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The Vigileo™ APCO/Oximetry Monitor is indicated for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics. The monitor also displays parameters, such as stroke volume and stroke volume variation, used to assess fluid status and vascular resistance. The Vigileo™ APCO/Oximetry Monitor may be used in all settings in which critical care is provided.

The Vigileo™ Arterial Pressure Cardiac Output (APCO)/Oximetry Monitor (Vigileo™ Monitor) is a microprocessor-based instrument. When used with an Edwards FloTrac sensor, the Vigileo™ Monitor is capable of continuously monitoring the following parameters: Cardiac Output (CO); Cardiac Index (CI): Stroke Volume (SV): Stroke Volume Variation (SVV); Systemic Vascular Resistance (SVR); Systemic Vascular Resistance Index (SVRI); Oxygen Delivery (DO2); and Oxygen Delivery Index (DO2I). When used with Edwards Oximetry catheters, the Vigileo™ Monitor is capable of continuously monitoring the following parameters: Central venous oxygen saturation (ScvO2); and, Mixed venous oxygen saturation (SvO2).

The Vigileo™ Monitor, version 3.08, is a microprocessor-based instrument designed for continuous monitoring of hemodynamic parameters and oximetry. The provided text, a 510(k) summary, outlines its acceptance criteria and the studies conducted to demonstrate its safety and effectiveness.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly state numerical acceptance criteria in a table format for specific performance metrics (e.g., accuracy, precision for CO, CI, etc.). Instead, the acceptance criteria are implicitly stated as demonstrating "substantially equivalent" performance to the predicate device (K103094, Vigileo™ Arterial Pressure Cardiac Output/Oximetry Monitor). The reported device performance is described in terms of successful completion of various tests, confirming this substantial equivalence.

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

The 510(k) summary mentions "pre-clinical animal studies" and "comparative analysis of clinical data" and "comparison testing of clinical cases" for the test set. However, it does not specify the exact sample size (number of patients, animals, or data points) used for these test sets.

The data provenance is stated as including:

• Bench studies: Likely internal laboratory testing.
• Pre-clinical animal studies: Originating from animal subjects. The country of origin is not specified but typically would be internal to the company or contracted research in a regulated environment.
• Clinical data/cases: Originating from human patients. The country of origin and whether the data was retrospective or prospective is not specified.

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

The document does not specify the number of experts used to establish ground truth for the test set, nor does it detail their qualifications. The study relies on "comparative analysis of clinical data" and "comparison testing of clinical cases" against a predicate device, implying that the ground truth for these clinical cases would have been established through a combination of established clinical methods and the predicate device's measurements.

4. Adjudication Method for the Test Set

The 510(k) summary does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for the test set. It mentions "comparative analysis" and "comparison testing," which suggests direct comparison of the subject device's outputs with the predicate device's outputs or established clinical reference methods, rather than a human expert adjudication process for image interpretation or diagnosis.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The device in question is a monitor that provides numerical hemodynamic and oximetry parameters, not an imaging device or AI algorithm for diagnosis that would typically involve human readers. The comparative effectiveness focused on the technical performance of the device itself against a predicate, not on how human readers' performance improves with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

While the device is a "Single-Function, Preprogrammed Diagnostic Computer," the term "standalone" in the context of AI often refers to an algorithm making a diagnosis without human input. This device provides physiological measurements to clinicians, rather than a diagnostic interpretation in the way an AI algorithm might. Therefore, the concept of a standalone AI algorithm is not directly applicable here. The device performs its functions (calculating CO, CI, SV, etc.) based on physiological inputs, which is inherently a "standalone" processing of data, but it's not an AI making a medical decision. The primary assessment was device performance and functionality, not an AI algorithm's diagnostic capabilities.

7. The Type of Ground Truth Used

The ground truth for evaluating the Vigileo™ Monitor's performance was established through:

• Comparison to a predicate device (K103094): The primary method of demonstrating substantial equivalence was by comparing the performance and functionality of the subject device against the previously cleared predicate device.
• Established clinical methods/measurements: Implied in the "pre-clinical animal studies" and "comparative analysis of clinical data," the accuracy of the measurements would be referenced against recognized standards or gold standard measurements for cardiac output and oximetry, even if not explicitly detailed in this summary.

