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The Endophys Blood Pressure Monitor Model BPM-30 is intended to continuously provide systolic, diastolic and mean blood pressure based on the output of the Endophys PSS3 Pressure Sensing Sheath in patients undergoing therapeutic and/or diagnostic procedures involving percutaneous vascular access. The Endophys Blood Pressure Monitor Model BPM-30 monitor is additionally intended for use in transport situations within hospital environments.

The Endophys BPM-30 Blood Pressure Monitor is an electronic device that provides compatibility between a physiological fiber optic blood pressure sensor (transducer) and conventional invasive arterial blood pressure inputs to a standard physiological patient monitor. The device converts the optical transducer data to electrical signals that are interpreted by a conventional patient monitor and/or are displayed directly on the BPM-30. The BPM-30 accurately emulates a fluidic arterial blood pressure transducer and supplies electrical signals to its output that are indistinguishable from a conventional fluidic blood pressure transducer.

The BPM-30 is implemented as a self-contained unit that has a fiber optic transducer connection as an input source and communicates with a patient monitor as its output. The BPM acts to directly emulate the electrical interface characteristics of conventional fluidic blood pressure transducers (that patient monitors are compatible with) while providing much more precise blood pressure data derived from a fiber optic transducer placed within an artery. Electrically emulating a conventional fluidic transducer uniquely allows a fiber optic pressure sensor to be used with a wide variety of existing physiological patient monitors without modification of those monitors. Systolic, diastolic, and mean blood pressure values are also displayed directly on the BPM-30 every four seconds.

The BPM-30 is powered by a standard AC power adapter. The BPM-30 also has an internal battery supply that will automatically recharge and maintain operation during brief (up to 30 minutes) power interruptions. The BPM-30 is used outside of the sterile environment and has standard alerts and alarms.

The BPM-30 has an operating pressure range of -30 to 300 mmHg with an accuracy of ±1 mmHg plus ±1% of reading for pressures ≤ 50 mmHg and within ±3% of reading for pressures ≥ 50 mmHg

The provided text describes a 510(k) premarket notification for the Endophys Blood Pressure Monitor Model BPM-30. It outlines the device's description, intended use, and a comparison to a predicate device (Endophys Blood Pressure Monitor model BPM-20). While it mentions "Performance Data" and lists several types of testing conducted, it does not provide specific acceptance criteria or the reported device performance in terms of accuracy metrics against a ground truth as typically expected for proving the device meets those criteria.

Instead, the performance data section states: "The modified Endophys Blood Pressure Monitor met all specified criteria and did not raise new safety or performance questions. Based on the design verification performance the modified Endophys Blood Pressure Monitor was found to have the safety and effectiveness profile that is similar to the predicate device." This indicates that the device was tested to meet internal design specifications and regulatory standards, and its performance was deemed similar to the previously cleared predicate.

Given the information provided, I cannot construct a table of acceptance criteria and reported device performance with specific numerical accuracy values. The document focuses on regulatory compliance and substantial equivalence to a predicate device, rather than a detailed clinical performance study with defined ground truth and expert evaluation.

However, I can extract the accuracy specification for the device, which would likely form part of its inherent design acceptance criteria.

Here's an attempt to answer the request based only on the provided text, highlighting what is implicitly or explicitly stated and what is missing:

Acceptance Criteria and Device Performance for Endophys Blood Pressure Monitor Model BPM-30

The provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (Endophys Blood Pressure Monitor Model BPM-20) rather than presenting a detailed clinical study for novel performance claims. Therefore, specific numerical acceptance criteria and a detailed breakdown of reported device performance in a clinical setting against a robust ground truth (e.g., expert consensus, pathology) are not explicitly provided in the document.

The document does state the performance specifications of the device, which implicitly serve as acceptance criteria for its design and manufacturing.

1. Table of Acceptance Criteria and the Reported Device Performance

Based on the "Summary of Technical Characteristics as Compared to the Predicate Device" and "Device Description" sections, the key performance specification mentioned is accuracy:

It is important to note that the document does not provide raw data, statistical analyses, or specific clinical study results to demonstrate how these accuracy figures were met in a performance study with a test set. It merely states that the "modified Endophys Blood Pressure Monitor met all specified criteria." The "Performance Data" section lists types of testing (Software Verification, Electrical Safety, EMC, Packaging, Functional Testing) but does not detail the results of these tests in terms of the accuracy specifications.

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

• Sample Size for Test Set: Not specified. The document lists types of performance data (e.g., functional testing, electrical safety) but does not mention the sample size of a patient-based test set or a clinical study.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not specified. There is no mention of the origin or nature of data for any performance testing.

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

Not applicable/Not specified. The document does not describe a study involving expert readers or the establishment of ground truth in a clinical context (e.g., for interpretation of medical images). The testing appears to be primarily engineering verification and validation against technical specifications rather than a comparative clinical performance study.

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

Not applicable/None specified. Since there's no mention of a clinical test set requiring expert interpretation or adjudication, this information is not relevant to the provided text.

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. The device described (Blood Pressure Monitor) is not an AI-assisted diagnostic device that would typically undergo an MRMC study. It is a measurement device.

