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The Quantum Perfusion Hybrid System is intended to collect, defoam and filter venous and suction blood during cardiopulmonary bypass. The device is intended to be used for periods up to six hours. The device is intended for adult patients.

The Quantum Perfusion Hybrid System is a system, including a blood reservoir consisting of an hardshell and softshell reservoir. The combination of defoaming bodies and filtering media of venous/vent and cardiotomy side allows both the filtration of debris and the retention of air bubbles. Product configuration includes, together with the Hybrid System, dedicated spare parts: an adapter 1/2" – 3/8"; a spare cap set; a blood sampling set. The device is intended to be used for periods up to six hours. The Quantum Perfusion Hybrid System is a sterile device with non-pyrogenic fluid pathways, sterilized by ethylene oxide, conceived for single use only and is not to be re-sterilized by the user; the device has a declared shelf life of 2 years.

The provided text is a 510(k) summary for a medical device (Quantum Perfusion Hybrid System) and primarily focuses on proving substantial equivalence to predicate devices through non-clinical testing. It does not contain information about a study proving device performance against specific acceptance criteria for an AI/software-driven device.

Therefore, I cannot provide the requested information, as the document details a traditional medical device submission, not one related to an AI/ML component with associated performance studies (MRMC, standalone algorithm, ground truth establishment, etc.). The document explicitly states: "No clinical data have been included in the current 510(k) submission to support substantial equivalence to legally marketed predicate and reference devices." and "No animal studies have been performed except for mandatory biocompatibility tests...".

The non-clinical testing mentioned is focused on general device performance for a cardiopulmonary bypass blood reservoir, such as pressure drop, mechanical resistance, air handling, and filtration efficiency, verifying it meets established engineering requirements for this type of device, which are inherent to the device's design and function rather than a set of statistical acceptance criteria that would typically be associated with an AI/ML algorithm's performance.

To answer your request, a document detailing an AI/ML device would be needed, specifically discussing its performance study, acceptance criteria, test set details, ground truth, and potentially MRMC study results.

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The MVR Venous Reservoir Bag is indicated for use during cardiopulmonary bypass surgery in an extracorporeal circuit utilizing a membrane oxygenator for up to 6 hours in duration. The MVR Holder (Model MVR-SH) is indicated for use with the MVR Collapsible Venous Reservoir Bag.

The MVR Venous Reservoir Bag, with or without Cortiva bioactive surface, is a single-use, sterile, nonpyrogenic variable volume device used in conjunction with a membrane oxygenator during cardiopulmonary bypass (CPB) surgery. It is sterilized using ethylene oxide. It is designed to accommodate blood from the patient and suctioned blood from the cardiotomy reservoir. The internal screen of the venous reservoir is designed to assist in tramping air, which may enter the venous reservoir during priming or perfusion on the inlet side of the reservoir. Air trapped in the venous reservoir bag can be removed using the one-way stopcock located at the top of the reservoir.

Blood that comes from the patient flows into the reservoir and is delivered through a pump to the oxygenator and other axillary devices, and back to the patient. The oxygenator can be connected to a heater/cooler device, recirculation circuit, cardioplegia circuit, and the main blood path.

Products coated with Cortiva bioactive surface include a "CB" prefix in the model number. The primary blood-contacting surfaces of the product are coated with Cortiva bioactive surface. This coated surface enhances blood compatibility and provides a blood-contacting surface that is thromboresistant. Cortiva bioactive surface contains nonleaching heparin derived from porcine intestinal mucosa.

The document provided does not describe a study involving device performance, diagnostic accuracy, or clinical outcomes that would typically include acceptance criteria, sample sizes for test and training sets, expert involvement, or adjudication methods.

Instead, this is a 510(k) premarket notification for a medical device (MVR™ Venous Reservoir Bag) which primarily focuses on demonstrating substantial equivalence to a legally marketed predicate device. The "Summary of Testing" section describes biocompatibility testing and a design assessment related to a material change in a component (one-way stopcock) of the device.

Therefore, many of the requested categories (e.g., specific acceptance criteria for performance, sample sizes for test/training sets, number/qualifications of experts, adjudication methods, MRMC studies, standalone performance, type of ground truth for performance, training set sample size/ground truth establishment) are not applicable to the information presented in this document.

However, I can provide the available information related to the biocompatibility testing and design assessment.

1. Table of Acceptance Criteria and Reported Device Performance (for Biocompatibility and Design Assessment):

Given the nature of the document, the "performance" here refers to meeting biocompatibility standards and
the assessment that functional performance is unaffected.

