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This product is indicated for use in the extracorporeal circuit during cardiopulmonary bypass (CPB) surgical procedures.

Medtronic Tubing Packs are used in cardiopulmonary bypass procedures for connecting the primary devices of the bypass circuit. Medtronic Tubing Packs consist of coated and uncoated tubing, connectors and various medical devices that are pre-assembled into user-specified extracorporeal cardiopulmonary bypass perfusion circuits. Tubing Packs are intended for use within the extracorporeal blood pathway during cardiopulmonary bypass surgical procedures. Medtronic Tubing Packs are currently packaged into qualified clear tray and sterile packaging systems. This submission is to add additional tubing and connectors for use in Tubing Pack and is changing as part of continual process improvement efforts. The component additions include tubing and connectors that may be coated or uncoated. The coating types include: Cortiva, Trillium and Balance and these three types of coatings are identical to the cleared existing components for Tubing Packs (K891687, K012538 and K122811). The components being added do not have any changes in materials, technology or labeling than previously cleared components for Tubing Packs. These additional components are representative of currently cleared components and do not add any additional risk to patients therefore, Medtronic believes these components may be added to the Tubing Packs. All packaging components remain unchanged (peel pouches, ties, bands, trays, lids and shipper). There is no change to the sterile barrier, sterilization and test methods used for these components.

This looks like information for a regulatory submission for a medical device. Based on the provided text, here's a breakdown of the acceptance criteria and the study conducted to prove the device meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

The document does not explicitly state the sample size used for the test set in quantitative terms (e.g., number of units tested). Instead, it mentions that "worse case testing for tubing and connectors" was performed and "verification results were leveraged based on most challenging components." This suggests that a subset of components representing the most challenging scenarios was selected for testing.

The data provenance is from Medtronic, Inc.'s internal testing. It is prospective in the sense that the testing was conducted specifically for this submission to verify the performance of the added components. The country of origin of the data is implicitly the United States, as Medtronic is based there and submitting to the FDA.

3. Number of Experts and Qualifications for Ground Truth

This device (Medtronic Tubing Pack) is a Class II medical device, specifically "Cardiopulmonary Bypass Vascular Catheter, Cannula, or Tubing." The "ground truth" in this context refers to established engineering and biocompatibility standards and performance requirements for such medical components, rather than clinical interpretation by medical experts (like radiologists for imaging devices).

The document does not mention the use of experts to establish a "ground truth" for a test set in the way one would for an AI-powered diagnostic device. The "ground truth" for this device's performance is derived from established industry standards, internal product specifications, and regulatory requirements that define acceptable limits for pressure integrity, biocompatibility, etc. The document refers to "product specification" and "rationalization documentation" as the basis for evaluation.

4. Adjudication Method

An adjudication method (like 2+1, 3+1) is typically used in clinical studies where there's a need to resolve discrepancies in expert opinions on imaging or clinical assessments. For this type of device (tubing and connectors), the "adjudication" is based on objective measurement against predefined specifications and standards. There is no mention of human adjudication in the traditional sense for reconciling expert interpretations for a test set.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. MRMC studies are relevant for devices that involve human interpretation, particularly in diagnostic imaging, to assess improvements in reader performance with AI assistance. This device is a passive component for cardiopulmonary bypass and does not involve human interpretation in a diagnostic capacity or AI assistance.

6. Standalone Performance Study

The studies described are essentially standalone performance studies for the device components. The verification and validation testing assesses the "algorithm only" (if one considers the manufacturing process and design as the "algorithm" for a physical device) against predetermined performance specifications. The tests for pressure integrity, spallation, kink resistance, pull force, tubing life, and biocompatibility are all evaluations of the device's inherent performance characteristics without human interaction being part of the primary performance metric.

7. Type of Ground Truth Used

The ground truth used is primarily engineering specifications, material science standards, and biocompatibility standards, as outlined in the "product specification" and various "rationalization documentation" (e.g., Mechanical Requirements, Coating Requirements, Biocompatibility per product specifications). Essentially, the "ground truth" is established industry and regulatory benchmarks for the safety and efficacy of cardiopulmonary bypass components.

8. Sample Size for the Training Set

This document does not mention a "training set" as this is not an AI/machine learning device. The "training" for a physical medical device typically refers to the design, manufacturing process, and quality control procedures, which are developed and refined over time based on engineering principles and previous device iterations. There isn't a "training data" set in the context of an algorithm.

9. How Ground Truth for the Training Set Was Established

As there is no "training set" in the AI/machine learning sense, there is no ground truth established for it. The development and refinement of the device's design and manufacturing processes (analogous to "training" for a physical product) would be based on:

• Engineering design principles
• Material science knowledge
• Previous iterations of similar devices (predicates)
• User feedback
• Regulatory requirements and standards for medical devices.

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The recirculation line is indicated for use in connecting tubing and/ or devices during cardiopulmonary bypass procedures up to 6 hours in duration.

The recirculation line consists of a 0.6 cm (1/4 in) flexible line with Y connector and female luer ports. The recirculation line provides a path from the recirculation port of the Affinity Fusion® Oxygenator with Integrated Arterial Filter to the venous reservoir. It is configured for maximum flexibility to facilitate ease of circuit set up and priming.

The provided text describes the 510(k) submission for the Medtronic Affinity Fusion® Recirculation Line. This device is a cardiopulmonary bypass tubing component, and its approval was based on demonstrating substantial equivalence to a predicate device, not on meeting specific quantitative acceptance criteria derived from a clinical study.

Therefore, many of the typical elements requested in the prompt, such as acceptance criteria tables with performance, sample sizes for test sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance, are not applicable to this type of submission. This is a pre-clinical bench testing submission for a physical medical device, not a software-driven diagnostic or AI device.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The specific quantitative acceptance criteria or detailed performance results (e.g., burst pressure in psi, pull-off force in Newtons) are not disclosed in this summary. The summary only states that these tests were conducted and the device's performance was verified.

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

• Sample Size: Not specified in the summary. Performance tests typically involve a statistically relevant number of samples, but the exact count is not provided.
• Data Provenance: Pre-clinical bench testing. The country of origin of the data is implicitly the United States, given Medtronic's location and the FDA submission. The data is prospective in the sense that the device was manufactured and then subjected to these tests as part of the approval process.

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

• Not Applicable. For mechanical/physical performance tests, "ground truth" is established by direct measurement and observation against engineering specifications, not by expert consensus in a clinical context. The "experts" involved would be engineers and technicians conducting the bench tests and interpreting the results according to validated test methods.

4. Adjudication Method for the Test Set:

• Not Applicable. Adjudication methods like 2+1 or 3+1 are used for interpreting subjective clinical data (e.g., imaging reads). For bench testing, results are typically objective measurements or pass/fail criteria against engineering specifications.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• No. This is a physical medical device, not an AI or imaging-based diagnostic device. Therefore, MRMC studies are not relevant.

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

• No. This is a physical medical device, not an algorithm or software.

7. The Type of Ground Truth Used:

• Engineering Specifications/Validated Test Methods. The "ground truth" for these tests refers to established engineering requirements and validated test protocols for integrity, bursting, and pull-off strength.

8. The Sample Size for the Training Set:

• Not Applicable. This device did not involve a "training set" in the context of machine learning or algorithms. Its design and manufacturing process would involve internal development and testing, but not a dataset for training.

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

• Not Applicable. See point 8.

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