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

Yes, implicitly. The accuracy specifications (±1 mmHg plus ±1% of reading for pressures ≤ 50 mmHg, and within ±3% of reading for pressures ≥ 50 mmHg) are for the device itself, implying its standalone measurement performance. This is typically established through bench testing and calibration, which aligns with "Functional Testing" mentioned in the "Performance Data" section.

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

For a blood pressure monitor, the ground truth would typically be established by a highly accurate reference blood pressure measurement device (e.g., a calibrated pressure transducer or manometer) or a standardized pressure source in a laboratory setting. The document does not explicitly state the type of ground truth, but it would align with calibrated reference measurements used during functional and design verification testing.

8. The sample size for the training set

Not applicable/Not specified. This device is a traditional medical device, not an AI/ML device that requires a training set.

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

Not applicable. This device is not an AI/ML device that requires a training set.

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The Endophys Blood Pressure Monitor Model 651 is intended for use in a catheterization laboratory to continuously provide systolic, diastolic and mean blood pressure based on the output of the Endophys Pressure Sensing Sheath in patients undergoing therapeutic and/or diagnostic procedures involving percutaneous vascular access.

The Endophys Blood Pressure Monitor Model 651 is a blood pressure computer that computes and continuously displays systolic, diastolic and mean blood pressure values. The BPM obtains an optical signal from the Endophys Pressure Sensing Sheath, which is a standalone catheterization sheath that is inserted percutaneously during intravascular diagnostic or interventional procedures. The BPM converts the optical transducer data to electrical signals and displays blood pressure measurements.

The Endophys Blood Pressure Monitor Model 651 is powered by a standard AC power adapter. The Endophys Blood Pressure Monitor Model 651 is used outside of the sterile environment and has standard alerts and alarms.

The Endophys Blood Pressure Monitor Model 651 has an operating pressure range of 0-300 mmHg with an accuracy of ±2mmHg or ±4% of the reading, whichever is greater.

The provided document is a 510(k) premarket notification letter and summary for a Blood Pressure Monitor. It outlines the device's indications for use, technological characteristics, and performance data provided to support substantial equivalence to a predicate device.

However, the request asks for information related to a study proving a device (presumably an AI/imaging device, given the context of "human readers" and "ground truth" derived from experts) meets acceptance criteria, specifically for applications like those that might involve image analysis or disease detection.

The provided document describes a Blood Pressure Monitor, which is a physiological measurement device, not an AI-assisted diagnostic imaging device. Therefore, many of the requested criteria (e.g., sample size for test set, number of experts, adjudication method, MRMC studies, standalone algorithm performance, training set details) are not applicable to the type of device described in the input text.

The acceptance criteria and performance data for a blood pressure monitor would typically involve accuracy against a reference standard, electrical safety, electromagnetic compatibility, and functional testing, as mentioned in the document. It does not involve AI model performance metrics like sensitivity, specificity, or AUC, nor does it involve human expert ground truth establishment for image interpretation.

Given this fundamental mismatch, I can only provide information relevant to the blood pressure monitor based on the provided text, recognizing that it addresses very different types of acceptance criteria and study methodologies than those implied by the prompt's structured questions.

Based on the provided document (K160945 for the Endophys Blood Pressure Monitor, Model 651), the following is applicable:

The device is a Blood Pressure Monitor, not an AI/imaging device requiring multi-reader studies or complex ground truth establishment by experts for diagnostic interpretation. Its acceptance criteria and performance studies are focused on its accuracy in measuring blood pressure and its electrical and safety compliance.

Acceptance Criteria and Reported Device Performance (for a Blood Pressure Monitor)

Study that Proves the Device Meets Acceptance Criteria:

The document states that "The following performance data were provided in support of the substantial equivalence:"

• Functional Testing
• Electrical Safety (IEC 60601-1)
• Electromagnetic compatibility (IEC 60601-1-2)
• Safety and Essential Performance for Invasive blood pressure monitoring equipment (IEC 60601-2-34)

The conclusion states: "The modified Endophys Blood Pressure Monitor Model 651 met all specified criteria and did not raise new safety or performance questions. Based on the design verification performance the modified Endophys Blood Pressure Monitor was found to have a safety and effectiveness profile that is similar to the predicate device."

Addressing the prompt's specific questions with respect to the provided document (and highlighting non-applicability):

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

   • See table above. The document primarily focuses on technical and safety standards compliance and intrinsic accuracy, not clinical diagnostic performance metrics.

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

   • Not specified in the document for the performance testing. These are typically design verification/validation tests for electro-mechanical devices, often conducted in-house to demonstrate compliance with standards and specifications. The document does not indicate a clinical study with a patient test set size or data provenance details in the way an AI diagnostic device submission would.

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

   • Not applicable. This device measures blood pressure. "Ground truth" would be established by a primary reference standard source for blood pressure measurement, not by human experts interpreting data.

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

   • Not applicable. This pertains to expert consensus for complex diagnostic interpretation, which is not relevant to a blood pressure monitor.

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 is a standalone physiological measurement device, not an AI-assisted diagnostic tool involving human readers.