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

• Biocompatibility Testing: The document does not specify exact sample sizes for each biological endpoint test. It references compliance with ISO 10993 and USA FDA Guidance Document on Use of ISO 10993-1 standards, which typically outline specific sample size requirements for each test.
  • Data Provenance: The tests for the device component were either conducted by Medtronic (or a contracted lab) or referenced from a supplier certificate. The reference device data ("Step™ Auto Suture™ Dilator and Cannula") was applied, suggesting internal company data or previous submissions. The supplier certificate indicates tests were conducted "in accordance with 'Good Laboratory Practice'". This appears to be prospective testing for regulatory submission. Country of origin for data is not specified beyond being part of a US FDA submission process.
• Design Assessment: No specific sample size is discussed as it was a qualitative assessment.

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

• Not Applicable in this context. The biocompatibility tests are laboratory-based, with "passing" results determined by established scientific/regulatory standards rather than expert consensus on a ground truth. For the design assessment, no specific number or qualification of experts is mentioned; it's a statement of internal engineering/design conclusion.

4. Adjudication method for the test set:

• Not Applicable. As mentioned above, the results are determined by objective laboratory test outcomes against established Pass/Fail criteria, not by human adjudication of observations or interpretations.

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 physical medical device (venous reservoir bag) and does not involve AI, human readers, or diagnostic interpretation.

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

• Not Applicable. This is a physical medical device, not an algorithm or software.

7. The type of ground truth used:

• For Biocompatibility: The "ground truth" is defined by the objective pass/fail criteria of the specified ISO 10993 and USP Class VI biological endpoint tests (e.g., no significant cytotoxicity, no sensitization, no systemic toxicity, etc.).
• For Design Assessment: The "ground truth" is the engineering assessment that the material change has no impact on the functionality or performance of the final product.

8. The sample size for the training set:

• Not Applicable. There is no "training set" as this is not an AI/machine learning device. The biocompatibility tests are evaluative, not for training.

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

• Not Applicable. As there is no training set, this question is not relevant.

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The BMR1900 PHISIO Closed Venous Reservoir Bag is intended to be used in cardiopulmonary bypass procedures for periods of up to six hours.

The BMR1900 PHISIO Closed Venous Reservoir Bag (hereinafter BMR1900) is a softshell, flexible, polyvinylchloride bag designed for use in cardiopulmonary bypass surgery for periods up to six hours. It is supplied sterile with non-pyrogenic fluid pathways, for single use only, and is not to be resterilized by the user. As for the unmodified device, the BMR1900 PHISIO. is composed of the following elements: - · A collapsible bag that serves as an in-line closed venous reservoir to contain blood volume. - · An integral 105 micron polyester filter screen which is mainly intended to facilitate the removal of large air bubbles from the blood. - A dual four-wav stopcock assembly used to manually purge the air captured by the filter screen or to administrate drugs or other solutions as needed during the cardiopulmonary bypass procedure. - A 1/2" venous blood inlet port and a 3/8" blood outlet port. - Connectors integral to the blood inlet port that are used to measure temperature and saturation/hematocrit of the incoming blood using external monitoring equipment, as needed. The BMR1900 PHISIO is designed with a 1900 mL maximum operating volume and a minimum operating volume equals to 300 mL and can be used at any flow rate up to 6 liter per minute. The venous blood inlet/outlet ports and the dual four-way stopcock assembly are opposite located with respect to the horizontal axis: the formers are placed in the bottom of the device while the latter at the top of the bag. Considering the vertical axis, both modified and unmodified devices present the blood inlet port with the integral cardiotomy inlet placed on one side of the bag while the blood outlet port is located on the opposite side of the bag. Blood enters the bag through the inlet port and passes through a polyester filter screen before exiting the bag through the outlet port. The purpose of the filter is to facilitate the removal of large air bubbles from the blood. The BMR1900 PHISIO will be available with two configurations that differ only for the orientation of the venous blood inlet. The BMR1900 PHISIO. has the connector of the venous blood inlet right oriented (figure 1) while the BMR1900 L PHISIO. has the connector of the venous blood inlet left oriented (figure 2) The modified device is modified version of the currently marketed BMR1900 PH.I.S.I.O product

The provided text describes a 510(k) premarket notification for the BMR 1900 PHISIO Closed Venous Reservoir Bag, a medical device. This is a submission for a modified medical device, which is compared to its unmodified predicate device. The document focuses on demonstrating substantial equivalence rather than a device's initial performance study against clinical endpoints.

Therefore, the specific information requested in the prompt, such as acceptance criteria based on clinical outcomes, human reader improvement with AI, or detailed ground truth establishment for novel algorithms, is not applicable in this context. The study outlined here is a non-clinical performance study to show that the modified device is as safe and effective as the original, legally marketed device.

Here's the information that can be extracted and how it relates to the prompt's questions:

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

Since this is a substantial equivalence submission for a modified device, the "acceptance criteria" are effectively that the modified device performs equivalently to the unmodified predicate device across several non-clinical tests. The document states that the modified device "successfully met all acceptance criteria."