8. The Sample Size for the Training Set

The 510(k) summary does not mention a "training set" in the context of machine learning or AI development. This device is a preprogrammed diagnostic computer that likely uses established physiological algorithms, not a machine learning model that requires a training set. Therefore, this question is not applicable in the context of the provided document.

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

As there is no mention of a "training set" for a machine learning model, the question of how its ground truth was established is not applicable based on the provided information.

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The Vigileo APCO/Oximetry Monitor is indicated for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics. The monitor also displays parameters, such as stroke volume and stroke volume variation, used to assess fluid status and vascular resistance. The Vigileo APCO/Oximetry Monitor may be used in all setting in which critical care is provided.

The Vigileo Arterial Pressure Cardiac Output (APCO)/Oximetry Monitor (Vigileo Monitor) is a microprocessor-based instrument. When used with the FloTrac sensor, the Vigileo Monitor continuously measures key parameters of arterial pressure cardiac output (CO), cardiac index (CI), oxygen delivery (DO2), oxygen delivery index (DO2I), stroke volume (SV), stroke volume variation (SVV), stroke volume index (SVI), systemic vascular resistance (SVR) and systemic vascular resistance index (SVRI). When used with Edwards oximetry catheters, the Vigileo Monitor measures central venous oxygen saturation (ScvO2) and mixed venous oxygen saturation (SvO2). The instrument software has been revised to enhance the SVV algorithm, improve the GUI and add compatibility with additional external devices for data output.

The provided text describes the Vigileo Arterial Pressure Cardiac Output (APCO)/Oximetry Monitor. This submission is a 510(k) for a revised version of an existing device, focusing on software enhancements rather than a new clinical application. As such, the study described is a comparison to a predicate device, aiming to demonstrate substantial equivalence, rather than a clinical trial establishing effectiveness against acceptance criteria in the way a novel device might.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state formal "acceptance criteria" in terms of specific performance metrics (e.g., accuracy, sensitivity, specificity, or error bounds for CO/SVV measurements) that the device must meet against a predefined gold standard. Instead, the focus is on substantial equivalence to a predicate device (K082308, an earlier version of the Vigileo Arterial Pressure Cardiac Output/Oximetry Monitor).

The reported device performance is described in a qualitative manner:

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

The document mentions "comparison testing of clinical cases" and "comparative analysis of clinical data" but does not provide specific numbers for the sample size (e.g., number of patients, number of data points) used in these clinical comparisons.

The data provenance (country of origin, retrospective/prospective) is not specified.

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

This information is not provided. Given that the study is a comparison to a predicate device for substantial equivalence with minor software revisions, it's unlikely that independent experts were used to establish a new "ground truth" for the test set in the same way one might for a diagnostic imaging AI with unknown pathology. The "ground truth" for comparison would likely be the measurements obtained from the predicate device itself, or potentially highly accurate invasive measurements (e.g., thermodilution cardiac output) if those were used to validate both the predicate and the revised device in parallel. The document does not specify this.

4. Adjudication Method for the Test Set:

This information is not provided. As above, for a device modification showing substantial equivalence to a predicate, a complex adjudication process by multiple human annotators is less likely to be applicable.

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

No, an MRMC comparative effectiveness study was not done. The device itself is a monitor for physiological parameters, not a diagnostic imaging aid that human readers interpret. Therefore, the concept of "human readers improving with AI vs. without AI assistance" does not apply to this device. The "AI" here refers to algorithms for calculating hemodynamic parameters, not an assistance tool for human interpretation.

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

Yes, the primary evaluation described is a standalone performance assessment. The Vigileo Monitor, with its enhanced SVV algorithm, directly generates numerical outputs for various hemodynamic parameters. The testing involved comparing these outputs from the revised device against those from the predicate device (and potentially against a gold standard method if available, though not explicitly stated as such for this submission). There is no "human-in-the-loop" aspect to the output generation from the device itself.