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

   • Partially applicable/Re-interpretation: The performance outlined (accuracy, electrical safety, etc.) is the "standalone" performance of the blood pressure monitor device itself. It operates as an algorithm (converting optical transducer data to electrical signals and displaying blood pressure) without human interpretive input beyond observing the displayed values. There's no separate "human-in-the-loop" aspect to its fundamental function for evaluation.

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

   • Based on standard practices for such devices: The ground truth for blood pressure measurement accuracy would typically be established by comparison to a highly accurate reference blood pressure measurement device (e.g., a manometer calibrated to a known standard, or another validated invasive blood pressure measurement system). It would not be expert consensus, pathology, or outcomes data in this context. The document does not explicitly state the reference method used.

8. The sample size for the training set

   • Not applicable. This is not a machine learning/AI device that requires a "training set" in the common understanding of the term for AI model development.

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

   • Not applicable. See point 8.

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The CORE® FM System is intended to measure blood pressure in all blood vessels, including the coronary and peripheral arteries during diagnostic and/or interventional procedures.

The CORE FM System should be used only by physicians who are thoroughly trained in cardiac or peripheral vessel catheterization procedures.

The CORE FM System provides the capability to make Fractional Flow Reserve (FFR) and Instant Wave-Free Ratio™ (iFR®) measurements. The system consists of a bedrail or cart mounted PC Console, a patient interface module (OPIM) for connecting the pressure measurement guide wire to the PC Console, and one or more Hemo Converter Box (HCB) modules for transmitting the aortic pressure and ECG signals form the hemodynamic monitoring system to the PC Console.

The provided text is a 510(k) summary for the Volcano CORE® FM Physiological Measurement System, which is a device intended to measure blood pressure, specifically Fractional Flow Reserve (FFR) and Instant Wave-Free Ratio™ (iFR®).

It does not include the detailed information, such as acceptance criteria table, sample sizes, expert qualifications, or details about comparative effectiveness studies, that would be present in a clinical performance study. The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device through various performance testing categories, but these categories generally refer to non-clinical tests (e.g., electrical safety, software verification, packaging validation, simulated use/usability) rather than a clinical study establishing the device's diagnostic performance against a ground truth.

Therefore, based solely on the provided text, I cannot describe the acceptance criteria and the study that proves the device meets the acceptance criteria in the manner requested, as the document does not contain that level of detail regarding clinical validation.

The closest relevant statement is: "The results of the performance data demonstrate equivalence to the predicate device." However, this does not detail specific clinical acceptance criteria or a clinical study design.

If the request is to complete the table and answer the questions based only on the provided text, the answer would mostly be "Information not provided in release.

Let's break down why each specific point cannot be addressed from the given text:

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

   • Information not provided: The document lists general categories of performance testing (EMC, Reliability, Electrical Safety, Design Verification, Software Verification, Packaging Validation, Simulated Use/Usability Validation) and states "The results of the performance data demonstrate equivalence to the predicate device." It does not provide specific numerical acceptance criteria (e.g., accuracy +/- X mmHg, sensitivity/specificity thresholds) or the reported numerical performance data.

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

   • Information not provided: No clinical sample sizes are mentioned. The testing described is primarily non-clinical.

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

   • Information not provided: This information would be relevant for a clinical study comparing device measurements to a "ground truth" established by experts. Since no such clinical study is detailed, this is not applicable.

4. Adjudication method for the test set:

   • Information not provided: Not applicable as no clinical test set 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:

   • Information not provided: The device is a "Physiological Measurement System" for blood pressure, FFR, and iFR, not an AI-assisted diagnostic imaging system that would typically involve human readers. Therefore, an MRMC study is not relevant to the described device.

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

   • Information not provided: The device is a measurement system. Its performance is inherent in its readings. The document states "The CORE FM takes the software code base for blood pressure measurement (FFR and iFR) from the software currently implemented on the CORE Mobile system," implying that the performance is based on the established accuracy of this measurement. However, specific standalone performance metrics (e.g., accuracy against a gold standard in a patient cohort) are not detailed.

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

   • Information not provided: Not detailed. For physiological measurements like FFR/iFR, the ground truth would typically be invasive pressure measurements. However, the document does not elaborate on how this was established or used in verification specific to the new device, beyond stating software code base inheritance.

8. The sample size for the training set:

   • Information not provided: This would be relevant for a machine learning model, but the description points to a software update based on an existing system, not necessarily a new machine learning model requiring a defined training set.

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

   • Information not provided: See point 8.

Conclusion:

The provided document, a 510(k) summary, serves the purpose of demonstrating substantial equivalence to a predicate device for regulatory clearance. It does not include a detailed clinical performance study with the specific elements requested (acceptance criteria table, sample sizes, expert involvement, MRMC studies, ground truth methodology for clinical data) that would typically be found in a paper describing the clinical validation of a novel diagnostic or AI-powered device. The "Performance Data" section lists high-level categories of testing, largely non-clinical, leading to the conclusion of "equivalence to the predicate device."