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 does not specify the sample size for each non-clinical test. The tests were performed on "sterile aged devices" equivalent to "at least 3 years" of aging. The provenance is not explicitly stated beyond the applicant being Sorin Group Italia S.R.L. and the tests being "in vitro testing." This implies laboratory-based tests rather than human patient data, and thus is more akin to prospective testing of manufactured devices.

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 is a non-clinical engineering and materials performance study, not a study involving human expert interpretation or ground truth establishment in a clinical sense.

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

Not applicable. This is a non-clinical engineering and materials performance study, not a study requiring adjudication of expert opinions.

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 non-clinical performance study for a physical medical device (a blood reservoir bag) and does not involve AI or human readers.

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

Not applicable. This device is not an algorithm or AI.

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

The "ground truth" in this context would be the established performance characteristics and safety profile of the unmodified BMR1900 PHISIO predicate device. The tests performed on the modified device aim to demonstrate that it functions identically to this established benchmark.

8. The sample size for the training set

Not applicable. This is not a machine learning or AI device, so there is no "training set."

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

Not applicable. There is no training set. The "ground truth" for the non-clinical comparisons is the performance of the previously cleared predicate device, which would have been established through its own initial premarket submission and subsequent clinical use.

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The Intersept filtered cardiotomy reservoir with Cortive surface is indicated for use in the cardiopulmonary bypass circuit during surgery for:

• an air/fluid separation chamber
• a temporary storage reservoir for priming solution and blood
• the filtration of particulates from bank blood and the storage and filtration of blood recovered from the field by suction
• the addition of medications or other fluids.

The Intersept Filtered Cardiotomy Reservoir with Cortiva BioActive Surface is a single-use, device with a sterile, nonpyrogenic fluid path. The maximum capacity of each reservoir is 2,600 mL. The maximum recommended flow rate is 2 liters per minute (LPM). Each reservoir has eight luer or 0.6 cm (0.25 in) ID access ports; four suction access ports, two pre-defoamer and two post-defoamer access ports. One of the post-defoamer access ports is intended for use as a vent. Each Intersept Filtered Cardiotomy Reservoir contains an open cell polyurethane defoamer with a 20-micron microaggregate filter covered with a polyester sleeve.

The provided document is a 510(k) premarket notification for a medical device, the "Intersept™ Filtered Cardiotomy Reservoir with Cortiva™ BioActive Surface." It details the device's indications for use, comparison to predicate devices, and a summary of testing conducted to demonstrate substantial equivalence.

However, this document does not contain the kind of detailed information typically found in acceptance criteria or a study write-up designed to prove a device meets those criteria, especially in the context of an AI-powered diagnostic device performing a specific task (like identifying lesions in medical images).

Here's why and what information is missing:

• Device Type: This submission is for a physical medical device (a cardiopulmonary bypass blood reservoir), not an AI algorithm. Therefore, the "acceptance criteria" and "study" described in the prompt, which are strongly geared towards AI performance metrics (sensitivity, specificity, AUROC, reader studies, ground truth establishment), don't directly apply in the same way.
• Performance Metrics: The "reported device performance" in this document refers to physical and biological performance (bioactivity, leaching, coverage, biocompatibility, filtration efficiency, blood trauma), not diagnostic accuracy.
• Clinical Study Design: There is no description of a clinical study involving human subjects or experts assessing diagnostic performance as would be relevant for an AI algorithm. The testing described is laboratory-based and focused on material properties and basic device function.

Based on the provided document, here's what can be extracted and what remains unanswered regarding the prompt's specific requests (assuming the prompt's structure is still applied, despite the mismatch in device type):

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

Interpretation/Note: These are not "acceptance criteria" in the sense of diagnostic performance thresholds for an AI, but rather verification/validation checks for physical and biological device properties. The "Pass" indicates the device met Medtronic's internal criteria for these tests.

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

• Sample Size for Test Set: Not specified in the provided document. The document lists "tests" but doesn't detail the number of units or samples used for each test.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not applicable for a physical device's lab testing. The tests are laboratory-based and not derived from clinical patient data from a specific country or study type.

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

• This question is not applicable as the device is not an AI diagnostic algorithm, and "ground truth" in the context of medical image interpretation by experts is not relevant to this submission. The tests performed are laboratory-based physical and biological assays.

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

• Not applicable. There is no adjudication process involving human interpretation or consensus for the validation of this physical device. Verification/validation tests are typically performed according to established protocols.

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

• Not applicable. This device is not an AI algorithm, and therefore, an MRMC study comparing human reader performance with and without AI assistance was not performed.

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

• Not applicable. The device is a physical medical device, not an algorithm.

