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The 7.0 Fr. Endobronchial Blocker is intended for use to differentially intubate a patient's bronchus in order to isolate the left or right lung for procedures which require one-lung ventilation.

The catheter contains a balloon at its distal tip. The proximal end of the catheter is made up of a Y-fitting. One port of the Y-fitting is connected to a pilot balloon assembly. This balloon assembly facilitates inflation of the distal balloon and maintains inflation until it is released. The other port of the Y-fitting connects to the through lumen of the catheter which incorporates a removable looped guide wire that is used to help traverse the catheter along the length of a previously positioned bronchoscope. When the balloon catheter has been advanced to either the right or left bronchus, the guide loop is removed and discarded leaving the through lumen open.

The provided text describes a medical device submission, specifically a 510(k) premarket notification for the 7.0 Fr. Endobronchial Blocker. It details the device's description, indications for use, and a comparison to predicate devices for substantial equivalence. However, this document does not contain the information requested regarding acceptance criteria and a study proving the device meets those criteria, as typically found in reports for AI/ML-driven devices or complex diagnostic systems.

The "Test Data" section only generally states:

The 7.0 Fr. Endobronchial Blocker was subjected to the following tests to assure reliable design and performance under the specified testing parameters. These tests include:

• Performance Testing
• Biocompatibility Testing

The results of these tests provide reasonable assurance that the device has been designed and tested to assure conformance to the requirements for its use as an Endobronchial Blocker.

This is a high-level summary and does not provide the specific quantitative acceptance criteria or detailed study outcomes that would typically be presented for performance evaluation. The device described is a physical medical device (a catheter with a balloon), not an AI/ML software or diagnostic tool that would typically have the kind of performance metrics (sensitivity, specificity, AUROC, etc.) and associated study methodologies requested in the prompt.

Therefore, I cannot populate the table and answer the subsequent questions based on the provided text. The document focuses on regulatory clearance based on substantial equivalence to predicate devices, rather than a detailed clinical performance study with acceptance criteria for a novel diagnostic or AI-assisted function.

To answer your request, here's what would be provided if the document contained the information:

(Hypothetical/Illustrative Table - Not based on the provided text)

Hypothetical/Illustrative Answers to Questions (based on how such a study would be reported, not on the provided text):

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

   • Test Set Sample Size: (e.g., 500 cases)
   • Data Provenance: (e.g., Retrospective, multi-center data from hospitals in the USA, UK, and Germany)

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

   • Number of Experts: (e.g., 3 independent experts)
   • Qualifications: (e.g., Board-certified Radiologists, 10+ years of experience in chest imaging, specializing in [relevant area])

4. Adjudication method for the test set:

   • Adjudication Method: (e.g., 2+1; if two experts agreed, that was the ground truth. If they disagreed, a third senior expert adjudicated the final ground truth. Or, Majority vote if more than 2 experts disagreed).

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:

   • MRMC Study Done: (e.g., Yes)
   • Effect Size: (e.g., Human readers showed a statistically significant increase in diagnostic accuracy of 8% (e.g., from 75% to 83%) when using AI assistance compared to without AI assistance, with a 95% CI of [5%, 11%]).

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

   • Standalone Study Done: (e.g., Yes, the performance metrics in the table above represent standalone algorithm performance.)

7. The type of ground truth used:

   • Ground Truth Type: (e.g., Expert consensus as described in point 4, confirmed by pathology reports for a subset of cases.)

8. The sample size for the training set:

   • Training Set Sample Size: (e.g., 10,000 cases)

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

   • Training Set Ground Truth Establishment: (e.g., Established by consensus of 2 junior radiologists, verified by a senior radiologist for a random 10% subset, supplemented with metadata from electronic health records including pathology and operative reports.)

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