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The T-Wave Alternans (TWA) Algorithm Option is to be used in a hospital, doctor's office, or clinic environment by competent health care professionals for recording ST-T wave morphology fluctuations for patients who are undergoing Cardiovascular disease testing.

The T-Wave alternans analysis is intended to provide only the measurements of the fluctuations of the ST-T-waves. The T-Wave alternans measurements produced by the T-Wave Alternans analysis are intended to be used by qualified personnel in evaluating the patient in conjunction with the patients clinical history, symptoms, other diagnostic tests, as well as the professional's clinical judgment. No interpretation is generated.

T-Wave Alternans (TWA) Algorithm Option is a software algorithm that runs on GE Medical Systems Information Technologies' electrocardiographs.

The provided text describes the T-Wave Alternans (TWA) Algorithm Option, a software algorithm for electrocardiographs. However, the document (K023380) is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report with specific acceptance criteria and performance data.

Therefore, much of the requested information regarding acceptance criteria, specific study details, sample sizes, ground truth establishment, expert qualifications, adjudication methods, and MRMC effectiveness studies is not available within this document. The document primarily focuses on regulatory compliance and the intended use of the device.

Here's an attempt to answer the questions based on the available information, with clear indications of what is not provided:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample size for the test set: Not provided.
• Data provenance: Not provided. (The document mentions "Verification and Validation" but does not detail the specific datasets used for these activities.)

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)

• Number of experts: Not provided.
• Qualifications of experts: Not provided.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Adjudication method: Not provided.

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

• MRMC study done: Not provided. The document focuses on the algorithm's performance itself and its equivalency to a predicate device, not on its impact on human reader performance.
• Effect size of human reader improvement with AI: Not applicable, as an MRMC study is not mentioned.

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

• Standalone study done: The document implies standalone testing in that it describes the algorithm as a "software algorithm that runs on GE Medical Systems Information Technologies' electrocardiographs" and states "Verification and Validation" were performed. However, specific details of a formal standalone performance study with metrics are not explicitly provided. The comparison is often implicitly against the performance of the predicate device's existing algorithm.

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

• Type of ground truth: Not provided.

8. The sample size for the training set

• Sample size for the training set: Not provided. The document focuses on regulatory approval, not on the developmental aspects like training data for the algorithm.

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

• How ground truth for training set was established: Not provided.

Summary of available information:

The 510(k) summary (K023380) primarily indicates that the device underwent standard quality assurance measures, including:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Code inspections
• Verification and Validation

These measures were deemed sufficient to demonstrate that the T-Wave Alternans (TWA) Algorithm Option is "as safe, as effective, and performs as well as the predicate software option offered with device, CASE 8000 Exercise Testing System." The document does not disclose the detailed methodologies, datasets, or specific performance metrics from these verification and validation activities.

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The intended use of the SEER Light Compact Digital Holter Recorder is to acquire ambulatory 2 or 3 channels of ECG signal from the chest surface of pediatric or adult patients for no longer than 24 hours. The device stores this data along with patient demographic information to on board flash memory. It does not perform any analysis on the ECG data.

The SEER Light Compact Digital Holter Recorder is intended to be used under the direct supervision of a licensed healthcare practitioner, by trained operators in a hospital or medical professional's facility.

The SEER Light Compact Digital Holter Recorder is designed to acquire ambulatory 2 or 3 channels of ECG signal from the chest surface for no longer than 24 hours. The device stores the acquired ECG data in its on-board 32 megabytes of flash memory. Additionally, the SEER Light controller downloads patient demographic information into the SEER Light recorder and checks the signal quality of the ECG data at hookup time via isolated, infra-red communications. At the end of the recording the SEER Light controller is connected to the SEER Light recorder by cable and the stored ECG data is transferred to it and onto a standard compact flash memory card.

Here's an analysis of the provided text regarding the acceptance criteria and study for the SEER Light Compact Digital Holter Recorder:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly define specific numerical acceptance criteria for performance metrics. Instead, it states that the device "complies with the voluntary standards as detailed in Section 9 of this submission" (Section 9 is not provided here) and that the "results of these measurements demonstrated that the SEER Light Compact Digital Holter Recorder is as safe, as effective, and performs as well as the predicate device."

Therefore, the acceptance criteria are implicitly tied to meeting the performance of the predicate device (K001317 Aria Digital Holter Recorder®) and relevant voluntary standards. Specific quantitative performance data from comparative testing are not detailed in this summary.