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

• Not applicable / Differently Defined: "Ground truth" for this device refers to established scientific/engineering principles, validated analytical methods, and predetermined specifications for physical and biological characteristics (e.g., certain levels of bioactivity, filtration efficiency, or absence of harmful leaching). It's not clinical "ground truth" derived from patient outcomes or expert reads.

8. The sample size for the training set

• Not applicable. This device is not an AI algorithm that requires a training set. The development of the device would involve engineering design, material selection, and iterative testing, not "training."

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

• Not applicable. As above, no training set or its associated ground truth establishment is relevant to this physical device submission.

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INSPIRE SVR 1200 with Ph.I.S.I.O. coating is intended for use in adult surgical procedures requiring cardiopulmonary bypass. It collects and handles venous blood from cardiotomy reservoir. The INSPIRE SVR 1200 is intended to be used for 6 hours or less.

INSPIRE SVR 1200 with Ph.I.S.I.O. coating is intended for use in adult and small adult surgical procedures requiring cardiopulmonary bypass. It collects and handles venous blood and suction blood from cardiotomy reservoir. The INSPIRE SVR 1200 is intended to be used for 6 hours or less.

The Sorin INSPIRE SVR 1200 (hereinafter referred to as INSPIRE SVR 1200) is a flexible PVC soft shell venous reservoir bag. This reservoir may be attached to the INSPIRE 6F C and INSPIRE 8F C oxygenator systems using a molded fitting connected to the gas exchange module. The blood contacting surfaces of this device are coated with a phosphorylcholine-based (Ph.I.S.I.O.) coating that provides a uniform surface. The device is provided with a 1/2" venous inlet connector and a 3/8" blood outlet connector. The venous inlet has an integral cardiotomy reservoir connector to allow receipt of blood from both venous cannulation and from a cardiotomy reservoir.

The INSPIRE SVR 1200 can be operated at flow rates up to 8 liters per minute (I/min) and has a maximum reservoir volume of 1325 mL.

The INSPIRE SVR 1200 soft shell venous reservoir is similar to the predicate devices as it consists of a soft PVC material and is used to collect blood during cardiopulmonary bypass procedures lasting up to 6 hours. The intended use and principles of operation are consistent with the predicate devices. It differs from the predicate devices in volume and dimensions, length of purge lines, and it includes a mounting backplate.

The device is ethylene oxide sterilized, has a non-pyrogenic fluid path and is for single use only.

The provided text describes the 510(k) premarket notification for a medical device called INSPIRE SVR 1200, a flexible PVC soft shell venous reservoir bag used during cardiopulmonary bypass procedures. The document focuses on demonstrating the substantial equivalence of this new device to previously marketed predicate devices.

However, the information required to answer your specific questions about acceptance criteria, study details, and ground truth establishment (especially for AI/ML device testing) is not present in the provided text. The document describes a traditional medical device submission, where "acceptance criteria" primarily refer to meeting specific performance and safety standards through non-clinical laboratory testing, rather than a study involving a test set, expert readers, or AI/ML performance metrics.

The document lists various non-clinical tests performed on the device (e.g., biocompatibility, blood trauma, flow rate capacity, structural integrity) and states that the device "successfully met all acceptance criteria for each of the following tests." These acceptance criteria are implicitly the performance specifications for these physical and functional tests, designed to show the device's substantial equivalence to predicates.

Therefore, I cannot provide details on:

1. A table of acceptance criteria and reported device performance (in the context of AI/ML performance metrics like sensitivity, specificity, etc.): The document lists types of tests but not specific quantitative acceptance criteria or their corresponding numerical results for each test.
2. Sample size used for the test set and data provenance: The tests are likely bench tests or in-vitro tests on mechanical properties and blood interaction, not a "test set" of patient data in the AI/ML sense.
3. Number of experts used to establish ground truth and qualifications: This is not relevant to the type of testing described (physical and chemical properties of a medical device).
4. Adjudication method for the test set: Not applicable.
5. Multi-reader multi-case (MRMC) comparative effectiveness study or human reader improvement with AI assistance: This device is a physical component used in a surgical procedure, not an AI diagnostic or assistance tool.
6. Standalone (algorithm only without human-in-the-loop performance): Not applicable, as this is not an algorithm-based device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Ground truth in this context would be laboratory measurements and established biological safety standards, not case-level diagnostic ground truth.
8. The sample size for the training set: Not applicable, as this is not an AI/ML device that undergoes training.
9. How the ground truth for the training set was established: Not applicable.

In summary, the provided document describes the regulatory approval process for a physical medical device (a blood reservoir) based on its functional, material, and safety properties, demonstrating substantial equivalence to a predicate device through non-clinical testing. It does not contain information relevant to the testing and validation of an AI/ML-based medical device.

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The Capiox® Advance Hardshell Reservoir is a hardshell reservoir used to store blood during extracorporeal circulation from both the venous line and the cardiotomy line. The reservoir contains filters to remove particulate matter and defoamers to facilitate air bubble removal.

