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The Magellan-2200, Model-3 Anesthesia Machine is intended/indicated for spontaneous or manually assisted ventilation of patients during anesthesia. It may be used for the delivery of gases and anesthetic vapor. It is capable of monitor/alarm functions for oxygen concentration, breathing pressure and source oxygen pressure.

The Model-3 is a gas machine for anesthesia or analgesia. The device consists of the following components: an inlet gas manifold for oxygen and air; pressure gauges for oxygen and air; a low-pressure alarm for inlet oxygen surveillance; an oxygen analyzer and monitor; an oxygen flow selector for nasal cannula or oxygen mask for pre- and post-anesthesia use; an oxygen flush button; oxygen and air flowmeters; an agent-specific vaporizer; a common gas outlet; a carbon dioxide absorber with one way valves; and a reservoir bag/pressure gauge/pressure relief/scavenger outlet arm.

This document is a 510(k) summary for a medical device (anesthesia machine) and does not contain information related to acceptance criteria, device performance metrics, or study details as one would find for an AI/ML-driven device.

Therefore, I cannot provide the requested information. The provided text describes a modification to an existing anesthesia machine and seeks to demonstrate substantial equivalence to predicate devices, rather than presenting a performance study against specific acceptance criteria for an AI model.

The document discusses:

• Device Name: Magellan-2200, Model-3 Anesthesia Machine
• Intended Use: Spontaneous or manually assisted ventilation, delivery of gases and anesthetic vapor, monitor/alarm functions for oxygen concentration, breathing pressure, and source oxygen pressure.
• Technological Characteristics: Lists components like inlet gas manifold, pressure gauges, oxygen analyzer, flowmeters, vaporizer, CO2 absorber, etc.
• Substantial Equivalence: States the Model-3 has the same intended use and similar indications, principles of operation, and technological characteristics as predicate devices.

There is no mention of:

• Acceptance criteria for device performance (e.g., accuracy, sensitivity, specificity for diagnostic functions).
• Any study performed to demonstrate meeting such criteria.
• Sample sizes, data provenance, ground truth establishment, expert adjudication, or MRMC studies.
• Standalone algorithm performance.

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