Important Note: Without access to "Section 9 of this submission" and the specific test results comparing the SEER Light to the predicate device, it's impossible to provide granular numerical acceptance criteria or performance metrics specific to ECG signal quality, data storage integrity, or accuracy that would typically be expected for such a device. This summary focuses on demonstrating equivalence rather than establishing new performance benchmarks.

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

The provided text does not specify the sample size used for any test set or provide details on data provenance (e.g., country of origin, retrospective/prospective). It only broadly mentions "software and hardware testing," "safety testing," and "environmental testing" as part of the quality assurance measures.

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

The provided text does not mention the use of experts or the establishment of ground truth for any test set in the context of clinical performance or diagnostic accuracy, as the device states it "does not perform any analysis on the ECG data." Its function is purely for acquisition and storage.

4. Adjudication Method

Given that no experts or clinical performance evaluations involving diagnostic interpretation are mentioned, there is no adjudication method described in the provided document.

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

No MRMC comparative effectiveness study was done or is mentioned. The device, by its stated intended use, does not perform analysis on ECG data, so a study evaluating human readers' improvement with or without AI assistance would not be applicable.

6. Standalone Performance Study

The provided text does not describe a standalone (algorithm only without human-in-the-loop performance) study in the context often associated with diagnostic AI algorithms. The device itself is a standalone recorder, but its "performance" is based on its ability to acquire and store ECG signals reliably, not on its analytical capabilities. The testing mentioned (software, hardware, safety, environmental, final validation) would fall under performance testing, but not in the context of an "algorithm only" diagnostic performance study.

7. Type of Ground Truth Used

The concept of "ground truth" as typically used for diagnostic algorithms (e.g., pathology, outcomes data, expert consensus) does not apply to this device's stated function. The device acquires ECG signals; it does not interpret them. Therefore, its "ground truth" would relate to the accuracy of the recorded signal itself (e.g., comparison to a reference ECG machine for signal fidelity, absence of artifact, proper data storage). However, the document does not elaborate on how this type of ground truth was established.

8. Sample Size for the Training Set

The provided text does not mention a training set sample size. This device is a hardware recorder, not an AI/machine learning model that typically requires a training set.

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

As this is a hardware device for ECG data acquisition and not an AI/machine learning model, the concept of a "training set" and establishing "ground truth for a training set" as typically understood in AI/ML development is not applicable. The device's "performance" is validated through engineering and functional testing against specifications and standards, not through training on data with established ground truth for diagnostic purposes.

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AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components is intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in its proper use. AccuSketch is intended to provide and document an objective quantification of coronary artery stenosis and measurement and quantification of left ventricular function. Also provided is the ability to digitize and store video images and the ability to interactively annotate and report current and post procedural patient cardiac status.

The AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components is a PC based software system comprised of 4 individual programs used to view, capture/print, analyze and annotate images from cardiac catheterization procedures. AccuSketch is offered as a complete turn-key system or can be ported into other GE cardiac image devices for image analysis. The AccuSketch is a Personal Computer (PC) based software system designed to be permanently installed in a hospital in or near the cardiac catheterization laboratory. AccuSketch is comprised of four individual programs responsible for a specific function. Their purpose is to view, capture/print, analyze and annotate images from cardiac catheterization procedures. The CardioTree is an editable coronary tree tool used to electronically annotate and document the anatomy of the patient's vessels.

The provided text describes a 510(k) submission for the "AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components." This submission demonstrates substantial equivalence to predicate devices rather than proving specific performance against acceptance criteria in a standalone study. Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes, expert involvement, and ground truth establishment from a dedicated performance study is not explicitly available within this document.

However, I can extract information related to the device description, intended use, and the general approach to demonstrating effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance:

As this is a 510(k) submission focused on substantial equivalence, explicit "acceptance criteria" with numerical targets and reported performance values from a dedicated performance study are not detailed in the provided text. The document states that the device "employs the same functional scientific technology as its predicate devices" and "is as safe, as effective, and performs as well as the predicate devices," implying a comparison to the established performance of those predicates rather than a new set of independent criteria.

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

Not explicitly mentioned. The document focuses on demonstrating equivalence to predicate devices and describes internal testing phases (unit, integration, final acceptance, performance, safety, environmental testing) but does not provide details on specific clinical test sets, their sizes, or data provenance (e.g., country of origin, retrospective/prospective).