7. The Type of Ground Truth Used:

The document implies that the ground truth for comparison was the measurements obtained from the predicate device (K082308). It states "comparative analysis of clinical data" between the "pending and the predicate devices." While it's possible that a more invasive, established gold standard (like thermodilution for cardiac output) was also used in the original validation of the predicate device, it's not explicitly stated as the ground truth for this particular submission's comparison. The software enhancements were validated against the behavior of the previous software version.

8. The Sample Size for the Training Set:

This information is not provided. The document makes no mention of a "training set" in the context of machine learning, which is a modern concept for AI. The "SVV algorithm enhancement" is more likely a traditional algorithmic improvement rather than a deep learning model trained on a large dataset. Therefore, the concept of a "training set" as understood in current AI contexts is unlikely to apply directly here.

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

As per point 8, the concept of a "training set" for a machine learning model is not explicitly mentioned or implied. If the SVV algorithm was "enhanced," it would likely have been refined based on established physiological principles and potentially validated against existing physiological data or expert consensus on wave-form analysis, rather than through a machine learning training process with a distinct ground truth dataset. The document doesn’t provide details on the specific method of algorithm enhancement or its associated ground truth establishment.

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The Vigileo APCO/Oximetry Monitor is indicated for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics.

The Vigileo APCO/Oximetry Monitor is a microprocessor-based instrument which, when connected to a FloTrac sensor, continuously measures arterial pressure cardiac output (APCO). When connected to an Edwards oximetry catheter, the monitor measures oxygen saturation (oximetry) in adults or pediatrics. The monitor also calculates other derived parameters including cardiac index, stroke volume, stroke volume index, stroke volume variation, systemic vascular resistance, systemic vascular resistance, delivered oxygen, delivered oxygen index, and pulse oximetry saturation.

This 510(k) submission describes the Vigileo APCO/Oximetry Monitor, which is intended to continuously measure hemodynamic parameters like cardiac output and oximetry. The submission claims substantial equivalence to a predicate device (Vigileo APCO/Oximetry Monitor: K062134) and states that functional testing was performed to demonstrate this equivalence. However, no specific acceptance criteria or detailed study results are provided in the provided text. The document focuses on the regulatory aspects of the submission and the determination of substantial equivalence based on functional testing and comparative analysis to the predicate device.

Given the information provided:

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

   • Acceptance Criteria: Not explicitly stated in the provided text. The submission broadly claims "equivalence to the predicate device" and that the device "has been demonstrated to be as safe and effective as the predicate device."
   • Reported Device Performance: Not detailed in terms of specific metrics. The text only states that the device "successfully underwent functional testing demonstrating equivalence to the predicate device."

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

   • Not specified in the provided text.

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 as no specific test set requiring expert-established ground truth is described. The evaluation relies on functional testing and comparison to a predicate device.

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

   • Not applicable as no specific test set requiring adjudication is 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:

   • Not applicable. This device is a monitor, not an AI-assisted diagnostic tool for human readers.

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

   • The "functional testing" mentioned implies a standalone evaluation of the device's performance against the predicate. However, details of this testing are not provided.

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

   • Not explicitly stated. The "functional testing" would likely involve comparing the device's measurements against a known standard or a validated reference method, which serves as the de-facto ground truth for such a device. This reference method is typically the "predicate device" in a substantial equivalence claim.

8. The sample size for the training set:

   • Not applicable, as this device is not described as involving a machine learning algorithm that requires a training set.

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

   • Not applicable, as no training set is mentioned.

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The Vigileo APCO/Oximetry Monitor is indicated for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics.

The Vigileo APCO/Oximetry Monitor is a microprocessor- based instrument which, when connected to a FloTrac sensor, continuously measures arterial pressure cardiac output (APCO). When connected to an Edwards oximetry catheter, the monitor measures oxygen saturation (oximetry) in adults or pediatrics. The monitor also calculates other derived parameters including cardiac index, stroke volume, stroke volume index, stroke volume variation, systemic vascular resistance, systemic vascular resistance, delivered oxygen, delivered oxygen index, and pulse oximetry saturation.

The provided text is a 510(k) summary for the Vigileo APCO/Oximetry Monitor. It is a regulatory document and does not contain detailed information about acceptance criteria or specific study designs to prove device performance against such criteria. The document states that the device has undergone "functional testing demonstrating equivalence to the predicate device" and that a "Comparative Analysis" demonstrated it to be "as safe and effective as the predicate device." However, it does not provide the specifics of these tests or analyses.