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The Endophys Blood Pressure Monitor is intended for use in a catheterization laboratory to continuously provide systolic, diastolic and mean blood pressure based on the output of the Endophys Pressure Sensing Sheath in patients undergoing therapeutic and/or diagnostic procedures involving percutaneous vascular access.

The Endophys Blood Pressure Monitor ("BPM") Model 651 is a blood pressure computer that computes and continuously displays systolic, diastolic, and mean blood pressure values. The BPM obtains an optical signal from the Endophys Pressure Sensing Sheath, which is a stand-alone catheterization sheath that is inserted percutaneously during intravascular diagnostic or interventional procedures. The BPM converts the optical transducer data to electrical signals and displays blood pressure measurements.

The provided text describes a 510(k) premarket notification for the "Endophys Blood Pressure Monitor" (K141615). However, it does not include detailed acceptance criteria or a study proving the device meets specific performance criteria in the way typically required for AI/ML device evaluations (e.g., sensitivity, specificity, accuracy against a recognized standard). This document is a regulatory approval letter and a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed performance study against specific acceptance metrics.

Therefore, I cannot populate the requested table and answer many of the questions as the information is not present in the provided text.

Based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size: Not specified. The document mentions "design verification testing" and "performance testing" but does not provide details on sample sizes for any test sets that would typically assess clinical performance.
• Data provenance: Not specified.

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

• Not applicable/Not specified. The document focuses on performance relative to predicate devices and general safety/effectiveness, not on a ground truth established by experts for a specific diagnostic task.

4. Adjudication method for the test set

• Not applicable/Not specified.

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 blood pressure monitor, not an AI/ML diagnostic aid for human readers.

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

• Not explicitly detailed as a distinct 'standalone' study for an algorithm in the AI/ML sense. However, the device itself "computes and continuously displays systolic, diastolic, and mean blood pressure values" based on an optical signal. The "design verification testing" and "performance testing" would assess this standalone measurement capability. No specific metrics are provided.

7. The type of ground truth used

• The document states the device "continuously provide[s] systolic, diastolic and mean blood pressure based on the output of the Endophys Pressure Sensing Sheath." The "ground truth" would implicitly be the established accuracy of pressure measurements against a recognized standard (e.g., an invasive catheter-based pressure measurement device or laboratory-calibrated pressure sensors), but this is not explicitly detailed with specific metrics or methodologies in the provided summary.

8. The sample size for the training set

• Not applicable/Not specified. This is not an AI/ML device in the modern sense that involves a separate training phase with a distinct dataset.

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

• Not applicable. No training set is mentioned for this type of device.

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The SphygmoCor® Cardiovascular Management System (CvMS) provides a derived ascending aortic blood pressure waveform and a range of central arterial indices. The CvMS is used with a tonometer over a radial artery calibrated with a standard cuff blood pressure measurement. It is to be used on those patients where information related to ascending aortic blood pressure is desired but in the opinion of the physician, the risks of cardiac catheterization procedure or other invasive monitoring may outweigh the benefits.

The CvMS Heart Rate Variability (HRV) option is intended for use in obtaining HRV measurements in response to controlled exercises.

The CvMS Pulse Wave Velocity (PWV) option is intended for use in obtaining PWV measurements. The PWV option is used on adult patients only.

The SphygmoCor CvMS device (un-modified device) is a computerized tool for providing a derived ascending aortic blood pressure waveform and a range of central anterial indices. The CvMS is used with a tonometer over the radial artery to capture a pressure waveform which is used to derive central pressure and is calibrated with a standard blood pressure cuff measurement. The CvMS is intended for use on those patients where information related to ascending aortic blood pressure is desired but in the opinion of the physician, the risks of cardiac catheterization procedure or other invasive monitoring may outweigh the benefits. In addition, the CvMS incorporates an option to enable users to measure Heart Rate Variability (HRV) in response to controlled exercises.

The SphygmoCor CvMS with the PWV option (modified device) is a software addition to the SphygmoCor CvMS device (K070795). This software feature provides an additional central arterial indice - Pulse Wave Velocity (PWV).

The provided document describes the SphygmoCor Cardiovascular Management System (CvMS), with a specific focus on the Pulse Wave Velocity (PWV) option.

Here's an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list quantitative acceptance criteria for the PWV measurement or a detailed performance report against such criteria. Instead, it states that "All tests confirmed the product met the acceptance criteria" and that a clinical comparison study "demonstrated similar performance between the two devices" (the modified SphygmoCor CvMS with PWV and its predicate).

While explicit acceptance criteria are not provided, the implied acceptance criteria are:

• The software verifies and validates correctly.
• The device performs similarly to the predicate device in a clinical comparison.

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

The document states, "a clinical comparison study was conducted." However, it does not specify the sample size used for this test set nor the data provenance (e.g., country of origin, retrospective or prospective nature of the study).

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

The document does not provide information on the number of experts used or their qualifications for establishing ground truth for the test set. Given that the predicate device is also a non-invasive blood pressure and cardiac monitor, the "ground truth" for the comparison would likely be the measurements provided by the predicate device itself.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the test set.