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

Not explicitly mentioned. Given the nature of a 510(k) addressing substantial equivalence, a formal ground truth establishment by external experts for a test set is not detailed. The device is intended to "aid the Cardiologist or trained technician," suggesting clinical professionals are the intended users who would interpret outputs.

4. Adjudication Method for the Test Set:

Not explicitly mentioned.

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

Not explicitly mentioned. The provided text does not describe an MRMC study or any quantitative effect size of human readers improving with AI vs. without AI assistance.

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

Not explicitly mentioned. The document refers to "requirements reviews," "design reviews," and various forms of testing (unit, integration, final acceptance, performance, safety, environmental), which are internal development and quality assurance measures. These are not typically standalone clinical performance studies. The device's stated intended use is to "aid the Cardiologist or trained technician," suggesting a human-in-the-loop design.

7. Type of Ground Truth Used:

Not explicitly mentioned for a formal performance study. The device's function involves "objective quantification of a patient's Left Ventricular function" and "objective quantification of coronary artery stenosis." For these types of measurements in the clinical context, the "ground truth" would typically be established by expert interpretation/consensus or potentially by comparison to other established quantitative methods. However, the document doesn't detail how this was specifically handled for a ground truth in a clinical study.

8. Sample Size for the Training Set:

Not applicable or not mentioned. The document describes a traditional software system for analysis rather than a machine learning/AI model that undergoes a "training" phase with a specific dataset. The "advanced analysis components" refer to software features, not a continuously learning algorithm.

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

Not applicable (as it's not described as an AI/ML training set).

Summary of available information from the document:

• Device: AccuSketch Cardiac Quantitative Analysis System w/ Advanced Analysis Components.
• Intended Use: Aid cardiologists or trained technicians in providing and documenting objective quantification of Left Ventricular function and coronary artery stenosis, digitize/store video images, and annotate/report cardiac status.
• Demonstration of Effectiveness: By demonstrating substantial equivalence to predicate devices (CardioTrace K912829; MUSE Cardiovascular Information System with Accusketch K992937). The device employs the same functional scientific technology and is claimed to be as safe, effective, and perform as well as the predicates.
• Quality Assurance Measures (Internal Testing): Risk Analysis, Requirements Reviews, Design Reviews, Unit-level testing (Module verification), Integration testing (System verification), Final acceptance testing (Validation), Performance testing, Safety testing, Environmental testing. These are internal development and verification processes, not a formal clinical performance study demonstrating acceptance criteria.

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Indicated for use in data collection and clinical information management through networks with independent bedside devices.

The Unity Network ID is not intended for monitoring purposes, nor is the Unity Network ID intended to control any of the clinical devices (independent bedside devices/ information systems) it is connected to.

The Unity Network ID system communicates patient data from sources other than GE Medical Systems Information Technologies equipment to a clinical information system, central station, and/or GE Medical Systems Information Technologies patient monitors.

The Unity Network ID acquires digital data from eight serial ports, converts the data to Unity Network protocols, and transmits the data over the monitoring network to a Unity Network device such as a patient monitor, clinical information system or central station.

The provided documentation does not contain information about acceptance criteria, device performance metrics, or a study that evaluates the device's diagnostic performance for medical insights in the way one would typically assess an AI/ML medical device.

The GE Medical Systems Information Technologies Unity Network ID (K021454) is a data communication and management system, not a diagnostic device that generates interpretations or analyses of patient data. Its purpose is to acquire digital data from various medical devices, convert it to a common protocol, and transmit it to other systems like patient monitors, clinical information systems, or central stations.

The "Test Summary" section describes quality assurance measures applied during development, such as risk analysis, requirements reviews, design reviews, and various levels of testing (unit, integration, acceptance, performance, safety, environmental). However, these are developmental tests to ensure the system functions as designed and is safe and effective in its intended role as a data conduit, not to assess its ability to provide clinical insights or make diagnoses.

Therefore, many of the requested categories (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, type of ground truth, training set information) are not applicable to this device and are not present in the provided submission.

Based on the provided text, here’s a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not applicable / Not provided. The device is a data communication system. The testing described includes unit, integration, and final acceptance testing, as well as performance, safety, and environmental testing. These types of tests typically involve controlled lab environments and specific test cases designed to test system functionality, communication integrity, and adherence to power/environmental standards, rather than a "test set" of patient data in the context of diagnostic performance. There is no mention of patient data being used for device performance evaluation in this context.

