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The Quantum Mini Ventilation Module is intended to provide independently regulated O2 outputs for a controlled flow of O2 into the ECC circuit. The Quantum Mini Ventilation Module is an accessory that works with the Quantum workstation.

The following parameters are provided by the Quantum Mini Ventilation Module:

· Control of gas flow (02)

· Extracorporeal gas flow measurements for O2

The Quantum Mini Ventilation Module is only to be used by an experienced and trained clinician. It is not intended to be used by a patient or other untrained personnel.

The Quantum Mini Ventilation Module is a gas control unit that is intended to provide independently regulated oxygen outputs for a controlled flow for procedures involving an extracorporeal circuit.

The Quantum Mini Ventilation Module provides a simplified patient ventilation capability. The device consists of a single O2 input port that receives oxygen from the hospital infrastructure and two (2) oxygen outputs that are designed to provide O2 sweep and pO2 Reg.

The device interfaces with and is powered by any model of the Quantum workstation. The Quantum Mini Ventilation Module does not contain any user interface; instead, all measurements are displayed on the Quantum workstation.

This is a summary of the acceptance criteria and study information for the Quantum Mini Ventilation Module, based on the provided FDA 510(k) summary.

Note: This device is a cardiopulmonary bypass gas control unit, which typically involves engineering performance testing rather than studies involving AI algorithms or human reader performance with medical images. Therefore, many of the requested fields related to AI, medical image analysis, and expert consensus for ground truth are not applicable to this type of device.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: Not applicable in the context of a "test set" for an AI algorithm or medical image data. The testing described is engineering performance testing of hardware and software.
• Data Provenance: Not applicable. The testing is internal engineering and software validation.

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

• Not applicable. This is not an AI/image-based device where expert consensus on "ground truth" for a test set is typically established.

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

• Not applicable. This is not an AI/image-based device requiring an adjudication method for a test set.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No. This is a medical device for controlling gas flow in cardiopulmonary bypass, not an AI-assisted diagnostic tool.

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

• Not applicable. This device is a hardware module with embedded software for control and measurement, not a standalone AI algorithm. It operates under the control of an experienced and trained clinician via the Quantum workstation.

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

• Ground Truth Type: For engineering performance testing, the "ground truth" refers to established engineering standards, specifications, and validated measurement techniques ensuring the device functions as designed and meets regulatory requirements for safety and performance (e.g., accurate flow measurements against calibrated instruments, electrical safety compliance, EMC compliance).

8. The sample size for the training set:

• Not applicable. This device does not use a "training set" in the machine learning sense. Software development involves verification and validation against requirements and design specifications.

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

• Not applicable. This device does not have a "training set" in the machine learning sense.

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The Quantum Ventilation Module is intended for the continuous monitoring of critical clinical parameters during procedures that require extracorporeal circulation. The Quantum Ventilation Module is an accessory that only works with the Quantum Workstation. Parameters provided by the Quantum Ventilation Module include:

• Measurement of up to three blood flow channels and arterial and venous flow differential and gas bubbles
• Extracorporeal gas flow measurements that includes O2 & CO2 and calculated CO2 removal
• Predicted PO2 and PCO2
• Up to three temperature channels
• Up to three circuit pressure channels
• Reservoir level indication
• Two channels of vacuum
• Blend and control gas flow (air/O2/CO2)

The Quantum Ventilation Module is to only be used by an experienced and trained clinician. The device is not intended to be used by the patient or other untrained personnel.

The Quantum Ventilation Module is an on-line, cardiopulmonary bypass, blood gas monitor that is used for extracorporeal monitoring of blood oxygen (arterial and venous) saturation, hematocrit, and hemoglobin levels. The Quantum Ventilation Module provides gas blending and continuous non-invasive monitoring of critical clinical parameters in extracorporeal circuits used in cardiopulmonary bypass (CPB) or extracorporeal membrane oxygenation (ECMO) procedures. The Quantum Ventilation Module is an accessory to the Quantum Workstation. When paired with the Quantum Workstation, the combination of the Quantum Workstation and Quantum Ventilation Module (QVM2) is known as the Quantum Ventilation System.

