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TTCF is indicated for the treatment of hypoxemia with delivery of transtracheal high flows of a heated and humidified air/oxygen mixture to self-breathing patients with a cuff deflated fenestrated tracheostomy tube. TTCF is indicated for hospital use in adult patients.

The TTCF Gas Delivery System is a gas supply and humidification system mounted on a medical stand. Components include an oxygen blender, a flow meter, pressure relief valve, humidifier, and pressure monitor. A blended source of compressed air and oxygen allow choosing flow rate and FiO2 of the mixture. Flows are delivered at 6-15 LPM. Oxygen concentrations are available from 21% to 77%.

The provided text describes a 510(k) submission for the CS Medical TTCF Gas Delivery System. This is a medical device, not an AI/ML software. Therefore, the questions regarding acceptance criteria, study details, ground truth, and expert evaluation are not applicable in the context of AI/ML performance.

The document primarily focuses on establishing "substantial equivalence" of the new device to a legally marketed predicate device (Transtracheal Systems, Inc., TTHF-1000, K981078). This involves demonstrating that the new device has the same intended use, similar technological characteristics, and raises no new questions of safety or effectiveness.

Here's a breakdown of the information provided, re-contextualized to the device clearance process:

1. Acceptance Criteria and Reported Device Performance:

The concept of "acceptance criteria" for an AI/ML model's performance (e.g., sensitivity, specificity thresholds) is not relevant here. Instead, the "acceptance criteria" for device clearance are focused on demonstrating:

• Hazard Analysis: Acceptable and mitigated potential hazards (following ISO 14971).
• Electrical Safety: Demonstrated for individual components.
• Effectiveness: Demonstrated for individual components by previous 510(k) clearance (i.e., the components themselves are already proven safe and effective).
• Biocompatibility: Plastic materials meet ISO 10993.
• Substantial Equivalence: The device is designed, labeled, and verified for performance and safety in a manner that makes it substantially equivalent to the predicate device.

Reported Device Performance (against the concept of substantial equivalence):

• Indications for Use: Same as predicate device (treatment of hypoxemia with delivery of transtracheal high flows of heated and humidified air/oxygen mixture to self-breathing adult patients with a cuff deflated fenestrated tracheostomy tube).
• High Flow Oxygenation: Same as predicate (high flow oxygenation for treatment of hypoxemia in self-breathing adult patient populations).
• Heated/Humidified Air-Oxygen Mixtures: Same as predicate.
• Open System Support: Both devices support an open system.
• Flow Rates: Same as predicate (6-15 LPM delivering oxygen mixture up to 77%).

Differences noted but deemed not to impact substantial equivalence:

• Intended Use Environment: TTHF-1000 for home use, TTCF for hospital use.
• System Delivery Pressure: Substantially lower for the TTCF system at the catheter.
• Oxygen Supply: TTCF uses facility piped oxygen, predicate uses an air compressor.

2. Sample Size for Test Set and Data Provenance:

This section is not applicable to traditional medical device clearance. No "test set" in the AI/ML sense (e.g., a dataset of images with ground truth labels) was used. The evaluation involves engineering testing and comparison to an existing device.

3. Number of Experts and their Qualifications:

This is not applicable. The evaluation does not involve clinical experts establishing ground truth for a dataset. The clearance process relies on regulatory experts at the FDA reviewing the manufacturer's provided documentation.

4. Adjudication Method:

This is not applicable. No adjudication of expert opinions on a dataset was performed.

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

This is not applicable. The device is a gas delivery system, not an AI diagnostic or assistive tool for human readers.

6. Standalone Performance Study:

This is not applicable in the AI/ML sense. The "effectiveness" of individual components was "demonstrated... by previous 510(k) clearance," meaning the sub-components had their own standalone performance verified previously. The current submission demonstrates the system's integration and safety.

7. Type of Ground Truth Used:

This concept is not applicable. There's no "ground truth" derived from expert consensus, pathology, or outcomes data in the context of validating an AI/ML algorithm's performance. The "truth" in this context is adherence to safety standards, engineering specifications, and functional equivalence to a predicate device.

8. Sample Size for Training Set:

This is not applicable. The device is not an AI/ML algorithm, so there is no training set.

9. How Ground Truth for Training Set was Established:

This is not applicable for the same reason as above.

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