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

The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study. The clinical comparison mentioned is between two devices, not an assessment of human reader performance with and without AI assistance. Therefore, there is no effect size given for human readers improving with AI vs. without AI assistance.

6. Standalone (Algorithm Only) Performance

The document does not explicitly present a standalone (algorithm only) performance study with metrics like sensitivity, specificity, or accuracy. The focus is on the performance of the device (which includes the software/algorithm) as a whole, compared to a predicate device. The software verification and validation activities are mentioned, implying that the algorithm's functionality was tested, but not in terms of traditional standalone diagnostic performance metrics.

7. Type of Ground Truth Used

The type of ground truth for the clinical comparison study was based on the performance of a legally marketed predicate device. Specifically, the unmodified SphygmoCor CvMS (K070795) and the Vascular Profiling System VP-2000 (K013434) were used as predicates for equivalence. The study aimed to show "similar performance" to these established devices rather than against an independent, gold-standard ground truth like pathology or long-term outcomes data.

8. Sample Size for the Training Set

The document only refers to a clinical comparison study and internal design/verification activities. It does not mention a separate training set or its sample size for the development of the PWV algorithm. It describes the PWV option as a "modular software addition" that calculates PWV using existing tonometry and ECG capabilities from the predicate device. This suggests that the algorithm leverages established physiological principles rather than being a machine learning model requiring a distinct training set in the typical sense.

9. How Ground Truth for the Training Set Was Established

Since a distinct "training set" for a machine learning algorithm is not mentioned, the document does not describe how ground truth for such a set was established. The PWV calculation method is explicitly defined as "measuring the distance between the two arteries and then dividing by At" (where At is the time difference between two pressure waveforms using ECG as a timing reference), indicating a deterministic algorithmic approach rather than a learned model from a labeled dataset.

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The SphygmoCor® Cardiovascular Management System (CvMS) provides a derived ascending aortic blood pressure waveform and a range of central arterial indices. The CvMS is used with a tonometer over a radial artery calibrated with a standard cuff blood pressure measurement. It is to be used on those patients where information related to ascending aortic blood pressure is desired but in the opinion of the physician, the risks of cardiac catheterization procedure or other invasive monitoring may outweigh the benefits.

The CvMS Heart Rate Variability (HRV) option is intended for use in obtaining HRV measurements in response to controlled exercises.

The CvMS is a modified version of the SphygmoCor Px (K012487). Like its predecessor, the CvMS is a computerized tool for the assessment of a range of central vascular parameters, including blood pressure, by peripheral pulse wave detection, callbration, and analysis that can be derived from the calibrated peripheral pressure waveform. The CvMS is used with a tonometer over the radial artery, and is calibrated with a standard blood pressure cuff measurement. The CyMS is intended for use on those patients where information related to ascending aortic blood pressure is desired but in the opinion of the physician, the risks of cardiac catheterization procedure or other invasive monitoring may outweigh the benefits. In addition, the CvMS incorporates an option to enable users to measure Heart Rate Variability (HRV) in response to controlled exercises.

The CvMS is made up of three primary components: 1) a proprietary signal processing electronics module; 2) proprietary software; and 3) a Millar Micro-Tip Pulse Transducer tonometer (Millar tonometer).

One notable new feature incorporated into the CvMS is the addition of the capability to noninvasively measure Heart Rate Variability (HRV) data. The CvMS measures the variability in intervals between R waves ("R-R intervals") on a continuous beat-to-beat basis for a period of time to provide HRV data and to use standard analysis procedures to provide stable and evoked measures of HRV in response to certain controlled exercises. The CvMS is also capable of providing Central Blood Pressure (PWA) and Pulse Wave Velocity (PWV) measurements.

The CvMS system is available in three different configuration options based upon these measurement capabilities. These options allow the user to select a measurement system that suits their particular clinical needs. These configuration options include:

1. SphygmoCor Px Pulse Wave Analysis (PWA) System (Px);
2. SphygmoCor Vx Pulse Wave Velocity (PWV) System (Vx); and
3. SphygmoCor Hx Heart Rate Variability (HRV) System (Hx).

All measurements may be stored and viewed on an attached computer which is attached to the CvMS's signal processing electronics module via a standard USB cable. The patient study reports are displayed on an attached computer.

Here's a breakdown of the acceptance criteria and study information for the SphygmoCor Cardiovascular Management System (CvMS), based on the provided text:

Acceptance Criteria and Device Performance

Note: The document primarily focuses on demonstrating substantial equivalence to predicate devices and compliance with safety and performance standards, rather than specific numerical acceptance benchmarks for clinical accuracy.

Study Information

The document describes performance testing and comparison testing rather than a formal clinical study with a specific test set.

• Sample Size Used for the Test Set and Data Provenance:

  • The document states "comparison testing between the CVMS and the SphygmoCor Px demonstrated that the devices performed substantially the same." However, it does not specify the sample size for this comparison or the data provenance (e.g., country of origin, retrospective/prospective).

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

  • Not applicable/Not specified. The testing described is a comparison against a predicate device and compliance with standards, not a ground truth established by experts on a test set in the traditional sense.