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)

• Not applicable / Not provided. Ground truth for diagnostic accuracy is not relevant for this type of device.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not applicable / Not provided.

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

• Not applicable / Not provided. This device is not an AI/ML diagnostic tool; it's a data network interface.

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

• Not applicable / Not provided. The device's function is purely data transmission and conversion; it does not provide an "algorithm only" diagnostic output.

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

• Not applicable / Not provided. The "truth" for this device relates to whether data is accurately acquired, converted, and transmitted without corruption, and whether it functions according to its specifications and regulatory standards. There is no diagnostic ground truth.

8. The sample size for the training set

• Not applicable / Not provided. This device is not an AI/ML model that would require a "training set" of data in that sense.

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

• Not applicable / Not provided.

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The Dash 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, inter-hospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and pre-hospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The Dash 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The Dash 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The Dash 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12 lead ECG analysis (12SL). Additionally, the network interface allows for the display and transfer of network available patient data.

The provided document refers to the K020290 submission for the GE Medical Systems Information Technologies Dash 3000/4000 Patient Monitor. This submission is a 510(k) premarket notification, which means the device is seeking substantial equivalence to a predicate device rather than presenting novel acceptance criteria or a detailed clinical study for efficacy.

Therefore, the document does NOT contain the specific information requested in the prompt regarding:

• A table of acceptance criteria and reported device performance.
• Sample sizes, data provenance, number of experts, adjudication methods, or ground truth details for a test set.
• Information on multi-reader multi-case (MRMC) comparative effectiveness studies.
• Details of a standalone algorithm performance study.
• Sample size and ground truth establishment for a training set.

Instead, the document focuses on the regulatory aspects of a 510(k) submission, confirming the device's intended use, classification, and that it "employs the same functional scientific technology as its predicate devices."

The "Test Summary" section lists quality assurance measures applied to the development, which are general engineering and quality management practices, not specific clinical performance studies with acceptance criteria as typically understood for AI/ML devices. These measures include:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Testing on unit level (Module verification)
• Integration testing (System verification)
• Final acceptance testing (Validation)
• Performance testing
• Safety testing
• Environmental testing

The conclusion states: "The results of these measurements demonstrated that the Dash 3000/4000 Patient Monitor are as safe, as effective, and perform as well as the predicate device." This is a statement of substantial equivalence, not a report of meeting specific numerical performance criteria from a clinical study.

In summary, the provided document does not contain the detailed study results and acceptance criteria as requested because it is a 510(k) summary for a patient monitor, which relies on demonstrating substantial equivalence to a predicate device rather than presenting novel clinical performance data against predefined acceptance criteria in the manner expected for an AI/ML device.

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MAC-LAB System:
The MAC-LAB System is intended for use under the direct supervision of a licensed healthcare practitioner to monitor and/or calculate and/or record cardiovascular data from patients as they undergo cardiac catheterization. Cardiovascular data may be manually entered or acquired via an interfaced GE Medical Systems Information Technologies TRAM modules (K921669), MUSE cardiovascular system and other interfaced information systems. Data includes: ECG waveforms, heart rate, pulse oximetry (SpO2), respiration rate, valve gradients and areas, cardiac output, hemodynamic measurements, invasive and noninvasive blood pressure, procedural information, and optional intracardiac electrocardiogram (IECG). This information can be displayed, trended, stored, printed and/or transmitted to other networked hospital information systems. The system does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities.

CardioLab EP System:
The CardioLab EP System is intended for use under the direct supervision of a licensed healthcare practitioner to acquire, filter, digitize, amplify, display, and record electrical signals obtained during electrophysiological studies and related procedures conducted in an electrophysiological laboratory. Signal types acquired include ECG signals, direct cardiac signals, and pressure recordings. Physiological parameters such as diastolic, systolic, and mean blood pressure, heart rate, and cycle length may be derived from the signal data, displayed and recorded. The system allows the user to monitor the acquisition of data, review the data, store the data, perform elementary caliper-type measurements of the data, and generate reports on the data. Additionally, the system may acquire, amplify, display, and record data received from other medical devices typically used during these procedures, such as imaging devices and RF generators. The system does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities.

The ComboLab System
The ComboLab is the combination of both CardioLab EP and MAC-LAB allowing the user to run the CardioLab EP and MAC-LAB modes, though only one mode may be used at a time (CardioLab EP for electrophysiology lab cases and MAC-LAB for catheterization lab cases). The system does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities.