The Quantum Ventilation Module performs five functions:

• 1. Provides measurements from embedded and attached sensors to monitor gases into and out of a blood oxygenator.
• 2. Provides measurements from attached sensors for blood flow, bubble detection, pressure, level, and temperature to monitor an extracorporeal blood loop.
• 3. Provides gas blending to ensure the precision delivery of FiO2, CO2 and sweep flow rates.
• 4. Provides regulation of vacuum supply to provide two channels of vacuum.
• 5. Sends these physiological measurements to the Quantum Workstation for display to the user.

The Quantum Ventilation Module, with its attached sensors, can measure flow, pressure, reservoir level, temperature and gas diagnostics, in addition to performing electronic gas blending of up to three gases and built-in vacuum management for the removal of waste anesthetic gas. The primary interface for controlling and displaying measurements is the Quantum Workstation; however, the Quantum Ventilation Module also contains a touchscreen display with control knobs. The Quantum Ventilation Module only works with the Quantum Workstation.

This FDA 510(k) summary for the Spectrum Medical Quantum Ventilation Module (K202733) indicates that it is a Class II device intended for the continuous monitoring of critical clinical parameters during extracorporeal circulation. The submission claims substantial equivalence to a legally marketed predicate device, Spectrum Medical Ltd.'s Quantum Ventilation Module (K181942).

Here's an analysis of the requested information based on the provided text:

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

The document does not explicitly state acceptance criteria in a quantitative table format for specific performance metrics (e.g., accuracy, precision for flow, pressure, temperature). Instead, it states that the proposed Quantum Ventilation Module (QVM2) has "equivalent sensor performance" to the predicate device.

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

The document states that "No animal testing was submitted" and "No clinical data were submitted" to support the substantial equivalence. The non-clinical testing mentioned (electrical safety, EMC, hardware, software) refers to engineering verification and validation, not a test set of clinical or animal samples. Therefore, information regarding sample size and data provenance in the context of clinical or animal testing is not applicable here as such studies were not performed.

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

Not applicable. Since no clinical or animal testing with a "test set" and "ground truth" established by experts was performed or submitted, this information is not provided. The assessment was based on non-clinical engineering testing and comparison to a predicate device.

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

Not applicable. No test set requiring expert adjudication was used.

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 medical monitoring and control unit, not an AI-assisted diagnostic imaging or interpretation device. Therefore, an MRMC study is not relevant to its type of performance evaluation.

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

Not applicable. This device is a hardware and software system for continuous monitoring and control during extracorporeal circulation, not a standalone algorithm. Its performance is evaluated through engineering verification and validation of its sensors and control mechanisms.

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

The concept of "ground truth" derived from expert consensus, pathology, or outcomes data is typically associated with diagnostic or prognostic devices that interpret patient data. For this device, the "ground truth" for its performance evaluation would be based on engineering standards, calibrated reference instruments, and defined physical parameters. For example, when testing flow measurement, the "ground truth" would be established by a known, accurately measured flow rate from a reference system.

8. The sample size for the training set

Not applicable. This device is not an AI/ML device that requires a "training set" in the conventional sense for model development. Its software verification and validation would involve testing against requirements, but not training data for a learning algorithm.

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

Not applicable, as there is no "training set" for an AI/ML model for this device.

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The Quantum Ventilation Module is intended for the continuous monitoring of critical clinical parameters during procedures that require extracorporeal circulation. The Quantum Ventilation Module is an accessory that only works with the Quantum Workstation. Parameters provided by the Quantum Ventilation Module include:

• · Measurement of up to three blood flow channels and arterial and venous flow differential
• Indication of gas bubbles
• · Extracorporeal gas flow measurements (02, CO2, gas flow, and CO2 removal)
• · Predicted PO2 and PCO2
• · Temperature
• · Up to three circuit pressure channels
• · Reservoir level indication
• Two channels of vacuum
• · Blend and control gas flow (air/O2/CO2)

The Quantum Ventilation Module is to only be used by an experienced and trained clinician. The device is not intended to be used by the patient or other untrained personnel.

The Quantum Ventilation Module provides gas blending and continuous non-invasive monitoring of critical clinical parameters in extracorporeal circuits used in cardiopulmonary bypass (CPB) or extracorporeal membrane oxygenation (ECMO) procedures. The Quantum Ventilation Module is an accessory to the Quantum Workstation or can be used in place of the Quantum Diagnostic Module as part of the Quantum Pump Console. When paired with the Quantum Workstation, the combination of the Quantum Workstation and Quantum Ventilation Module is known as the Quantum Ventilation System.