• Adjudication Method for the Test Set:

  • Not applicable/Not specified.

• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

  • No. An MRMC study is not mentioned. The device is standalone, and the assessment is of its performance compared to a predicate device and safety standards, not an AI-assisted human reading task.

• Standalone Performance (Algorithm Only) Study:

  • Yes. The described "hardware and software verification and validation testing" and "comparison testing between the CVMS and the SphygmoCor Px" are essentially standalone performance assessments of the device's algorithms and functionality. The comparison confirms its performance matches the predicate device.

• Type of Ground Truth Used:

  • For the comparison testing of the derived ascending aortic blood pressure waveform and central arterial indices: The "ground truth" was the performance of the legally marketed predicate device, SphygmoCor Px (K012487).
  • For safety and electrical standards: Compliance with recognized industry standards (IEC60601-1, IEC60601-1-2, AAMI EC13:2002) served as the "ground truth" for meeting those requirements.

• Sample Size for the Training Set:

  • Not applicable/Not specified. This device is a modified version of an existing system, and the description focuses on verification and validation of the modified system, not the training of a new AI algorithm.

• How the Ground Truth for the Training Set Was Established:

  • Not applicable/Not specified. (See above)

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The monitoring system ARGUS PB-2200 is for the monitoring of vital parameters such as:

Invasive blood pressure: systolic, diastolic and mean pressure
s and controller Brings and/or sidestream Invasive blood pressure. Systems, main and/or sidestream FIO2

lt will extend the functionality of the existing Argus PB-1000 system (K0122Z6).
The function and the promoter her PB-1000 and the visualisation unit AR It will extend the functionality of the existing Algust PB-1000 (PB-100) (PB-100)
The system comprises the parameter box PB-1000 and the visualisation unit ARGUS
(PBS) and th

The system compilses the parcined via a serial interface. PRO. The two units are connected via a serial intenated and calculated in the PB-2200. This All vital parameters and evaluations are registered and calouaced manager generally used
data is then transmitted to the visualisation unit ARGUS PRO or another generally us data is then transmitted to the visuallsation und monitored on the ARGUS PRO.
PC via the serial interface. All data can be shown and monitored on the ARGUS PRO. PC via the serial interface. All data can be snown and monecessed power input (RS
The PB-2200 is operated using an internal battery and an external power input (RS
e and the The PB-2200 is operated using an internal battery alle an and the manate from the 232/12V), which is, like the data transmission, completely sop
visualisation unit. The ARGUS PRO is powered via the normal mains connection

230V/110V.
The system is intended for use in the intensive care unit, in the recovery room, in the The system is intended for ass internal transports.

The system comprises the Parameter Box PB-1000 and the Visualisation Unit AR-GUS PRO. The two units are connected via a serial interface. All vital parameters and evaluations are registered and calculated in the PB-1000. This data is then transmitted to the visualisation unit ARGUS PRO or another generally used PC via the serial interface. All data can be shown and monitored on the ARGUS PRO. The PB-1000 operated using an internal battery and an external power input (RS 232/12V), which is, like the data transmission, completely separate from the visualisation unit. The ARGUS PRO is powered via the normal mains connection 230V/110V.

The provided 510(k) summary for the ARGUS PB-2200 Monitoring System indicates that no specific acceptance criteria or a dedicated study proving performance against such criteria were explicitly presented in the document. Instead, the submission relies on demonstrating substantial equivalence to a predicate device (ARGUS PB-1000 System, K012226) by showing that the ARGUS PB-2200 meets or exceeds various established safety and electromagnetic compatibility standards.

The key takeaway is that for this device, the "acceptance criteria" are the compliance with recognized medical device standards, and the "study" is the non-clinical testing performed against those standards.

Here's a breakdown of the requested information based on the provided text:

1. A table of acceptance criteria and the 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)

The document relates to non-clinical testing of the device against standards. There is no mention of a "test set" in the context of patient data or clinical performance. Therefore, sample size for a test set is not applicable (N/A) for this type of submission. The data provenance is related to in-house or contracted laboratory testing for compliance with international standards, likely performed in Switzerland (country of origin of SCHILLER AG). The testing is prospective in the sense that the device was actively tested against the standards.

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. This submission focuses on engineering and safety standards compliance, not on clinical performance evaluated by medical experts establishing ground truth from patient data.

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

Not applicable. There was no "test set" in the context of clinical data 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

No MRMC comparative effectiveness study was done. This device is a vital signs monitor, not an AI-assisted diagnostic tool for interpretation by human readers.

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

The device is a monitoring system for vital parameters. Its "performance" is its ability to accurately measure and display these parameters and comply with safety standards. The non-clinical tests described are essentially "standalone" performance evaluations against specified engineering and safety criteria. There is no mention of an algorithm in the sense of a diagnostic or interpretive AI, therefore, no standalone algorithm performance study as typically understood in AI/ML medical devices.

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

For the non-clinical tests, the "ground truth" is established by the defined parameters and tolerances within the referenced international standards (e.g., specific voltage levels for ESD, frequency ranges for emitted radiation, and safety requirements for medical electrical equipment). The device's performance is compared directly against these established standard requirements.