The Hardshell Reservoir is also used for post-operative chest drainage and autotransfusion procedures to aseptically return blood to the patient for blood volume replacement.

The Hardshell Reservoir is also used with the vacuum-assisted venous return technique during cardiopulmonary bypass.

The Hardshell Reservoir contains X-Coating, which is intended to reduce platelet adhesion on the surfaces of the device.

The device may be used for procedures lasting up to 6 hours.

The Capiox® Advance Hardshell Reservoir device and the predicate Capiox® RX Hardshell Reservoir device are both used as a blood storage devices during and after cardiopulmonary bypass procedures. Venous blood enters the reservoir via gravity, or by way of external vacuum that may be applied to the reservoir.

Venous blood that is drawn from the patient enters the device via the venous blood inlet port. The blood passes through a defoamer to remove air bubbles from the blood and through a filter to remove particulates from the blood.

Blood may also be suctioned into the reservoir from the cardiotomy field. This blood enters the device through the cardiotomy blood suction ports. The blood passes through a defoamer to remove air bubbles from the blood and through a filter to remove particulates from the blood.

Blood exits the device via gravity through the blood outlet port and is subsequently pumped through the remainder of the cardiopulmonary bypass circuit.

The design of the Capiox® Advance Hardshell Reservoir is comprised of a hardshell casing that serves as a blood containment system within the bypass circuit. The upper portion of the reservoir consists of a hardshell lid assembly that contains the necessary inlet ports and vent ports. It contains a rotatable venous blood inlet port. The total capacity of the reservoir is 4000mL.

The venous section of the reservoir contains a filter for particulate matter removal and a defoamer to facilitate air bubble removal. The cardiotomy section of the reservoir contains a filter for particulate matter removal and a defoamer to facilitate air bubble removal.

The provided text describes a 510(k) premarket notification for the Capiox® Advance Hardshell Reservoir (K153143). This is an administrative document for a medical device and, as such, it does not contain the detailed data from clinical studies with acceptance criteria, sample sizes, or ground truth establishment that would be present in a research paper.

However, I can extract the relevant information that is available about the performance evaluations and what they aim to show for the device:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists "Performance Evaluations" that were conducted to establish substantial equivalence to a predicate device (Capiox® RX Hardshell Reservoir; K130359). However, it does not provide specific numerical acceptance criteria or the reported device performance for each evaluation. It simply lists the types of tests performed.

The document states that "Clinical studies involving patients are not necessary to demonstrate substantial equivalence... Substantial equivalence is demonstrated with the following in-vitro performance evaluations." This indicates that the evaluations listed above are the studies that demonstrate the device meets the necessary criteria for substantial equivalence, implying their results were favorable and met internal company-defined specifications, even if those are not explicitly detailed here.

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

The document explicitly states: "Clinical studies involving patients are not necessary to demonstrate substantial equivalence of the Capiox® Advance Hardshell Reservoir to the predicate device." Therefore, there was no test set with human patient data used for this 510(k) submission.

The provenance of the data for the in-vitro performance evaluations is not specified, but it would typically be internal laboratory testing conducted by Terumo Cardiovascular Systems Corporation.

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

Not applicable, as no clinical studies with human patient data were conducted that would require expert-established ground truth. The evaluations were in-vitro tests, likely with predefined physical or chemical standards.

4. Adjudication method for the test set

Not applicable, as no test set with human patient data 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 cardiopulmonary bypass hard-shell reservoir, not an AI-powered diagnostic tool. No MRMC study or AI assistance is mentioned.

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

Not applicable. This device is a physical medical device, not a software algorithm.

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

The "ground truth" for the in-vitro performance evaluations would be the established scientific and engineering standards and specifications for devices of this type, as well as the performance of the predicate device. For example:

• Air Handling Performance: Likely measured against predefined thresholds for air bubble removal efficiency.
• Hemolysis: Measured against acceptable levels of blood cell damage according to ISO standards or industry best practices.
• Venous Filter Dynamic Hold Up and/or Pressure Drop: Measured against specifications ensuring adequate blood flow and minimal retention.
• Product Integrity/Seal, Burst, Leak, Circulation, Pull Testing: Measured against engineering specifications for mechanical strength and leak resistance.
• Pre-Connect Evaluation: Likely assessed for ease of connection and secure fit.
• Package Testing: Assessed against standards for maintaining sterility and integrity during shipping and storage.

These "ground truths" are based on engineering principles, industry standards (e.g., ISO), and the performance characteristics of the legally marketed predicate device.

8. The sample size for the training set

Not applicable. This is a physical medical device, not a machine learning model requiring a training set.

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

Not applicable.