The Quantum Ventilation Module performs five functions:

• 1. Provides measurements from embedded and attached sensors to monitor gases into and out of a blood oxygenator.
• 2. Provides measurements from attached sensors for blood flow, bubble detection, pressure, level and temperature to monitor an extracorporeal blood loop.
• 3. Provides gas blending to ensure the precision delivery of FiO₂ (21 to 100%), CO₂ and sweep flow rates.
• 4. Provides regulation of vacuum supply to provide two channels of vacuum. One is flow-regulated to remove waste anesthesia gas, the other pressure-regulated for applications including Vacuum-Assisted Venous Drainage (VAVD) and hemoconcentration.
• 5. Sends these physiological measurements to the Quantum Workstation for display to the user.

The Quantum Ventilation Module, with its attached sensors, can measure flow, pressure, reservoir level, temperature and gas diagnostics, in addition to performing electronic gas blending of up to three gases and built-in vacuum management for the removal of waste anesthetic gas. The primary interface for controlling and displaying measurements is the Quantum Workstation: however, the Quantum Ventilation Module also contains a display with control knobs. The Quantum Ventilation Module only works with the Quantum Workstation.

The provided document is a 510(k) Premarket Notification for a medical device called the Quantum Ventilation Module. This type of submission is for demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving safety and effectiveness through extensive clinical trials as would be required for a Premarket Approval (PMA) application.

Therefore, the document does not describe a study involving an AI algorithm or meeting the typical acceptance criteria for AI/ML device performance. Instead, it focuses on non-clinical performance data to demonstrate the device's functionality and safety as a medical instrument.

Given this context, I will address the questions to the best of what can be inferred from the provided text, noting where the information is absent due to the nature of a 510(k) submission for a non-AI hardware device.

Acceptance Criteria and Device Performance (Based on Non-Clinical Testing for a Hardware Device)

The document primarily discusses non-clinical performance data, which are typically tests to ensure the device performs as intended and is safe. The "acceptance criteria" here are implied by the successful completion of these tests.

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

Since this is a hardware device (Ventilation Module) and not an AI algorithm, the acceptance criteria are not in terms of common AI metrics like sensitivity, specificity, or AUC, nor is there comparative effectiveness data against human readers. The criteria are related to the device's physical and electronic performance, along with its software validation. The document states:

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

This information is not applicable in the context of an "AI test set" here. The "test set" would refer to the physical units of the device subjected to non-clinical tests. The tests performed ("Electrical safety", "Electromagnetic compatibility", "Electrosurgery interference", "Hardware testing of printed circuit boards", "Software verification and validation", "Usability validation") are typically laboratory-based engineering and software validation tests. The document does not specify the number of units tested, the conditions, or the specific "data provenance" (e.g., country of origin) beyond the manufacturer being in the UK. These are not data-driven performance studies on patient cohorts.

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

This is not applicable as this is a hardware device. Ground truth, in the context of AI, refers to annotated data. For a hardware device, "ground truth" might refer to established measurement standards or known physical properties used for calibration and validation of sensors. The document does not specify the number or qualifications of experts involved in these engineering validation processes.

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

Not applicable. Adjudication methods like 2+1 or 3+1 are used for establishing consensus among human readers for image labeling or clinical decision-making ground truth in AI studies. For hardware testing, performance is measured against engineering specifications and industry standards, not through expert adjudication in this manner.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No. This is a hardware medical device, not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study is not relevant, and the concept of human readers improving with AI assistance does not apply.

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

This refers to an AI algorithm's performance. The Quantum Ventilation Module is a hardware device with embedded software, but it's not an AI algorithm that makes diagnostic decisions or interpretations in the way this question implies. Its performance is the measurement and control capabilities of the instrument itself.

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

Not applicable. For a hardware device, the "ground truth" for non-clinical performance validation would be derived from:

• Engineering specifications and design documents.
• International and national standards for electrical safety, EMC, and medical device performance (e.g., IEC standards).
• Calibration standards for sensors (e.g., precision gas mixes, flow simulators, temperature baths, pressure gauges).
• Bench testing and physical measurements.

8. The sample size for the training set

Not applicable. This device is not an AI/ML model trained on a dataset. It's a hardware device with firmware.

