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The AS3700 Anesthesia Delivery System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The AS3700 is intended for use by licensed clinicians, for patients requiring anesthesia within a health care facility, and can be used in both adult and pediatric populations.

The AS3700 Anesthesia Delivery System is a device used to administer to a patient, continuously or intermittently, a general inhalation anesthetic and to maintain a patient's ventilation.

The provided text describes a 510(k) summary for the AS3700 Anesthesia Delivery System. This document focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a study with specific acceptance criteria and performance metrics for a diagnostic or AI-driven device.

Therefore, many of the requested elements (acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, training set details) are not applicable or cannot be extracted from this document.

However, I can extract the information relevant to how the device's performance was evaluated for its 510(k) clearance, which is primarily through compliance with recognized standards.

Here's the closest representation based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Device Meets Acceptance Criteria:

The document states that "The AS3700 Anesthesia Delivery System has been tested and found to be in compliance with recognized safety, performance and electromagnetic compatibility standards." This implies a series of engineering verification and validation tests were conducted to ensure the device met the requirements of each listed standard. It also mentions a "risk analysis has been developed to identify potential hazards and document the mitigation of the hazards" and that "The device's software has been verified and validated in accordance with the appropriate test requirements."

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

• Not applicable/Not provided: This is an engineering safety and performance validation, not a clinical study involving human data or a machine learning evaluation. The "test set" would refer to the physical device and its components undergoing testing against engineering standards.

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 provided: Ground truth in this context refers to the defined specifications within the listed industry standards, which are established by expert consensus within standards bodies, not by individual clinical experts for a specific test set. The engineers conducting the tests would be qualified in medical device testing and regulatory compliance.

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

• Not applicable/Not provided: This pertains to clinical diagnostic studies involving reader interpretations, not engineering compliance testing.

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 device is an anesthesia delivery system, not an AI-powered diagnostic or assistive tool.

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

• Not applicable: This device operates with human input (licensed clinicians) and is not a standalone algorithm.

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

• Engineering Standards and Specifications: The "ground truth" for this device's performance is adherence to the technical specifications outlined in the various IEC, ISO, CGA, and ASTM standards listed. These standards represent established best practices and safety requirements for anesthesia delivery systems.

8. The sample size for the training set

• Not applicable: This is not a machine learning or AI device that requires a training set.

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

• Not applicable: This is not a machine learning or AI device that requires a training set.

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The MOVES™ is a portable computer controlled electrically powered emergency transport ventilator intended to provide continuous or intermittent ventilatory support for the care of adults who require mechanical ventilation.

The MOVES™ is intended to deliver high inspired oxygen concentrations via the MOVES™ O2 mask to spontaneously breathing patients who require elevated inspired oxygen.

MOVESTM is intended to be used in a transport or emergency setting on adult patients who weigh between 40 and 120kg.

MOVES™ provides the following supplemental functions for patients that it is ventilating or to whom it is delivering elevated inspired oxygen:

a. Suction
The MOVES™ suction pump is intended for aspiration and removal of fluids, tissue (including bone), gases, bodily fluids or infectious materials from wounds or from a patient's airway or respiratory support system.

b. Supplementary Oxygen
The MOVESTM is intended to provide supplemental oxygen enriched air to patients that require supplemental oxygen.

C. Patient Monitoring
The MOVESTM is intended to monitor physiological parameters of patients and provide these parameters to a health care provider for interpretation in the form of physiological data and system alarms. Physiological data and system alams will be available to the care provider from the monitor.

The MOVES™ is a portable multifunction patient support and monitoring system with the following capabilities:

• Computer controlled, electrically powered circle ventilator intended to provide . continuous or intermittent ventilatory support for the care of individuals who require mechanical ventilation.
• . Delivery oxygen-enriched air that may be supplied from an external oxygen source or generated internal to the system with the on-board oxygen concentrator.
• Patient monitoring functions including the following patient parameters: Pulse . Rate, Noninvasive BP (NIBP), Invasive BP (IBP), SPO2, Temperature, Respiration Rate, CO2, and O2.
• Suction/aspirator pump for medical suction procedures where secretions, blood . and other body fluids must be removed through the application of continuous negative pressure.
  The moves is capable of operating under battery power or external AC supply. It includes a handle and mounting equipment that allows it to attach to a stretcher.

The provided 510(k) summary for the MOVES™ device does not contain specific acceptance criteria in quantitative terms (e.g., minimum sensitivity, specificity, or error rates) or detailed results of a study designed to prove the device meets such criteria. Instead, it relies on a comparison to predicate devices and adherence to recognized standards.

Here's an analysis based on the information provided, outlining what is or isn't present regarding acceptance criteria and performance studies:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for device performance. Instead, it claims substantial equivalence to predicate devices and compliance with various IEC, ISO, ASTM, and ANSI/AAMI standards. The "reported device performance" is described qualitatively as meeting "all of its performance requirements" and being "substantially equivalent" to predicate devices.

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

This information is not provided in the document. The summary refers to "performance testing" but does not detail the methodology, sample sizes (e.g., number of test subjects, test scenarios, or data points), or provenance of any data used in such testing.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not applicable as the document does not describe a study involving expert-established ground truth for a test set. The validation approach is based on demonstrating equivalence to existing devices and compliance with technical standards.

4. Adjudication Method for the Test Set

This information is not applicable as the document does not describe a study requiring a test set with adjudicated ground truth.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or at least not described in this 510(k) summary. The device is not an AI-assisted diagnostic tool that would typically involve human readers.

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

This concept is not applicable in the context presented. The MOVES™ is a medical device for patient support and monitoring, not an algorithm being evaluated for standalone diagnostic or assistive performance. The "performance testing" mentioned refers to the device's functional operation.

7. The Type of Ground Truth Used

The concept of "ground truth" as typically understood in AI/imaging studies (e.g., pathology, expert consensus) is not directly applicable here. For this type of device, the "ground truth" would be the engineering specifications and performance capabilities of the device as measured against recognized standards and the performance of predicate devices. For example, a ventilation parameter's accuracy would be verified against a reference standard or precision instrument, not an expert opinion.

8. The Sample Size for the Training Set

This information is not provided and is not applicable in the context of this device. The MOVES™ device is not described as utilizing machine learning or AI that would require a "training set" in the conventional sense. Its "computer-controlled" nature implies programmatic logic rather than learned models.

9. How the Ground Truth for the Training Set was Established

This information is not applicable as there is no mention of a "training set" or a machine learning component requiring one.

In summary: The 510(k) process for the MOVES™ device focused on demonstrating substantial equivalence to already cleared predicate devices and compliance with relevant industry standards. The summary does not provide specific quantitative acceptance criteria or detailed results from a clinical or performance study with defined sample sizes, expert involvement, or ground truth establishment in the way one would expect for an AI/diagnostic software submission. The "performance testing" mentioned is general and aimed at confirming functional operation and safety against established standards and predicate device performance.

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