Summary:

The provided document describes a 510(k) premarket notification for a Class II medical device, the Capiox® Advance Hardshell Reservoir. The submission relies on demonstrating "substantial equivalence" to a predicate device through in-vitro performance evaluations rather than clinical studies with human patients. As such, information typically found in detailed studies evaluating diagnostic algorithms (like acceptance criteria, sample sizes for human readers/patients, ground truth establishment by experts, or AI-specific studies) is not present. The "studies" in this context are a series of laboratory-based engineering and performance tests designed to confirm that the modified device functions comparably and safely to its predicate.

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The Intersept filtered cardiotomy reservoir is indicated for use in the cardiopulmonary bypass circuit during surgery for:

• an air/fluid separation chamber;
• a temporary storage reservoir for priming solution and blood;
• the filtration of particulates from bank blood and filtration of blood recovered from the field by suction:
• the addition of medications or other fluids.

The Intersept filtered cardiotomy reservoir is also indicated for use after open heart surgery for:

• the post-operative collection of autologous blood from the chest and the aseptic return of blood to the patient for volume replacement.

The Intersept™ Filtered Cardiotomy Reservoir is a single-use, device with a sterile, nonpyrogenic fluid path. The maximum capacity of each reservoir is 2,600 ml. The maximum recommended flow rate is 2 liters per minute (LPM).

Each reservoir has eight luer or 1/4" (0.6 cm) ID access ports;

• four suction access ports .
• two pre-defoamer and two post-defoamer access ports. One of the post-defoamer access . ports is intended for use as a vent.

Each Intersept™ Filtered Cardiotomy Reservoir contains an open cell polyurethane defoamer with a 20 micron microaggregate filter covered with a polyester sleeve.

This document is a 510(k) premarket notification for the Intersept™ Filtered Cardiotomy Reservoir. It focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study proving the device meets specific acceptance criteria with reported performance metrics in the format requested.

Therefore, many of the requested sections (Table of acceptance criteria, sample sizes, expert details, adjudication methods, MRMC studies, standalone performance, ground truth details for training and test sets) cannot be fully answered from the provided text. The document is primarily a regulatory submission for a medical device, which often uses comparison to a predicate as the basis for clearance, rather than presenting a novel clinical study with detailed performance metrics against pre-defined acceptance criteria.

However, based on the provided text, here is what can be inferred and explicitly stated:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state numerical acceptance criteria for performance metrics. Instead, it relies on demonstrating "substantial equivalence" to a predicate device in terms of performance. The "Results" column only states "Pass," indicating that the device met the performance standards demonstrated by the predicate.

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

The document does not specify the sample sizes used for the "Filtration Efficiency," "Blood Trauma," or "Biocompatibility" tests. It also does not mention the data provenance (e.g., country of origin, retrospective/prospective).

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

Not applicable. The document describes engineering and biological testing, not a study involving ground truth established by medical experts for diagnostic interpretation.

4. Adjudication method for the test set

Not applicable. This is not a study requiring adjudication of expert interpretations.

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 not an AI/diagnostic device.

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

Not applicable. This is not an AI/diagnostic device.

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

For the tests mentioned:

• Filtration Efficiency: The ground truth would likely be established through standard laboratory methods for measuring particle retention (e.g., gravimetric analysis or particle counting) against a known challenge.
• Blood Trauma: Ground truth would be established through laboratory analysis of blood samples (e.g., measurement of hemolysis, platelet activation, or other markers of blood damage) directly comparing the device's impact to that of the predicate or established benchmarks.
• Biocompatibility: Ground truth is established through standardized in-vitro and/or in-vivo testing according to ISO 10993 series for medical devices.

8. The sample size for the training set

Not applicable. This document does not describe a machine learning model, so there is no training set.

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

Not applicable. There is no training set.

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The venous hardshell cardiotomy reservoir is used to collect, store and filter blood in extracorporeal circulation, in cardiopulmonary bypass operations on pediatric patients for up to 6 hours. The reservoir can also be employed postoperatively as drainage and autotransfusion reservoir (e.g., for thorax drainage) to return the autologous blood to the patient which was removed from the thorax for the volume exchange.

The Neonatal and Pediatric Venous Hardshell Cardiotomy Reservoirs with and without SOFTLINE Coating are developed for surgical procedures requiring cardiopulmonary bypass for pediatric patients. They are used as a blood buffer in the extracorporeal circuit and are used as a collecting and defoaming device for sucked blood. The device is supplied sterile and non-pryogenic.

The provided document describes a 510(k) premarket notification for a medical device modification, specifically for Neonatal and Pediatric Venous Hardshell Cardiotomy Reservoirs. This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device's absolute safety and effectiveness through extensive clinical trials as would be required for a PMA (Premarket Approval) submission.