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

Not applicable. As there is no "training set" in the AI sense, this question is not relevant. The "ground truth" for developing the device's functionality would stem from engineering principles, clinical requirements for extracorporeal circulation, and established medical device design practices.

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The AtriClip Gillinov-Cosgrove LAA Clip is indicated for the left atrial appendage, under direct visualization, in conjunction with other open cardiac surgical procedures.

The AtriClip Gillinov Cosgrove LAA Clip is a single use, sterile, self-closing, implantable Clip to be deployed with a Reusable Clip Applier. When closed, the Clip applies uniform pressure over the length of the Clip to ensure consistent, reproducible, and secure occlusion of the left atrial appendage (LAA). The Clip is available in the following lengths to accommodate different sizes of LAA: 35 mm, 40 mm, 45 mm, and 50 mm. This Special 510(k) does not include any changes to the Clip.

This Special 510(k) includes modifications to package the Clip individually to be loaded on a Reusable Clip Applier.

This 510(k) summary document describes a modification to an existing device, the AtriClip Gillinov-Cosgrove LAA Clip. The core of the submission is to demonstrate substantial equivalence to the previously cleared device (K093679 and K122276), asserting that the modifications do not affect performance.

Therefore, the submission does not contain a new study that defines and tests against acceptance criteria for device performance as a standalone product. Instead, it relies on the previous clearances and tests demonstrating that the new packaging does not degrade the previously established performance.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Not directly applicable in the format of specific functional performance criteria for the device itself.
The acceptance criteria in this specific 510(k) are focused on the impact of packaging modifications.

• Acceptance Criteria: The new individual packaging must adequately protect the device during shipment.
• Reported Device Performance: "The Clip was tested to confirm new packaging of the Clip adequately protects the device during shipment." (The document states testing was done, implying it met the criteria, but doesn't provide specific test results or metrics here).

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

• Test Set Sample Size: Not specified for the packaging test.
• Data Provenance: The testing for the packaging modification would have been internal AtriCure, Inc. testing, likely prospective for the new packaging configuration.

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

Not applicable. The "ground truth" for packaging protection is determined by engineering and performance testing (e.g., integrity, sterility, functional checks after simulated shipping), not expert consensus in a clinical sense.

4. Adjudication method for the test set

Not applicable. Adjudication methods like 2+1 or 3+1 typically refer to expert review processes for clinical data, which is not described for this packaging modification.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance

Not applicable. This is a medical device for occlusion of the left atrial appendage, not an AI or imaging diagnostic tool.

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

Not applicable. This is a physical implantable medical device.

7. The type of ground truth used

For the packaging modification, the "ground truth" would be the successful completion of specified packaging validation tests (e.g., sterile barrier integrity, product integrity after shipping simulation, etc.).

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device requiring a training set.

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

Not applicable.

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The document states: "The Clip was tested to confirm new packaging of the Clip adequately protects the device during shipment. Complete Design Control testing for the Clip was previously included in the original 510(k) K093679."

This indicates that:

• A specific test (or series of tests) was conducted to evaluate the individual packaging's ability to protect the device during transit. The details of this test (e.g., specific parameters, number of units tested, acceptance criteria for "adequately protects") are not provided in this summary but would have been part of the full 510(k) submission.
• For the performance of the Clip itself (e.g., sealing, occlusion effectiveness, biocompatibility), the submission relies on the comprehensive design control testing and evaluations performed for the original 510(k) K093679. The current submission asserts "there is no change to indications for use/intended use, the implant Gillinov-Cosgrove Clip, or the basic design of the Clip and Clip Applier configuration," and "The modifications do not affect the ability of the Clip to be successfully deployment on the LAA." Essentially, the previous studies prove the device meets its core acceptance criteria, and this submission demonstrates the change does not compromise those criteria.

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The Stöckert Gas Blenders (2L, 5L, and 10L) are intended to enable qualified personnel to set monitor and control gas flows of medical grade gases (air/02/CO2) during cardiopulmonary bypass. The Stockert Gas Blenders are used as components of or optional accessories to the Stöckert S5 System (or any compatible Sorin system using the S5 firmware versions of 3.0 or greater) for periods of six hours or less.