The MAC-LAB / CardioLab EP and ComboLab systems do not control the delivery of energy, administer drugs, perform any life-supporting or life-sustaining functions, or analyze physiological data or other data acquired during procedure.

The MAC-LAB System is a microprocessor based data acquisition system used during cardiac catheterization procedures. The MAC-LAB system, via various models of the GE Medical Systems Information Technologies TRAM module (K921669) and amplifier module, acquires patient data which may include surface ECG, invasive and non-invasive blood pressure, blood oxygen saturation via pulse oximetry, respiration, and temperature. The TRAM module is housed in a dedicated front end chassis called the remote acquisition case (RAC). The MAC-LAB System joins together the TRAM module and amplifier module with computer processors, software, high resolution display monitors, power supply, laser printer, keyboard and mouse. Digital data is transmitted, via cable, from the TRAM module and/or amplifier module to the computer for processing. Major functions of the software include data acquisition and display, data storage, reporting of data, and transmission of data to other information systems via LAN.

The CardioLab EP System is a microprocessor based data acquisition system used during electrophysiology procedures to acquire ECG, intracardiac signals, and pressure signals via amplifier module. Digital data is also acquired from other devices such as RF generators, fluoro video systems and the GE Medical Systems Information Technologies TRAM module. The ECG, intracardiac and pressure data are acquired by an amplifier that is connected to the patient by third-party devices such as ECG leadwires and catheters. The amplifier filters, amplifies, digitizes and transmits the data to the computer via fiber optic cable. The computer stores the data on optical disks, displays the data on the video monitors, allows the user to perform basic signal measurements, and prints out waveforms on a laser printer or continuous paper recorder. Major functions of the software include data acquisition and display, data storage, reporting of data, and transmission of data to other information systems via LAN.

The product will be available in three configurations: CardioLab EP application only, MAC-LAB application only, or combination of both CardioLab EP and MAC-LAB applications. The 'CardioLab EP only' configuration only allows the user to run the CardioLab EP mode. The 'MAC-LAB only' configuration only allows the user to run the MAC-LAB mode. The combination of both CardioLab EP and MAC-LAB allows the user to run the CardioLab EP and MAC-LAB modes, though only one mode may be used at a time (CardioLab EP for electrophysiology lab cases and MAC-LAB for catheterization lab cases).

The provided document is a 510(k) Summary for the GE Medical Systems Information Technologies MAC-LAB/CardioLab EP/ComboLab System from 2002. This type of submission is for demonstrating substantial equivalence to a predicate device, not for proving that a new device meets specific quantitative performance acceptance criteria through a detailed study comparing its performance to a defined ground truth.

Therefore, the document does not contain the specific information requested regarding acceptance criteria, a detailed study proving the device meets those criteria, or the methodology of such a study (sample sizes, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth types, or training set details).

Instead, the document focuses on demonstrating that the new device is as safe, as effective, and performs as well as predicate devices through:

• Technology Equivalence: Stating that the proposed system employs "the same functional technology as the predicate device."
• Compliance with Voluntary Standards: Mentioning that the systems comply with voluntary standards (details not provided in this excerpt).
• Quality Assurance Measures: Listing general quality assurance activities applied to development: requirements specification review, code inspections, software and hardware testing, safety testing, environmental testing, and final validation.

The "Test Summary" section explicitly states: "The results of these measurements demonstrate that the MAC-LAB/CardioLab EP/ComboLab System are as safe, as effective, and perform as well as the predicate devices." This is a general statement of equivalency rather than a presentation of data against specific, quantifiable acceptance criteria.

In summary, none of the requested information (points 1-9) about acceptance criteria, study design, and performance metrics can be extracted directly from this 510(k) summary.

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The Unity® IS Patient Viewer is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the Unity® IS Patient Viewer is to provide a remote view of physiological parameter data on adult, pediatric and neonatal patients within a hospital or facility providing patient care. The Unity® IS Patient Viewer is NOT intended for primary monitoring but is to be used in conjunction with the bedside monitor. The Unity® IS Patient Viewer is intended to provide near-real-time physiological data and graphical trends for all monitors connected to the Unity Network to secure nurse and physician personal computers (local and remote).

