the ECG waveform, alerting the clinician to ST-segment changes. The significance of ST-segment changes must be determined by a clinician. The device is not designed, sold or intended for use except as indicated.

The OBSERVER Central Station with ST-segment measurement is an optional feature of the OBSERVER Central Station with arrhythmia analysis. This feature allows for the measurement of the ST-segment level and slope and the issuance of alarms for ST elevations and depressions. The clinician may adjust certain waveform points and alarm priority and limits or rely on default settings for each patient to be analyzed.

The OBSERVER Central Station (K933404) is a PC-based monitoring system designed to provide remote surveillance with alarms, trending and retrieval of wave-form and numeric physiological data for up to 8 patients who are monitored via various DINAMAP* Physiological Monitors or other appropriate bedside/patient monitors.

The OBSERVER Central Station displays, records and stores physiological data including ECG, non-invasive and invasive blood pressure, heart rate, temperature and pulse oximetry. The system is designed to be used with a hardwire interface using RS 232; wireless connectivity using 900 MHz spread spectrum or fixed frequency; or VHF (174-216 MHz, TV channels 7 through 13), including patient-worn telemetry. Monitors that may be networked with the OBSERVER Central Station for ECG include members of the Johnson & Johnson Medical Inc. DINAMAP* family of monitors, such as the DINAMAP MPS* Select* Monitor (K955113) and the DINAMAP* PLUS Monitor (K943709 and K912188), and patient-worn ECG VHF telemetry (VitalCom, Inc. K942147). The OBSERVER Central Station uses a Pentium PC with an SVGA, touch or non-touch, color monitor. Recordings can be made on either the built-in two-channel thermal recorder or with an optional HP LaserJet* Printer. Also optional is full disclosure (history) of all waveforms.

The OBSERVER* Central Station with ST-segment measurement is a continuous monitoring device. The device was found to be substantially equivalent to the currently marketed OBSERVER Central Station with arrhythmia analysis (K933404) and the ST-segment measurement feature of the VitalCom, Inc. VCOM Central Monitor (K942147).

1. Acceptance Criteria and Reported Device Performance:

The document does not explicitly state numerical acceptance criteria for each performance metric. It mentions that the software was "tested against" databases to "measure" the algorithm's performance. The conclusion states that the modified device is "safe, effective and substantially equivalent" to predicate devices.

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

• Sample Size: Not explicitly stated, as the document refers to "AHA and MIT databases" and the "European ST-T database." These are established public databases containing numerous ECG recordings.
• Data Provenance: The databases used are:
  • AHA (American Heart Association) database
  • MIT (Massachusetts Institute of Technology) database
  • European ST-T database
    These are generally retrospective, publicly available datasets for ECG algorithm testing, often compiled from various clinical sources. The specific country of origin for each sample within these databases is not detailed in this summary, but they are recognized international benchmarks.

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

The document does not specify the number of experts or their qualifications for establishing the ground truth within the AHA, MIT, or European ST-T databases. These databases are typically curated with expert-validated annotations, but the details of that validation process are external to this 510(k) summary.

4. Adjudication Method for the Test Set:

The document does not describe an adjudication method for the test set as part of this submission. The ground truth for the databases is assumed to be established by the curators of those databases.

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

No MRMC comparative effectiveness study is mentioned for this device. The regulatory submission focuses on the algorithm's performance against standard databases and its substantial equivalence to predicate devices, not on human-in-the-loop performance improvement.

6. Standalone (Algorithm Only) Performance:

Yes, a standalone performance evaluation was done. The "Performance" section explicitly states that "The ST-enabled arrhythmia analysis software was tested against the AHA and MIT databases" and "The algorithm was also tested against the European ST-T database." This indicates an algorithm-only performance evaluation.

7. Type of Ground Truth Used:

The ground truth used is implied to be expert-annotated ECG waveforms from established public databases (AHA, MIT, European ST-T). These databases typically provide reference annotations for QRS complexes, arrhythmias, and ST-segment changes, which are considered the ground truth for evaluating such algorithms.

8. Sample Size for the Training Set:

The document does not specify the sample size for the training set. It focuses on the validation of the algorithm against known test databases.

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

The document does not describe how the ground truth for any training set was established. Given that the software was developed by VitalCom, Inc. (who also developed the ST-segment software for a predicate device), it's likely they used proprietary or established datasets for training, with ground truth established through expert review, but this is not detailed in the 510(k) summary.

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The VentNet system consists of a PC based Central Monitoring Station and either a hardwire or wireless communication means allowing the remote monitoring of up to 24 continuous mechanical ventilators. VentNet further has a means of communication via paging system for the remote notification of alarms or changes in ventilator status. The VentNet automatically records ventifator setting changes and alarm events with patient physiological data from the monitored ventilators. The user may then review this information in a ventilator flowsheet format or print it as pre-formatted reports.