The Stöckert Gas Blender Base Unit is 200 mm wide, 185 mm high, and 270 mm deep and it weighs 2.5 kg. It can be used either from a suitable horizontal surface such as a table or cart or it can be mounted on one of the masts (using the mast holder). It is attached to HLM console with the supplied 24V/CAN connector. This connection provides both power and communication between the Stöckert Gas Blender and the System Display Panel of the HLM. The Stöckert Gas Blenders are designed to provide a maximum mixed gas flow rate of 2L/min, 5L/min or 10 L/min depending on the model used to allow the perfusionist to purge the oxygenator with gas during the priming process. The front panel is the user interface and includes the on/off key, displays and controls. The rear panel houses the three inlet gas connections, the gas mix outlet, and the 24V/CAN connector. Gas line connectors are fast release connectors, consisting of a male connector (installed on the tubing) and a coupler socket (on the housing of the Gas Blender). Both sets (male and female) of connectors are labeled with the respective gas for which they are intended to be used. The Stöckert Gas Blenders enable the qualified perfusionists who are managing the cardiopulmonary bypass circuit using a Stöckert S5 or Sorin C5 System to precisely set, monitor and control the gas flows required for the oxygenation of the patient's blood during extracorporeal circulation. The supply sources for air, O2 and CO2 are connected to the rear inlets of the Stöckert Gas Blender and the gas mixture outlet is connected to the oxygenator (not supplied). The Stöckert Gas Blenders are optional accessories to and designed to be operated with the Stöckert S5 System/Sorin C5 System. They cannot be operated independently from the heart lung machine console. The values for total gas flow (air + O2), FiO2 and CO2 can be adjusted independently without affecting the remaining two values. Gas flow is displayed at both the Stöckert Gas Blender base unit and the remote display module situated in the Stöckert S5 System/Sorin C5 System "control desk" or "System Panel." Set values and actual values are continuously monitored and any discrepancy between them causes both optical and acoustic alarms. If desired, the perfusionist may set alarm limits at the remote display module to monitor the blood flow/gas flow ratio for the arterial pump.

The provided text describes the Stöckert Gas Blender and its FDA 510(k) submission. However, it does not include detailed information about acceptance criteria or a study that specifically proves the device meets those criteria in the format requested.

The document is a 510(k) summary for a medical device (Stöckert Gas Blender). For this type of submission, substantial equivalence to a predicate device is the key, not necessarily a detailed clinical study demonstrating specific performance metrics against pre-defined acceptance criteria in the way a new drug or a novel AI diagnostic might.

Based only on the provided text, here's what can be extracted and what is missing:

1. Table of acceptance criteria and reported device performance:

This information is not provided in the document. The document states that "Design verification and validation testing presented in the 510(k) included electrical/safety testing (IEC60601-1), EMI/EMC testing (IEC60601-1-2), and Functional Acceptance testing, and design validation testing (internal and external)." However, it does not list the specific acceptance criteria for these tests (e.g., accuracy of gas flow, precision of mixture) or the numerical performance results of the device against those criteria.

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

This information is not provided. The document mentions general "testing" but no specific test sets or their characteristics.

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

This information is not applicable/not provided. This device is a gas blender for heart-lung machines, not an AI diagnostic that requires expert interpretation for ground truth. Its performance would be validated through engineering and functional testing.

4. Adjudication method for the test set:

This information is not applicable/not provided. (See point 3).

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

No. The document explicitly states: "No formal clinical testing was provided as the basis for substantial equivalence or is required." Therefore, no MRMC study was conducted or reported here.

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

This concept is not applicable to this device. The Stöckert Gas Blender is a physical medical device that blends gases, not an algorithm. Its "standalone performance" would be its functional performance, which is generally verified through engineering tests, but specific details are not provided in this summary.

7. The type of ground truth used:

This information is not explicitly stated or applicable in the traditional sense of clinical ground truth (e.g., pathology). For a physical device like a gas blender, "ground truth" would be established by reference standards, calibrated measurement equipment, and compliance with engineering specifications. The document mentions "prospectively defined design and performance specifications," which would form this basis.

8. The sample size for the training set:

This information is not applicable/not provided. As this is a physical device and not an AI/machine learning algorithm, there is no "training set."

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

This information is not applicable/not provided (see point 8).