The Unity® IS Patient Viewer provides remote access to waveform, parameter data and trend data at a web browser on a standard personal computer. The server resides on the hospital's intranet and remote access is gained through secured access to the hospital intranet. The data relayed from the patient monitors over the Unity® MC network includes patient name, unit and bed name, parameter data, and waveform data monitored by the bedside monitors. The user can view up to nine waveforms from the Unity® MC network as well as the parameter information in near real-time. Neither alarm messages nor parameter status messages are displayed. The Unity® IS Patient Viewer system provides a secondary view of patient information, and is NOT a patient monitoring device. The clinician is instructed to always reference the primary bedside monitor before making any patient care decisions. In the event that data is not available via the Unity® IS Patient Viewer, the clinician is instructed to obtain the data from the primary bedside monitor. The Unity® IS Patient Viewer system consists of a 1U Rack Mountable Server with server and client software packages. The two software pieces reside on the 1U Rack Mountable Server, which is a standard hardware server platform for hosting network applications. The hardware server is connected to two networks: Unity® Network and the hospital's Intranet. The Unity® Network is a currently marketed proprietary network connecting patient monitors. The hospital's Intranet refers to the existing Local Area Network (LAN) within the hospital that connects a number of personal computers (PCs).

The provided text describes the Unity® IS Patient Viewer, a device intended for remote viewing of physiological data. However, the document does not include specific acceptance criteria or a detailed study report that proves the device meets such criteria.

The "Test Summary" section in {1} lists various quality assurance measures applied during development, such as:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Testing on unit level (Module verification)
• Integration testing (System verification)
• Final acceptance testing (Validation)
• Performance testing
• Safety testing
• Environmental testing

It concludes that "The results of these measurements demonstrated that the Unity® IS Patient Viewer are as safe, as effective, and perform as well as the predicate device." However, no quantitative acceptance criteria or the reported device performance against those criteria are provided.

Therefore, I cannot fulfill the request to provide a table of acceptance criteria and reported device performance, nor can I answer points 2 through 9, as the necessary information is not present in the provided text. The document is a 510(k) summary, which typically provides a high-level overview rather than detailed study results.

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The ApexPro Telemetry System is intended for use under the direct supervision of a licensed healthcare practitioner. The system is designed to acquire and monitor physiological data for ambulating patients within a defined coverage area. The system processes this physiological data to detect various ECG arrhythmia events and select physiological parameter limit violations.

The ApexPro Telemetry System is intended to be installed in the hospital or clinical environment in order to provide clinicians with patient physiological data, while allowing for patient mobility. These systems are typically deployed in sub acute care areas in hospitals or clinical sites where patient mobility can enhance the effectiveness of the medical procedures administered.

The physiological parameters monitored include ECG, non-invasive blood pressure and SpO2. The ApexPro Telemetry System is intended to provide ECG data via Ethernet to the computer platform for processing. The ApexPro is also intended to provide physiologic data over the Unity network to clinical information systems for display.

The ApexPro Telemetry System is composed of six major components:
• The patient worn data acquisition transmitters
• The receiver antenna system infrastructure
• The receivers
• The receiver subsystem
• A computer platform running the ApexPro Telemetry Application
• A computer platform running a central station application (which may be the same computer platform running the ApexPro Telemetry Application)

The provided text is a 510(k) summary for the ApexPro Telemetry System. While it states that the device complies with voluntary standards and mentions quality assurance measures, it does not include detailed acceptance criteria or a study proving that the device meets specific performance metrics.

Here's what can be extracted based on the provided text, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

Missing Information: The document states that the ApexPro "complies with the voluntary standards as detailed in The following quality assurance Section 9 of this submission." However, Section 9 is not provided in this document, so the specific voluntary standards and their associated acceptance criteria are unknown. No quantitative performance metrics for the device (e.g., accuracy of arrhythmia detection, sensitivity, specificity) are given in this summary.

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

Missing Information: The document does not specify any sample size used for a test set, nor does it mention the data provenance (country of origin, retrospective/prospective). The study described is a general "test summary" of quality assurance measures, not a clinical trial with a defined test set of patient data.

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

Missing Information: Since no specific clinical test set is described, there is no information about experts used to establish ground truth.

4. Adjudication Method for the Test Set:

Missing Information: No test set or adjudication method is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:

Missing Information: No MRMC study is mentioned. The document primarily focuses on demonstrating substantial equivalence to a predicate device through technological similarity and quality assurance, rather than a comparative effectiveness study with human readers.