Therefore, I cannot extract the requested information from the provided text. The document focuses on regulatory approval based on substantial equivalence to a predicate device rather than a detailed performance study with acceptance criteria.

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The PreSep Oximetry and PediaSat Oximetry Catheters are indicated for hemodynamic monitoring in adults and pediatrics through blood sampling, hemodynamic monitoring and oxygen saturation measurement.

The dilator, included with each catheter, is indicated for enlarging the opening in a vessel for preparation of percutaneous entry of the catheter.

The Vigileo Arterial Pressure Cardiac Output /Oximetry Monitor is indicated for continuously measuring arterial pressure cardiac output and oximetry to assess oxygen delivery and consumption. When connected to an Edwards oximetry catheter, the monitor measures oximetry in adults and pediatrics.

The PreSep Oximetry and PediaSat Oximetry Catheters are used with Edwards oximetry monitors to continuously measure oxygen saturation in adults and pediatrics. These catheters also provide the means for infusion of solutions, measuring pressure and taking blood samples. The dilator included with either the PreSep Oximetry or PediaSat Oximetry Catheter is used to enlarge the opening in a vessel for preparation of percutaneous entry of the catheter.

The Vigileo APCO/Oximetry monitor is a microprocessor-based instrument which, when connected to a dual disposable pressure transducer (DDPT), continuously measures arterial pressure cardiac output (APCO). When connected to an Edwards oximetry catheter, the monitor measures oxygen saturation (oximetry) in adults or pediatrics. The monitor also calculates other derived parameters including cardiac index, stroke volume, stroke volume index, stroke volume variation, system vascular resistance, and systemic vascular resistance index.

The provided text describes a 510(k) summary for the Edwards Lifesciences PreSep Oximetry and PediaSat Oximetry Catheters, and the Vigileo Arterial Pressure Cardiac Output/Oximetry Monitor.

Based on the provided text, the submission does NOT include specific acceptance criteria or a study proving the device meets quantitative acceptance criteria in the typical sense for an AI/ML device.

The submission is for a medical device cleared through the 510(k) pathway, which focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving performance against specific acceptance criteria with detailed statistical studies as would be expected for a novel AI/ML algorithm.

Therefore, the following information cannot be extracted directly from the provided document:

1. A table of acceptance criteria and the reported device performance: Not present. The submission focuses on substantial equivalence rather than numerical performance against pre-defined criteria.
2. Sample size used for the test set and the data provenance: Not present. There is no mention of a "test set" in the context of an AI/ML performance study. The functional testing mentioned is likely for engineering verification and validation of the device hardware and software, not an AI/ML performance evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not present. Ground truth for an AI/ML system is not applicable here as it is not an AI/ML device.
4. Adjudication method for the test set: Not present.
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 is not an AI/ML device, so an MRMC study is not relevant and not mentioned.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: This is not an AI/ML device, so "standalone algorithm performance" is not relevant and not mentioned.
7. The type of ground truth used: Not applicable as this is not an AI/ML device.
8. The sample size for the training set: Not applicable as this is not an AI/ML device.
9. How the ground truth for the training set was established: Not applicable as this is not an AI/ML device.

What is present in the document is a claim of substantial equivalence and successful functional testing:

• Acceptance Criteria (Implicit for 510(k) clearance): Substantial equivalence to predicate devices regarding safety and effectiveness for their intended use.
• Study Proving Acceptance Criteria:
  • "The PreSep Oximetry and PediaSat Oximetry Catheters, dilator and the Vigileo Arterial Pressure Cardiac Output/Oximetry Monitor have been demonstrated to be as safe and effective as the predicate devices for their intended use."
  • "The PreSep Oximetry and PediaSat Oximetry Catheters, dilator and the Vigileo Arterial Pressure Cardiac Output/Oximetry Monitor have successfully undergone functional testing. These products have been shown to be equivalent to the predicate devices."

In summary, the provided text describes a traditional medical device submission (catheters and a monitor) and not an AI/ML device. Therefore, the specific criteria requested for an AI/ML performance study are not found in this document. The "study" mentioned is the functional testing and comparative analysis to predicate devices to establish substantial equivalence for 510(k) clearance.