In summary:

The provided document is a 510(k) summary for a medical device focused on demonstrating substantial equivalence to a predicate device. It confirms that engineering, safety, and functional testing were performed but does not delve into the specific acceptance criteria or the detailed results of those tests, nor does it involve clinical studies or AI-related performance metrics.

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The Cardica® PAS-Port® Proximal Anastomosis System is intended to create the aortic anastomosis of aortic autologous vein grafts.

The Cardica® PAS-Port® Proximal Anastomosis System is a mechanical device used to facilitate an aortic vein graft anastomosis. The connector replaces sutures to create a secure, patent and reproducible anastomosis. The PAS-Port® Proximal Anastomosis System consists of a connector and a delivery system.

The provided text does not contain information about acceptance criteria or a study proving that the device meets those criteria. This is a 510(k) summary for a medical device (PAS-Port® Proximal Anastomosis System) seeking substantial equivalence to a predicate device.

The document focuses on:

• Device identification and categorization: Trade name, common name, classification, regulation number.
• Predicate device: K081225.
• Device description: How it works for aortic vein graft anastomosis.
• Indications for Use: To create the aortic anastomosis of aortic autologous vein grafts.
• Comparison to predicate device: Stating substantial equivalence and similarity in indications for use and technological characteristics.
• Device Testing Results and Conclusion: A general statement that in vitro and in vivo testing was performed to ensure substantial equivalence, safety, and effectiveness. However, specific acceptance criteria, study designs, or actual performance metrics are not detailed.
• FDA Clearance Letter: Confirming substantial equivalence based on the provided information.

Therefore, I cannot provide the requested table or answer the specific questions about sample size, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth details, or training set information. These details are typically part of a more extensive submission package to the FDA, not usually included in the public 510(k) summary.

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The Cardica® C-Port® xA Anastomosis System is intended for the creation of anastomoses in blood vessels and grafts, including use in coronary artery bypass grafting procedures.

The Cardica C-Port xA Anastomosis System is a sterile, single use device for creation of a reliably patent end-to-side anastomosis between a conduit and a small vessel. The product consists of accessories to assist in the conduit loading and a device that completes the anastomosis with stainless steel clips. Once the conduit has been loaded onto the device and the device positioned against the target vessel, the anastomosis is created by pushing the actuation button.

The provided text is a 510(k) summary for the Cardica® C-Port® xA Anastomosis System. It is focused on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria in a study with an AI component. Therefore, much of the requested information about AI model performance and study details is not present.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not specify quantitative acceptance criteria or provide detailed performance metrics like sensitivity, specificity, accuracy, or F1-score for the device itself. Instead, the submission states that "All necessary verification testing has been performed on the C-Port xA Anastomosis System with the modified clip to assure substantial equivalence to the predicate device and to assure the safety and effectiveness of the device."

The focus is on demonstrating that the modified device is as safe and effective as the predicate device (Cardica® C-Port® xA Anastomosis System, K053524). This is a common approach for 510(k) submissions where a modification to an already cleared device is being presented.

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

The document does not provide details on the sample size used for any specific test set, nor does it mention data provenance (e.g., country of origin, retrospective or prospective). The testing mentioned is "verification testing" to assure substantial equivalence, rather than a clinical trial with a defined test set for performance.

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

This information is not applicable and therefore not present. The device is a surgical instrument (anastomosis system) and not an AI or diagnostic device that requires expert-established ground truth for image or data interpretation. The "ground truth" for a device like this would relate to its mechanical performance, biocompatibility, and ability to create a functional anastomosis, which would be assessed through engineering tests, animal studies, or potentially human clinical data (though not detailed here).

4. Adjudication Method for the Test Set

This information is not applicable and therefore not present, as there is no diagnostic output that requires 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

There is no mention of an MRMC study, AI, or human readers. The device is a surgical instrument.

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

This is not applicable as the device is a manual surgical instrument, not an algorithm or AI system.

7. The Type of Ground Truth Used

The concept of "ground truth" as it applies to an AI or diagnostic device (e.g., pathology, outcomes data) is not directly applicable here. For this surgical device, the "ground truth" would be related to its engineering specifications, successful creation of an anastomosis, and patient outcomes related to the surgical procedure, as determined through various verification and potentially pre-clinical/clinical tests. The document broadly states "All necessary verification testing has been performed," without detailing the specific "ground truth" for each test.