8. The sample size for the training set

The document does not describe a "training set" as it is commonly understood for AI/ML models. This device is a hardware monitoring system, not an AI/ML product that undergoes a training phase with a dataset.

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

Not applicable. No training set for an AI/ML model was used or described.

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The APB for Windows is a software package to be used by a trained physician or health care provider to load, download, review and print data from the Mobile-O-Graph blood pressure monitor. The software will store and playback systolic, diastolic pressures as well as patients heart rates to be reviewed by a trained physician.

The ABP for Windows Software is a software designed to be used in conjunction with I.E.M's Mobile-O-Graph Blood Pressure Monitor, Model ABP Control (K964235). The software will allow the user to program the Mobile-O-Graph using the software by inputting patient identification, protocols and setting recorder clock. The software will have the ability to download the data recorded from the Mobile-O-Graph to the computer to be reviewed by a trained professional. The software will allow the data to be printed and e-mailed in PDF or HTML format if desired. The ABP for Windows does not perform any diagnosis or provide any interpretation of data, it can only display and print the downloaded data such as systolic, diastolic, heart rates and mean arterial blood pressure in tabular or graphical form which was recorded by the Mobile-O-Graph. The physician will be able to review, edit and print the data collected. The ABP for Windows will provide information such as when patient events occurred , errors during recording and when day and night were marked on the Mobile-O-Graph. The software ABP for windows will be shown to be substantially equivalent to the software which is provided by I.E.M.'s Mobile-O-Graph Blood Pressure Monitor, Model ABP Control.

The provided document is a 510(k) premarket notification for the "ABP for Windows" software, which is designed to be used with the Mobile-O-Graph Blood Pressure Monitor (K964235). The submission focuses on demonstrating substantial equivalence to the predicate device's software.

Based on the provided text, the ABP for Windows software does not perform any diagnosis or provide any interpretation of data. It is purely for displaying, storing, and printing data recorded by the Mobile-O-Graph, which is then reviewed by a trained professional. Therefore, the concept of "acceptance criteria" related to diagnostic performance metrics (like sensitivity, specificity, AUC) and a "study that proves the device meets the acceptance criteria" in the traditional sense of AI/CADe devices for interpretation is not applicable here.

The "study" described is a comparison of technological characteristics to demonstrate substantial equivalence, rather than a clinical performance study.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

As the device is software for data management (displaying and printing) and not for diagnostic interpretation, the acceptance criteria are related to its functional compatibility with the predicate device's software and its ability to process and display the blood pressure data accurately.

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

Not applicable. This is not a study involving a "test set" of patient data for diagnostic performance evaluation. The "tests" mentioned are for software safety and efficacy, likely functional testing and compatibility, not based on patient data provenance.

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

Not applicable. There is no diagnostic "ground truth" establishment described, as the software does not perform diagnosis or interpretation.

4. Adjudication Method for the Test Set

Not applicable. No "test set" requiring adjudication is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

No. This type of study is not relevant for this software's intended use, which is data management, not diagnostic assistance.

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

Yes, in a conceptual sense related to software functionality. The comparison of technological characteristics against the predicate software evaluates the "algorithm only" in terms of its ability to manage and display data, rather than interpret it. The software's performance is standalone in that it processes and presents data without human intervention in the data processing step, but human review is required for interpretation.

7. The type of ground truth used

Not applicable for diagnostic performance evaluation. For functional equivalence, the "ground truth" would be the demonstrated functionality of the predicate device's software and the specified technical requirements for the new software.

8. The sample size for the training set

Not applicable. This software does not use machine learning or AI models that require a "training set" of data.

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

Not applicable. No training set is involved.

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The RadiAnalyzer is intended for use under the direction of a licensed physician to calculate, display and record vascular data. Data is acquired from a PressureWire Sensor and an External Pressure Transducer (EPT). The information is displayed on the integrated screen and/or transferred to a cardiac monitor. Data includes: systolic, diastolic and mean blood pressure, heart rate, and Fractional Flow Reserve (FFR). The RadiAnalyzer is intended for use in catheterization and related cardiovascular specially laboratories.

The RadiAnalyzer™ is a blood pressure computer, to be used as a diagnostic tool when the diagnosis is based on patient blood pressures. The device comprises a graphic display that presents real-time pressure curves as well as numerical values, and is operated via a remote control. The device has two entries for pressure signals, one for a PressureWire™ Sensor, and another for an External Pressure Transducer (EPT) and corresponding outlets for connection to a cardiac monitor. The RadiAnalyzer™ could also be connected to a RadiAnalyzer™-Printer or to a PC with the RadiView™ software installed.

This submission, KD13943, is a 510(k) summary for the RadiAnalyzer™ System, a blood pressure computer. The manufacturer, RADI Medical Systems AB, is seeking clearance for a device that is "identical to the predicate devices" in its mechanical, electrical, and signal properties, with the only stated new feature being a "new PC-software for digital transfer of RadiAnalyzer™ physiological recordings."

