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This device is intended for use during procedures when a wound or surgical site must be cleared by non-contact means for improved visibility at the site.

The ClearView Blower/Mister includes a hand grip with a 3 1/4" or 6 1/2" malleable stainless steel shaft for ease of positioning the device near the surgical site. The soft, silicone tip contains a plastic tube which carries saline to the tip. The proximal end includes a fluid inlet line which terminates in a locking female luer for connection to the fluid administration set. The gas line, located on the proximal end, has an in-line 0.2 micron filter and terminates in a slip connector for connection to the gas source tubing.

Here's an analysis of the provided text, focusing on acceptance criteria and the study demonstrating that the ClearView Blower/Mister meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not provide specific sample sizes (e.g., number of devices tested, number of repetitions for each test) for the non-clinical performance data. It describes the tests conducted on "this device" (ClearView Blower/Mister) and "the predicate device."

The data provenance is not explicitly stated. Given it's a 510(k) submission, it's highly likely to be internal company testing (Medtronic/DLP) conducted in a controlled laboratory environment. The testing is prospective in the sense that the experiments were designed and executed to evaluate the new device against its predicate and established criteria.

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 to this submission. The tests performed are non-clinical, measuring physical characteristics and performance of the device (force, mist pattern, flow rates). Ground truth was established through direct physical measurement using scientific instrumentation, not through expert consensus or clinical evaluation.

4. Adjudication Method for the Test Set

This information is not applicable. Since the tests are objective physical measurements, there's no need for an adjudication method as would be used for subjective assessments or image interpretation.

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 was no MRMC comparative effectiveness study conducted. This is a non-clinical evaluation of a surgical device, not an AI or imaging diagnostic tool.

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

This is not applicable. The device is a physical surgical instrument, not an algorithm.

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

The ground truth for the non-clinical performance tests was based on objective physical measurements using instruments and controlled experimental setups. This includes:

• Measurement of force exerted by the gas/saline stream.
• Visual/instrumental assessment of mist pattern shape and centering.
• Measurement of air and saline flow rates.

8. The sample size for the training set

This information is not applicable. There is no "training set" as this is not a machine learning or AI-based device.

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

This information is not applicable. As stated above, there is no training set. The "ground truth" for the performance evaluation was established through direct physical measurements of the device's characteristics.

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The indications or intended use for the DLP Octopus™ Tissue Stabilizer and the predicate product, Cardiothoracic Systems, Inc. (CTS) Thoracic Access Platform and Stabilizer are the same. Both are intended for use du ring coronary artery bypass grafting to isolate diseased artery and minimize motion of the beating heart to facilitate the grafting procedure.

The design of the Octopus"" is similar to both predicate products referenced in the Comparison Information Section. It features plastic handle with vacuum tubing connection, malleable stainless steel arm and suction tip similar to the DLP Cardiac Suction Tube product. The "feet" design of the Octopus" is intended to position the anastomosis site between two "feet" for isolation and stabilization control which is the same as the CTS Thoracic Access Platform and Stabilizer.

This document is a 510(k) summary for a medical device (Octopus™ Tissue Stabilizer) and does not contain information about acceptance criteria or a study proving device performance in the way a clinical trial or AI/ML study would. It's a regulatory document demonstrating substantial equivalence to a predicate device.

Therefore, most of the requested information cannot be extracted from this text.

Here's how I can address the parts that are relevant to this type of document:

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

This document does not specify quantitative acceptance criteria or report performance metrics in the way a clinical study would (e.g., sensitivity, specificity, accuracy). Instead, it focuses on demonstrating substantial equivalence to existing predicate devices.

The "acceptance criteria" in this context are implicitly related to the regulatory requirements for showing that the new device is as safe and effective as the predicate device.

Reported Device Performance (Implicit from the document):

The rest of the requested information (sample size, data provenance, number of experts, adjudication method, MRMC study, standalone performance, type of ground truth, training set size, training set ground truth) is not applicable to this 510(k) summary document, as it describes a mechanical device for surgical use and not an AI/ML algorithm or a study involving human readers and a test set. This document relies on comparisons to predicate devices and biocompatibility testing, not on clinical performance metrics in the sense of accuracy, sensitivity, etc., that would require a ground truth or expert evaluation.

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The indications or intended use for the DLP Elongated and Treaded Cuff Retrograde Coronary Sinus Perfusion (RCSP) cannula are the same as the DLP, Research Medical and Sarns 3M marketed RCSP cannula. The cannula are intended for use in perfusing cardioplegia solutions retrograde through the coronary sinus.

The design of the DLP Elongated and Treaded Cuff RCSP cannula is similar to predicate products. Size and shape contain minor differences. Technological characteristics are equivalent. Cuff length and texture differences do not affect flow characteristics.

This document is a "SUMMARY OF SAFETY AND EFFECTIVENESS" for a medical device: the "DLP Elongated and Treaded Cuff Retrograde Coronary Sinus Perfusion (RCSP) cannula."

It does not contain any information about acceptance criteria, device performance metrics, or a study that proves the device meets specific criteria in the way typically expected for a detailed regulatory submission demonstrating new device efficacy or safety.

Instead, this document is a submission to demonstrate substantial equivalence to predicate devices. It explicitly states:

• "The indications or intended use for the DLP Elongated and Treaded Cuff Retrograde Coronary Sinus Perfusion (RCSP) cannula are the same as the DLP, Research Medical and Sarns 3M marketed RCSP cannula."
• "The design of the DLP Elongated and Treaded Cuff RCSP cannula is similar to predicate products. Size and shape contain minor differences. Technological characteristics are equivalent."
• "The materials used for the cuffs and cannula body are silicone which is same as that for DLP and SARNS 3M marketed RCSP devices. Materials have been tested to be biocompatibility acceptable."
• "No difference in Safety and Efficacy. Since materials, indications and technology are the same, no new issues of Safety and Efficacy of the device are introduced."
• "The differences are minor and nonsignificant differences."

Therefore, based on the provided text, I cannot complete the requested table or answer most of the questions because the document's purpose is not to present a new study with specific performance metrics and acceptance criteria. It argues for equivalence based on existing knowledge of predicate devices.

Here's how I would answer based only on the provided text, highlighting the absence of the requested information:

1. Table of acceptance criteria and the reported device performance

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

• Sample size: Not specified. No clinical or performance test data on a "test set" is presented in this summary.
• Data provenance: Not specified. The document relies on the established safety and efficacy of predicate devices, not new data from this specific device.

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. No ground truth for a test set was established as no new performance study is described.

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

• Not applicable. No test set or adjudication method is described.

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

• Not applicable. This document is for a physical medical device (cannula), 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 document is for a physical medical device (cannula), not an algorithm.

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

• Not applicable. No new ground truth was generated as no new performance study is described. The basis for safety and efficacy is "sameness" to existing devices.

8. The sample size for the training set

• Not applicable. This document is for a physical medical device (cannula), not a machine learning model.

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

• Not applicable. This document is for a physical medical device (cannula), not a machine learning model.

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