8. The Sample Size for the Training Set

This is not applicable since the device is not an AI system that requires a training set.

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

This is not applicable for the same reason as above.

In summary, this 510(k) submission is for a modification to a mechanical surgical device and primarily focuses on demonstrating substantial equivalence to a predicate device through verification testing. It does not involve AI, image analysis, or diagnostic capabilities, and therefore, most of the requested information regarding AI model performance, expert ground truth, and study designs for such applications is absent.

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The Cardica® C-Port™ Anastomosis System is intended for the creation of anastomoses in blood vessels and grafts, including use in coronary artery bypass grafting procedures.

The Cardica C-Port™ Anastomosis System is a sterile, single-patient use device. The Cardica® C-Port™ Anastomosis System is designed to create a reliable and consistent end-to-side anastomosis between a conduit and a small vessel. The product consists of accessories to assist in conduit loading and a device that completes the anastomosis with stainless steel clips. Once the conduit has been loaded onto the device, and the device positioned against the target vessel, the anastomosis is created by pushing an actuation button.

The provided text states that "All necessary bench, animal, and clinical testing has been performed on the C-Port™ Anastomosis System and packaging to ensure substantial equivalence to the predicate devices and to ensure the safety and effectiveness of the device." However, no specific details about acceptance criteria, device performance, sample sizes, data provenance, expert qualifications, adjudication methods, or different types of studies (MRMC, standalone) are provided.

Therefore, I cannot extract the requested information. The document focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed report of a study proving the device meets specific acceptance criteria.

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The CorLink AAS is indicated for creation of an anastomosis between a venous graft conduit and the aorta for coronary artery bypass grafting (CABG). The Coring punch component penetrates the aorta and cuts a circumferential aortotomy in which the implanted device will be deployed.

This 510(k) notification describes the CorLink™ Automated Anastomotic Device indicated for creation of an anastomosis between a venous graft conduit and the aorta for coronary artery bypass grafting. The Coring punch device is intended for creating the aortotomy in which the implanted device will be deployed. The major differences between the two systems are: 1. The Piercing Tip and the Tissue Grabber are in one piece in the modified coring punch 2. Tissue Grabber button was replaced by an automatic Tissue Grabber activation button component 3. The Tissue Grabber in the modified coring punch contains 3 barbs instead of 2 as in the 510k cleared coring punch design 4. The Cylinder Cutting Edge diameter will range from 2.5 mm to 3.6 mm and from 2.9 mm to 4.0 mm in the 2.0 mm and 4.0 mm size kits (in 0.1 mm increments each), respectively. 5. The modified coring punch is single use only, whereas the 510(k) cleared coring punch was for single patient use.

This 510(k) summary does not contain information typically found in a clinical study report or a detailed validation study. Instead, it focuses on demonstrating substantial equivalence to a predicate device based on modifications to a component. Therefore, much of the requested information regarding acceptance criteria, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness studies is not present.

However, based on the provided text, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list quantitative "acceptance criteria" for the modified device's performance in the typical sense (e.g., a specific percentage success rate or a measurement tolerance). Instead, the criterion for acceptance is substantial equivalence to the predicate device in terms of performance, intended use, and technological characteristics.

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

• Sample Size: Not specified. The document mentions "performance testing" and "performance data gathered" but does not give specific numbers of tests or samples.
• Data Provenance: Not explicitly stated. The company is ByPass LTD, located in Herzelia B, Israel. The testing would presumably have been conducted by the manufacturer or a contract lab. Whether this was retrospective or prospective (in terms of design changes vs. new testing) isn't detailed, but the "performance testing provided in the application" suggests specific tests were conducted for this submission.

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

• This information is not provided in the 510(k) summary. The nature of the device (a surgical tool for creating an aortotomy) suggests "ground truth" would be established through direct observation of the punch's function and the resulting aortotomy in a controlled environment (e.g., animal models, cadaveric studies, or bench testing on tissue models), rather than through expert consensus on diagnostic images.

4. Adjudication Method for the Test Set

• Not applicable/Not specified. Adjudication methods like 2+1 or 3+1 are typically used in clinical trials or diagnostic studies where multiple readers interpret data. This is a device modification submission focused on mechanical function/performance.

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

• No. This is not an AI-assisted diagnostic device, and thus, an MRMC study comparing human readers with and without AI assistance is not relevant or mentioned.