VentNet's intended use is to supplement the operation of dispersed or remotely located mechanical ventilators. VentNet allows the remote monitoring of multiple ventilators from a central station. VentNet displays ventilator settings, ventilator alarm status and physiological patient information as communicated from the monitored mechanical ventilator. VentNet also includes an optional feature which causes automatic notification, via paging system to defined users of certain ventilator alarms. VentNet is not intended to replace on-hand competent medical staff in monitoring for, or responding to ventilator alarms but is intended to support that staff by notifying other respiratory care staff or ventilator specialists in the event of certain alarm conditions.

VentNet's secondary intended use is the automation of some of the record keeping and reporting functions performed during mechanical ventilation.

The VentNet system consists of a PC based Central Monitoring Station and either a hardwire or wireless communication means allowing the remote monitoring of up to 24 continuous mechanical ventilators. VentNet further has a means of communication via paging system for the remote notification of alarms or changes in ventilator status. The VentNet automatically records ventifator setting changes and alarm events with patient physiological data from the monitored ventilators. The user may then review this information in a ventilator flowsheet format or print it as pre-formatted reports.

The provided document is a 510(k) Premarket Notification summary for the VentNet Central Monitoring Station. It focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a dedicated study.

Therefore, the requested information regarding acceptance criteria, reported device performance, sample sizes, data provenance, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for a clinical study is not available within this document. The document primarily describes the device's technical specifications and compares them to predicate devices to establish substantial equivalence based on non-clinical performance data.

Here's an analysis of the information that is available, based on the prompt's request:

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

The document does not explicitly present a "table of acceptance criteria and reported device performance" in the way a clinical study would for an AI/medical device. Instead, it lists "Product and Technical Specifications" and "Device Claims" which implicitly serve as performance goals, and then leverages a comparison matrix to predicate devices to argue equivalence. No quantitative "reported device performance" against these specifications from a formal study is detailed.

However, we can infer some "acceptance criteria" from the "Device Claims" and "Product and Technical Specifications" sections. The "reported device performance" is then implicitly demonstrated by stating these specifications and implying they are met, as part of the overall argument for substantial equivalence via non-clinical testing.

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: Not applicable. The document describes "non-clinical performance data review" based on testing for EMI, software verification/validation, environmental testing, and stress testing. This implies technical testing, not a study with a patient "test set."
• Data Provenance: Not applicable for a clinical test set. The data provenance mentioned is related to engineering and software testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable. There is no mention of a test set with an associated ground truth established by experts. The device's function is data presentation and alarm relay, not diagnostic interpretation.

4. Adjudication method for the test set:

• Not applicable. No clinical 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:

• No. This is not an AI diagnostic device. It's a central monitoring station for ventilators. No MRMC study was conducted or mentioned.

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

• The document implies standalone system performance was evaluated through "software verification and validation of both the system software performance as well as the operating system software performance, environmental testing and stress testing both at the integration level and the system level." However, this refers to the system's technical functionality, not a standalone diagnostic algorithm's performance. The device is explicitly designed to support human staff, not replace them.

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

• Not applicable. The performance data reviewed involved validation of technical specifications and software functionality, not clinical diagnostic accuracy against a ground truth.

8. The sample size for the training set:

• Not applicable. This device is not an AI/machine learning device that would require a "training set" for model development.

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

• Not applicable. As above, no training set is relevant for this type of device.

Study Proving Acceptance Criteria:

The document states: "The determination of substantial equivalence was based on an assessment of nonclinical performance data. The data includes testing for EMI compatibility and susceptability, software verification and validation of both the system software performance as well as the operating system software performance, environmental testing and stress testing both at the integration level and the system level. The conclusion drawn from a review of the data indicates that the VentNet is substantially equivalent to the predicate devices."

This statement indicates that the "study" proving the device meets its (implicitly stated) performance criteria and is "substantially equivalent" involved:

• EMI Compatibility and Susceptibility Testing: To ensure the device operates correctly in its intended electromagnetic environment without interference and is not unduly affected by external electromagnetic sources.
• Software Verification and Validation: To confirm that the software performs as designed and meets all specified technical and functional requirements. This would involve unit testing, integration testing, system testing, and potentially user acceptance testing.
• Environmental Testing: To ensure the device can withstand specified operating and storage conditions (temperature, humidity, etc.).
• Stress Testing: To evaluate the system's robustness and stability under extreme or heavy load conditions.
• Integration and System Level Testing: To confirm that all components work together correctly as a complete system.

This approach demonstrates meeting technical specifications and equivalency to predicate devices, rather than a clinical performance study with patient data and a diagnostic ground truth.

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