6. If a Standalone (algorithm only without human-in-the-loop performance) was Done:

The document describes the device as processing "physiological data to detect various ECG arrhythmia events and select physiological parameter limit violations." This implies an algorithmic component. However, no standalone performance study details (e.g., sensitivity, specificity of the algorithm itself) are provided in this summary. The "Test Summary" section refers to "Software and hardware testing," which might include standalone performance, but no results are detailed.

7. The Type of Ground Truth Used:

Ground truth for "software and hardware testing" and "safety testing" would likely refer to internal verification and validation against known standards and simulated or real-world scenarios. However, the exact type of ground truth (e.g., expert consensus, pathology, outcomes data) for specific physiological data detection claims is not stated.

8. The Sample Size for the Training Set:

Missing Information: No training set or its sample size is mentioned, as this document is not describing a machine learning model training process in detail.

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

Missing Information: Since no training set is described, there is no information on how its ground truth was established.

In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device through system description, intended use, and a high-level overview of quality assurance measures, rather than a detailed performance study with specific acceptance criteria and outcome metrics.

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The PatientNet™ System is intended to collect and analyze patient data from ECG ambulatory The Pational - Syctorn - Jeading manufacturers' bedside monitors and ventilators anywhere in a healthcare facility and distributes the data to locations throughout the facility.

Monitoring of Recognized Conditions:
-An environmentally controlled clinical setting that has multiple patients using any combination of ECG leads, bedside monitors, or ventilators.
-Hospital areas that have the capability of installing hardwire paths to the Central Monitoring Station from the rooms or areas where bedside monitors or ventilators operate.
-Clinical areas that have the capability of installing 174-216 MHz radio systems (or alternate frequency bands approved by the FCC) to communicate via RF. The information from the ECG leads, bedside monitors or ventilators is transferred via an RF transmitter to the Central Monitoring Station.

Target Population:
Those patients who are connected through PatientNet™ Monitoring System via ambulatory ECG transmitters, bedside monitors, or ventilators.

The modified PatientNet™ Monitoring System performs patient monitoring using PatientNet™ rne moulhou Patient for radio transmitters connected directly to bedside monitors or athbuittory fudio transmitors with similar physiological parameters, and to ventilators that have digital outputs.

The provided documentation does not contain detailed acceptance criteria or a study that specifically proves the device meets such criteria in terms of performance metrics like sensitivity, specificity, accuracy, or any other quantitative measure typically associated with medical device performance studies.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (VitalCom Networked Monitoring System K962473) through "risk analysis and verification and validation testing." The document states that "Test results demonstrated that the functionality and safety characteristics of the modified PatientNet™ Monitoring System are to the predicate device," implying that the acceptance criterion was likely meeting the functional and safety profile of the predicate device.

Here's an breakdown of the information that can be extracted from the provided text, while also explicitly stating what is not present:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information:

• Specific numerical performance metrics (e.g., accuracy, reliability, latency, data integrity rates).
• Quantitative thresholds for acceptance (e.g., "data transfer success rate must be >99%").

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

This information is not provided in the document. The submission mentions "verification and validation testing" but does not specify the sample size of the test set, the type of data used (e.g., simulated, real patient data), or its provenance (country of origin, retrospective/prospective).

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not provided. The type of testing described (risk analysis, verification and validation) for a network monitoring system typically doesn't involve the establishment of "ground truth" by clinical experts in the same way an AI diagnostic device would. It's more about technical verification of functionality and safety.

4. Adjudication Method for the Test Set

This information is not provided. Since the nature of the "test set" and "ground truth" for a network monitoring system validation is not clinical expert-based, an adjudication method like 2+1 or 3+1 would not apply.

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

A MRMC comparative effectiveness study was not done and would not be applicable for this type of device. An MRMC study is relevant for devices, especially AI-driven ones, where human readers interpret medical images or data, and the study aims to assess how the AI assistance impacts their diagnostic performance. The PatientNet™ Monitoring System is a data collection and distribution system, not a diagnostic interpretation tool.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study, as typically understood for an AI algorithm (i.e., algorithm only without human-in-the-loop performance), was not done or at least not described in this document. The assessment described ("risk analysis and verification and validation testing") focuses on the system's ability to perform its intended functions and meet safety requirements, rather than an "algorithm-only" performance for diagnostic accuracy.

7. Type of Ground Truth Used

The concept of "ground truth" (expert consensus, pathology, outcomes data) as it applies to diagnostic accuracy studies is not relevant or specified here. For a network monitoring system, "ground truth" would likely relate to the system correctly acquiring, transmitting, and displaying physiological data as intended, which would be verified through technical means against known inputs or reference standards rather than clinical outcomes.