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

• Not applicable. This is a physical surgical device, not an algorithm.

7. The Type of Ground Truth Used

• The document implies that the ground truth for "performance testing" would relate to the successful creation of the aortotomy, its size, minimal tissue trauma, and integration with the implanted device. This would likely be assessed through direct physical measurement and visual inspection (e.g., histology, dimensional analysis) of the results of the punch's action on tissue. The text mentions the diameter range for the cutting edge, suggesting precise dimensional requirements.

8. The Sample Size for the Training Set

• Not applicable. This is a modification to a physical device, not a machine learning algorithm that requires a "training set."

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

• Not applicable, as there is no "training set" in the context of an AI algorithm. For the initial design and iteration of the device, engineering specifications and testing would have guided its development.

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The intended use of the Sechrist Model 3500CP-G Air/Oxygen Mixer is to enable qualified personnel to mix medical grade air and medical grade oxygen at operator selected ratios, for delivery to patients through various types of respiratory care and heart bypass oxygenation equipment.

The Sechrist Model Series 3500CP-G Air/Oxygen Mixer is a precision pressure regulation and proportioning device which is intended to mix medical grade air and medical grade oxygen. The mixer receives pressurized air and oxygen, at a nominal 50 psi, via Diameter Index Safety System (D.I.S.S.) inlet connections. The unit will operate satisfactorily with inlet pressures of 30 to 70 psi, providing the pressures are within 20 psi of one another. Two outlets for the mixed gas are provided. The air/oxygen mixers are configured with zero to three flowmeters. Accessories include air and oxygen hoses.

The provided 510(k) summary for the Sechrist 3500CP-G Air/Oxygen Mixer does not contain information about a study conducted to prove the device meets specific acceptance criteria based on numerical performance metrics. Instead, the submission focuses on demonstrating substantial equivalence to previously cleared predicate devices through adherence to established quality system standards and verification of the device's intended function.

Therefore, many of the requested details about acceptance criteria, device performance, sample sizes, ground truth establishment, expert adjudication, and MRMC studies are not applicable to this type of submission.

Here's a breakdown of the available information and how it relates to your request:

Acceptance Criteria and Reported Device Performance

Study Information (Based on the provided text):

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

   • Not applicable/Not provided. This 510(k) relies on demonstrating substantial equivalence to predicate devices and adherence to design/manufacturing standards, rather than a clinical performance study with a test set of data.

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

   • Not applicable/Not provided. No specific "test set" with "ground truth" derived from experts is mentioned for this type of submission.

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

   • Not applicable/Not provided.

4. 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 submission for a hardware device (gas mixer), not an AI/software device that would involve human readers or AI assistance.

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

   • Not applicable. This is a hardware device.

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

   • Not applicable/Not provided in the context of a performance study. The "ground truth" for this device's performance would be its ability to physically mix gases within specified tolerances, which would be verified through engineering testing and quality control during manufacturing, not typically a "ground truth" established by experts in a clinical study sense for a 510(k) submission like this.

7. The sample size for the training set:

   • Not applicable/Not provided. Training sets are relevant for machine learning algorithms, which is not the case here.

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

   • Not applicable/Not provided.

Summary of the 510(k) Approach:

The 510(k) for the Sechrist 3500CP-G Air/Oxygen Mixer demonstrates its acceptability through:

• Substantial Equivalence: Comparing the device's design, indications for use, and technological characteristics to legally marketed predicate devices (K802226, K992503, K841789, K863902, K901253). The key "study" here is the comparative analysis showing that the new device is functionally the same or very similar to existing cleared devices.
• Adherence to Standards: Compliance with established national and international quality management system standards (ISO 9001, ISO 13485, EN 46001, 21 CFR 820). This implies that the design, manufacturing, and performance verification processes are robust, reducing the need for a separate detailed clinical performance study in this context.
• Device Description: A detailed description of the device's function and operational parameters, which are presumed to be consistent with those of the predicate devices.

This type of submission typically relies on design verification and validation testing performed by the manufacturer, which demonstrates the device meets its own specifications, rather than a clinical study establishing performance against a "ground truth" in a patient population. These internal tests would verify parameters like pressure regulation accuracy, mixing ratio accuracy, and flow characteristics, but the 510(k) summary itself does not detail the results of these internal tests.

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