Therefore, the document does not contain the acceptance criteria or a study that proves the device meets specific performance criteria in the context of an AI/ML medical device submission. The provided information details design verification tests, which are engineering-focused assessments, not clinical performance studies with acceptance criteria as typically understood in the context of AI/ML performance metrics (e.g., sensitivity, specificity).

Here's why the requested information cannot be fully provided from this document:

• Device Type: The device is a "Venous Hardshell Cardiotomy Reservoir," which is a physical medical device used in cardiopulmonary bypass operations, not an AI/ML algorithm.
• Study Type: The submission is a 510(k) for a "device modification," which relies on demonstrating substantial equivalence through non-clinical (i.e., laboratory/benchtop) design verification tests rather than clinical studies.
• Focus: The focus of the 510(k) is on the safety and performance of the modified physical components (defoamer coating, flow rates, volumes), not on the diagnostic or predictive accuracy of an algorithm.

However, I can extract the relevant information regarding the design verification tests performed, which serve a similar function to "proving the device meets acceptance criteria" within the context of hardware modifications:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" with numerical targets for each test, nor does it provide a detailed "reported device performance" table with precise quantitative results. Instead, it indicates that the tests were performed to show the modified device is "as safe and effective as the originally cleared devices" and that the "evaluation and test results do not show any kind of risk potential."

Regarding the specific questions tailored for AI/ML device studies:

2. Sample size used for the test set and the data provenance: Not applicable. This is a physical device. The "tests" were design verification tests (benchtop/laboratory), not clinical studies with patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device's performance often comes from engineering specifications, established testing protocols, and physical measurements, rather than expert consensus on medical images or clinical outcomes.

4. Adjudication method for the test set: Not applicable. There is no mention of expert review or adjudication in the context of these engineering design verification tests.

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 physical device, not an AI/ML algorithm used for image interpretation or diagnosis by human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is a physical device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the design verification tests listed, the "ground truth" would be established by predefined engineering specifications, performance standards, biological safety standards (e.g., ISO standards for biocompatibility), and comparison to the predicate device's known performance characteristics.

8. The sample size for the training set: Not applicable. This device does not involve machine learning and therefore has no training set.

9. How the ground truth for the training set was established: Not applicable. This device does not involve machine learning and therefore has no training set.

In conclusion: The provided document is for a traditional medical device modification (physical product) and uses design verification testing to demonstrate substantial equivalence, not a clinical study to establish performance metrics for an AI/ML device. Therefore, many of the requested fields are not applicable to this submission type.

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The Affinity Pixie Cardiotomy/Venous Reservoir with Carmeda BioActive Surface or Balance Biosurface are indicated for use for neonate, infant, and small pediatric patients undergoing cardiopulmonary bypass procedures requiring a blood flow rate up to 2.0 L/min.

The Affinity Pixie Cardiotomy/Venous Reservoir is intended to be used in jan extracorporeal perfusion circuit to collect venous and cardiotomy suctioned blood during toutine cardiopulmonary procedures up to 6 hours in duration. The CVR is also intended for use during vacuum assisted venous drainage (VAVD) procedures.

The Medtronic Affinity Pixie Cardiotomy Venous Reservoir (CVR) is a single use device designed to collect and store blood during extracorporeal circulation. Cardiotomy blood is collected, filtered, and defoamed before mixing with the filtered venous blood. The reservoir can also be used for vacuum-assisted venous drainage.

The Affinity Pixie Cardiotomy Venous Reservoir is coated with either Carmeda BioActive Surface or Balance Biosurface. The device is single-use, nontoxic, nonpyrogenic, and supplied sterile for clinical use.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the Medtronic Affinity Pixie Cardiotomy Venous Reservoir:

This document is a 510(k) summary for a medical device (K141233), which primarily focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than establishing de novo safety and effectiveness through extensive clinical trials. Therefore, the "acceptance criteria" and "study" are interpreted within this regulatory context.

The device in question is the Medtronic Affinity Pixie® Cardiotomy Venous Reservoir with Carmeda® BioActive Surface or with Balance® Biosurface.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of a 510(k) submission, the "acceptance criteria" are generally framed as demonstrating equivalence to the predicate device in terms of design, materials, principles of operation, and performance. The "reported device performance" is the result of bench testing confirming these aspects.

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

The document explicitly states that "Bench testing was used to verify the performance characteristics of this device. Clinical testing was not required to establish substantial equivalence."

• Test Set Sample Size: Not specified in the provided document. For bench testing, typical sample sizes vary depending on the specific test and statistical requirements, but no numbers are given here.
• Data Provenance: The data is from bench testing conducted by Medtronic, Inc. This is not human clinical data; it's laboratory/engineering data. It is prospective in the sense that the tests were conducted specifically for this 510(k) submission. No country of origin for the data (beyond the applicant being US-based) is specified, but it would have been generated in a controlled, manufacturing/testing facility.