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The Vigileo APCO/Oximetry monitor is intended to measure arterial pressure cardiac output and oximetry. The monitor also calculates hemodynamic and oxygenation parameters. The DDPT is intended to measure intravascular pressures. It is intended to transmit those pressure readings to both a standard blood pressure monitor and to the Vigileo monitor.

The Vigileo APCO/Oximetry monitor is indicated for use for continuously measuring hemodynamic parameters such as cardiac output and oximetry to assess oxygen delivery and consumption.

The Pressure Monitoring Kit with TruWave dual disposable pressure transducer is indicated for use in intravascular pressure monitoring. It is also indicated for use with Edwards pulse pressure based cardiac output monitoring devices or hardware to measure cardiac output.

The Vigileo APCO/Oximetry monitor is a microprocessor-based instrument which, when connected to a DDPT, continuously measures arterial pressure cardiac output (APCO). When connected to an Edwards oximetry catheter, the monitor measures oxygen saturation (oximetry). The monitor also calculates other derived parameters including cardiac index, stroke volume, stroke volume index, stroke volume variation, system vascular resistance, and systemic vascular resistance index.

The provided 510(k) summary for the Vigileo APCO/Oximetry Monitor and Edwards Dual Disposable Pressure Transducer (DDPT) does not contain the detailed acceptance criteria or the specific study details that prove the device meets these criteria in the way a modern AI/ML device submission would. This submission is from 2005 and for a non-AI/ML medical device, focusing on substantial equivalence to predicate devices based on functional and safety testing.

Therefore, many of the requested fields cannot be directly extracted from the provided text. I will address each point based on the information available and indicate where information is missing or not applicable to this type of submission.

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

The submission does not explicitly state quantitative acceptance criteria in a dedicated table or reported performance metrics from a clinical study for the Vigileo device itself. Instead, the "Comparative Analysis" states: "Both the Vigileo APCO/Oximetry monitor and the DDPT have been demonstrated to be as safe and effective as the predicate devices for their intended uses." This implies that the acceptance criterion was equivalence to the predicate devices in terms of safety and effectiveness, demonstrated through functional and safety testing, not specific performance metrics like sensitivity, specificity, or accuracy compared to a ground truth.

2. Sample sized used for the test set and the data provenance

Not applicable. This submission describes functional and safety testing, not a clinical study with a test set of patient data in the context of an AI/ML device. There is no mention of patient data being used for a "test set" in the context of performance evaluation. The "functional testing" likely refers to engineering verification and validation without human subjects.

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

Not applicable. As this is not a study involving interpretation of data by experts for a ground truth, this information is not present.

4. Adjudication method for the test set

Not applicable. There is no mention of a test set requiring adjudication.

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. This device is not an AI-assisted diagnostic tool for human readers. It's a monitor measuring physiological parameters.

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

The device itself is a standalone monitor and transducer assembly for measuring physiological parameters. Its performance is inherent in its design and function. The "Functional/Safety Testing" mentioned would assess this standalone performance against engineering specifications and predicate device performance. It's not an "algorithm only" in the sense of an AI/ML model where human-in-the-loop is an option.

7. The type of ground truth used

For the "Functional/Safety Testing," the ground truth would likely be established through:

• Engineering specifications and standards: The device's measurements (e.g., arterial pressure, cardiac output, oxygen saturation) would be compared against known reference values from calibrated equipment.
• Predicate device performance: Performance metrics of the Vigileo were likely compared directly or indirectly to those of the Vigilance monitor and Metracor RODA Monitoring System (predicates for the monitor) and Phoenix Disposable Pressure Transducer (predicate for the transducer). This would involve comparisons of accuracy, precision, and reliability in controlled environments.

8. The sample size for the training set

Not applicable. This device is not an AI/ML device that requires a "training set" of data in the common sense. Its "training" is in its engineering design and manufacturing.

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

Not applicable, as there is no training set in the context of AI/ML. The "ground truth" for its development was based on established principles of physiology, medical device engineering standards, and the performance characteristics of its predicate devices.

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