Given the nature of a 510(k) submission for a device largely identical to a predicate and the provided document content, it is highly unlikely that a comprehensive standalone study with extensive performance metrics, ground truth establishment, or comparative effectiveness studies (MRMC) were conducted or are detailed in this summary. 510(k) submissions typically focus on demonstrating substantial equivalence to a legally marketed predicate device rather than conducting new, elaborate clinical performance studies unless the device introduces significant new technology, intended uses, or raises new questions of safety and effectiveness. This case appears to be a modification of an existing cleared device (K002067).

Therefore, the information regarding acceptance criteria and performance studies will be limited to what can be inferred or directly stated in the provided text, which primarily focuses on substantial equivalence based on technical characteristics rather than a new performance validation study as might be seen for novel AI algorithms.

Here's an analysis based on the provided text, acknowledging the limitations inherent in a 510(k) summary for a substantially equivalent device:

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, there are no explicit "acceptance criteria" or a detailed "reported device performance" table as one might expect for a novel device or AI algorithm. The core of this 510(k) is to demonstrate substantial equivalence to its predicate device (RadiAnalyzer™ System 510(k) # K002067). The key "performance" criterion for this submission is that the device's technical characteristics are identical to the predicate, apart from the new software component.

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

The provided text does not contain any information about a specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective). This is consistent with a 510(k) submission largely based on substantial equivalence to an existing device rather than a new performance study. The "test set" for this type of submission would primarily involve engineering verification and validation that the new device (or its modified component, the software) continues to function as intended and comparably to the predicate.

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

There is no mention of expert involvement for establishing ground truth as there is no specific performance test set described in the provided document. For a blood pressure computer, the "ground truth" for its core function (measuring and calculating pressures and FFR) would typically be the physical fluid dynamics and pressure readings themselves, validated through bench testing and, for the predicate, potentially prior clinical studies to correlate with clinical outcomes.

4. Adjudication Method for the Test Set

As no specific test set or clinical study is detailed for this 510(k) submission, there is no information regarding an adjudication method.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs without AI Assistance

No, an MRMC comparative effectiveness study was not conducted or described in this document. This device is a blood pressure computer that directly measures and calculates physiological parameters (BP, HR, FFR). It does not involve "human readers" interpreting images or data in a way that would lend itself to an MRMC study or "AI assistance" in the sense of an interpretive algorithm. Its function is to provide raw and calculated numerical data.

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

The device itself, the RadiAnalyzer, is a standalone instrument in that it performs calculations (Fractional Flow Reserve, systolic, diastolic, mean blood pressure, heart rate) based on sensor inputs without human intervention in the calculation process. However, the term "standalone performance" often refers to the performance of an algorithm in generating a diagnostic output without human interpretation or modification.

Since the device's function is to directly measure and calculate established physiological parameters from sensor data, its "standalone performance" is embedded in its engineering validation for accuracy, precision, and consistency of these measurements and calculations. The 510(k) relies on the fact that these core mechanical, electrical, and signal properties are identical to the predicate device. Therefore, the standalone performance, as recognized and cleared in the predicate device, is considered to be maintained. There is no new standalone algorithm described that would warrant a separate performance study of its own.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Given that this is a blood pressure computer measuring physical values, the ground truth for its core functions (blood pressure, heart rate, FFR calculations) would primarily be based on:

• Physical Reference Measurements: Comparison to highly accurate reference pressure transducers and flow models during design and verification.
• Physiological Principles: The FFR calculation itself is based on established physiological principles and equations.
• Prior Clinical Validation (of the predicate): The predicate device would have undergone validation to ensure its measurements correlate with clinical understanding and possibly patient outcomes, although specific details are not in this summary.

No human expert consensus, pathology, or outcomes data is explicitly mentioned as being used for ground truth in this specific 510(k) submission.

8. The Sample Size for the Training Set

There is no mention of a training set or its sample size. This device is not an AI/ML algorithm that requires training data in the typical sense. It is a hardware and software system for measuring and calculating physiological parameters.

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

As there is no training set described, there is no information on how ground truth for a training set was established.

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IBP: The ZOLL M Series IBP option is indicated for measuring arterial, venous, and intracranial pressures using invasive transducers with 5uV/V/mmHg sensitivity for use with resting patients in critical care and transport. The M Series IBP option is intended for use with adult and pediatric patients only. TEMPERATURE: The ZOLL M Series Temperature option is indicated for measuring temperature of adult and pediatric patients using YSI 400 compatible temperature sensors.

ZOLL M Series IBP and Temperature Option

I am sorry, but the provided text from the FDA 510(k) summary for the ZOLL M Series IBP and Temperature Options does not contain the acceptance criteria or a study detailing the device's performance against those criteria.

The document is a clearance letter from the FDA, confirming that the device is substantially equivalent to legally marketed predicate devices. It outlines the indications for use and contraindications but does not include any technical specifications, performance metrics, or study results related to sensitivity, specificity, accuracy, or other performance characteristics.

Therefore, I cannot provide the requested information in the table format or answer the questions about sample size, expert ground truth, adjudication methods, MRMC studies, standalone performance, or training set details. This information would typically be found in the more detailed 510(k) submission itself, which is not provided here.

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