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

Not applicable. Since clinical studies (which would typically involve expert reviewers to establish ground truth) were not required and not performed, there were no "experts" in this context establishing ground truth for a clinical test set. The "ground truth" for bench tests is based on engineering specifications, regulatory standards, and comparison to the predicate device's established performance.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods like '2+1' or '3+1' are used for interpreting clinical data, particularly image-based studies, often involving multiple readers. Given that this submission relies on bench testing and not clinical trials, no such adjudication method was employed.

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

No. A Multi-Reader Multi-Case (MRMC) comparative effectiveness study involves multiple human readers evaluating cases, often with and without AI assistance, to assess the impact of the AI on reader performance. This type of study is specifically for evaluating the effectiveness of AI algorithms in a clinical setting. As this device is a physical medical device (Cardiotomy Venous Reservoir) and not an AI/software as a medical device (SaMD), and no clinical studies were performed, an MRMC study was not applicable and was not conducted.

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

No. This question is also specifically relevant for AI/SaMD devices. Since the device is a physical reservoir for cardiopulmonary bypass and not an AI algorithm, a "standalone algorithm performance" study is not applicable and was not performed. The performance evaluated was of the physical device itself in bench tests.

7. The Type of Ground Truth Used

The type of "ground truth" used for this 510(k) submission is primarily based on:

• Engineering specifications and design requirements: For parameters like cap removal force, particulate generation, and biocompatibility.
• Regulatory standards: Ensuring compliance with relevant industry and FDA standards for blood-contacting devices.
• Predicate device performance: The critical "ground truth" for a 510(k) is the established, safe, and effective performance of the legally marketed predicate device (K100645). The new device's performance in bench tests must demonstrate it is "the same" or does not raise new questions of safety or effectiveness compared to this predicate.

8. The Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that requires a "training set." The concept of a training set is specific to machine learning.

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

Not applicable. As there is no AI/ML component, there is no training set and thus no ground truth established for it.

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The Better-Bladder™ is a device that isolates from blood contact when measurements of blood pressure in extracorporeal circuits are made during term procedures. The pressure signal can be used to control pump speed. It is also used as an inline reservoir to provide compliance in the circuit during short and long term procedures.

The Better-Bladder™ (BB) is a length of standard perfusion tubing, a portion of which has been processed to form a sausage shaped balloon with a thin wall that is then sealed within a clear, rigid housing. This device can be used as an inline blood reservoir during extracorporeal circulation. It can also be used to monitor the blood pressure noninvasively: because the pressure of blood flowing inside the tubing is transmitted across the thin wall to the housing chamber, this pressure can be monitored via a pressure monitoring line to a pressure sensor. The BB thereby serves as a pressure transducer protector, isolating the blood from the pressure sensor and allowing noninvasive pressure measurements, which in turn can be used as input signals to control the pump speed.

This 510(k) notification describes a medical device, the Better-Bladder™ BB14-72, and its substantial equivalence to a predicate device, focusing on its physical characteristics and performance in a mock circulatory system. The document does not describe the acceptance criteria and study design elements typically associated with AI/ML-based medical devices or diagnostics. Therefore, many of the requested fields cannot be directly answered from the provided text.

Here's an analysis based on the provided text, addressing the points where information is available and noting when it is not:

Acceptance Criteria and Reported Device Performance

The core acceptance criterion for the BB14-72 appears to be its ability to mitigate negative pressure spikes due to venous line obstruction, performing "as well or better than the predicate device," and providing "more time for a pump flow controller to respond than the predicate device."

Study Details

The provided document describes a performance study to demonstrate the BB14-72 device's mechanical characteristics, not a clinical study involving human patients or complex AI/ML algorithms.

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

   • Sample Size: Not explicitly stated as a numerical sample size. The testing involved comparing the BB14-72 against the predicate device (BB14) and a 1/4" standard perfusion tubing in a "mock extracorporeal circuit." The graphs show results for three devices/configurations.
   • Data Provenance: The study was conducted in a "mock extracorporeal circuit," which implies a laboratory setting. There is no mention of country of origin of data or whether it was retrospective or prospective. It's a prospective engineering performance test.

2. 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 was a physical device performance test using a mock circuit, not a diagnostic device requiring expert interpretation for ground truth. The "ground truth" was mechanical measurements (pressure and time).

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

   • Not applicable. See point 2.

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 not an AI/ML device, and no MRMC study was performed.

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

   • Not applicable. This is not an AI/ML algorithm; it is a physical medical device. The "standalone" performance shown is purely mechanical, not algorithmic.

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

   • The "ground truth" was direct physiological measurements (pressure and time) obtained from a simulated environment (mock extracorporeal circuit) under controlled conditions.

7. The sample size for the training set:

   • Not applicable. This is not an AI/ML device, and therefore no training set was used.

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

   • Not applicable. See point 7.

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