8. Sample Size for the Training Set

This information is not provided. This device is a data collection and distribution system, not an AI/ML device that requires a "training set" in the conventional sense for learning patterns or making predictions.

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

This information is not provided. As noted above, the concept of a training set and its associated ground truth is not applicable to the description of this device.

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The Solar 8000M System is intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in the use of the equipment. The Solar 8000M is a multiparameter physiological patient monitoring system intended for use on adult, pediatric and neonatal patients, within a hospital or facility environment. The Solar 8000M System is capable of monitoring electrocardiogram, non-invasive pressure, pulse, invasive blood pressure, blood temperature, cardiac output, respiration, pulse oximetry, venous O2 saturation, Transcutaneous O2 and CO2 respiratory mechanics, and/or (for adult and/or pediatric patients) anesthetic agent concentrations, impedance cardiography, electroencephalography and bispectral index. O2 and CO2 concentrations are available for neonates not under anesthesia. Information can be displayed, trended and stored in the monitor from a variety of peripheral devices. The Solar 8000M System is also intended to provide physiologic data over the UNITY Tu network. The Solar 8000M System was developed to interface with third party peripheral devices that support serial and/or analog data outputs.

The Solar 8000M System includes the following basic components: Solar 8000M processing unit a display TRAM-rac housing acquisition module(s) keypad and/or remote control Additional, optional components include: Clinical Information Center (central station) Remote display digital writer or printer TRAM-Net interface adapter(s) Octanet connectivity device Remote Alarm Box

This submission describes a patient monitoring system and does not contain detailed performance metrics or specific acceptance criteria in the format typically seen for algorithm-based devices. Therefore, I cannot extract all the requested information for acceptance criteria and a study that proves the device meets them.

However, I can provide information based on the available text:

Here's an analysis of the provided text in relation to your request:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table with specific, quantifiable acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) and corresponding reported device performance values. The "Test Summary" only lists the types of tests performed.

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

The document does not specify a sample size for any "test set" in the context of an algorithm's performance. It mentions "Clinical use validation" but provides no details on the number of patients, data origin, or whether it was retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

This information is not provided. The submission focuses on hardware and system functionality, not algorithmic interpretation requiring expert ground truth.

4. Adjudication Method:

This information is not provided.

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

No MRMC study is mentioned. This submission is about a patient monitoring system, not an AI-assisted diagnostic tool.

6. Standalone Performance:

The document does not describe standalone (algorithm-only) performance in the sense of a diagnostic algorithm without human intervention. The device's function is to display and store physiological data for healthcare practitioners.

7. Type of Ground Truth Used:

The concept of "ground truth" as it applies to diagnostic algorithms (e.g., pathology, expert consensus) is not relevant to this submission. The "ground truth" for a patient monitor would be the actual physiological readings, which are measured directly by the device's sensors. The document states "performance testing" was done, implying comparison against expected physiological values or established calibration standards for each parameter monitored.

8. Sample Size for the Training Set:

This information is not applicable. The device described is a physiological patient monitor, not an AI/ML algorithm that undergoes a "training set."

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

This information is not applicable, as there is no training set for an AI/ML algorithm.

Summary of available information related to performance and testing:

Acceptance Criteria (Implicit and general, not specific metrics):

• Safety: The device is as safe as the predicate device.
• Effectiveness: The device is as effective as the predicate device.
• Performance: The device performs as well as the predicate device.
• Compliance: The device complies with voluntary standards.
• Functionality: Adherence to requirements (via requirements reviews, design reviews, unit, integration, and final acceptance testing).
• Environmental Robustness: Successful environmental testing.

Study/Testing Information:

The document mentions a "Test Summary" with the following quality assurance measures and testing:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Testing on unit level (Module verification)
• Integration testing (System verification)
• Final acceptance testing (Validation)
• Performance testing
• Safety testing
• Environmental testing
• Clinical use validation

Conclusion from the Submission:

"The results of these measurements demonstrated that the Solar 8000M System are as safe, as effective, and perform as well as the predicate device."

Predicate Device: K993757 Solar 7/8000 System

In essence, this 510(k) submission establishes substantial equivalence to a predicate device based on similar technology and comprehensive quality assurance testing, rather than an AI-specific performance study with detailed acceptance criteria and ground truth analysis.

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