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The VORTRAN® Cuff Inflator (VCI) is intended to measure and regulate the intra-cuff pressure of Endotracheal tubes, Tracheostomy tubes and Laryngeal Mask Airways (LMAs). The VORTRAN® Cuff Inflator (VCI) is used under medical supervision in hospitals, pre-hospital (EMS), extended care facilities, and outpatient clinics, where a patient may be intubated.

The VORTRAN® Cuff Inflator (VCI) is a disposable, hand-held measuring device intended to measure and manually regulate intra-cuff pressure of Endotracheal, Tracheostomy, and LMA tubes.

The provided text describes the VORTRAN® Cuff Inflator (VCI) and its substantial equivalence determination by the FDA. However, it does not detail a study that defines acceptance criteria and then proves the device meets those criteria in the way typically seen for AI/ML-driven medical devices (e.g., involving AI model performance metrics like sensitivity, specificity, AUC).

This document is a 510(k) summary for a mechanical device, a cuff inflator, not an AI/ML-driven device. Therefore, many of the requested criteria in your prompt (e.g., sample size for test/training sets, experts for ground truth, MRMC studies, standalone AI performance) are not applicable to the information provided in this document.

The "Performance Data" section (Section VIII) states: "Performance testing included manometer accuracy, inflation and deflation functions, and absence of leaks. The performance testing includes a comparison between the VORTRAN® Cuff Inflator (VCI) and its predicate and reference devices, Posey Cufflator and Hospitech AG Cuffill."

Based solely on the provided document, here's an attempt to answer your questions, acknowledging the limitations for a non-AI/ML device:

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

The document provides "Pressure Accuracy and Range" as key performance characteristics. While not explicitly stated as "acceptance criteria" with pass/fail thresholds in the provided text, these are the performance targets the new device aims to match or be equivalent to.

Note: The document states for "Pressure Range": "(1) range has no significant difference, in comparison to its predicate or reference devices, and does not raise different questions of safety and effectiveness." This indicates the 0-60 cm-H2O range was deemed acceptable relative to the predicate/reference devices.

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 in the document. The performance testing is described generally ("Performance testing included manometer accuracy, inflation and deflation functions, and absence of leaks.").
• Data Provenance: Not specified. Given it's a technical performance test, it's likely lab-based and conducted by the manufacturer.
• Retrospective/Prospective: Not applicable in the context of device performance testing in this document.

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/Not specified. The ground truth for manometer accuracy, inflation/deflation function, and leak absence would be established by calibrated instruments and engineering measurements, not human expert consensus, for a mechanical device.

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

• Not applicable. This is not a human-reader study requiring 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

• No MRMC study was done, as this is a mechanical device, 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 is a mechanical device. Its performance is its standalone performance. There is no "algorithm" in the AI sense.

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

• For the performance characteristics mentioned (manometer accuracy, inflation/deflation, leaks), the ground truth would be established by calibrated reference standards and engineering measurements. For example, manometer accuracy would be verified against a highly accurate master pressure gauge.

8. The sample size for the training set

• Not applicable. This is a mechanical device, not an AI model requiring a training set.

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

• Not applicable.

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