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The CO2 Sample Lines are intended to be used where exhaled gas is monitored. The intended population: Patients requiring expired gas monitoring, adult to pediatrics. The intended environment of use: Hospital-OR, sub-acute, and pre-hospital settings.

Breath gas analysis is commonly performed to provide informatin related to a patient's condition. An example of a gas analysis often performed is capnography using an analyzer called a capnograph. Capnography is the monitoring of the time dependent respirary carbon dioxide(CO2) concentration, which may be used to directly monitor the inhaled and exhaled concentration of CO2, and indirectly monitor the CO2 concentration in a patient's blood. CO2 monitoring of patients respired gases can be used to display of information about CO2 production, pulmonary(lung) perfusion, alveolar ventilation (alveoli are hollow cavities in the lungs in which gas exchange is being performed) and respiratory patterns related to a patient's condition during anesthesia. In breath analysis systems, for example capnograraphy, breath gas can be sampled either by a mainstream or a sidestream analyzer. CO2 Sampling Lines are availabe for CQ2 sampling when mainstream capnography is used, so as to perform a mainstream capnographic measurement of the level of CO2. The CO2 Sampling Line is a sterile, disposable, singlie patient use cannula that allows sampling of patients exhaled gases. It consists of flexible extruded plastic tubes with standard connectors on each end. The cannula is a straight and flexible tube which permits the passage of a fluid such as carbon dioxide through an orifice (a buccal or nasal cavity of a patient). In addition, the CO2 sampling line is adapted used to connect between the patient's end of the breathing system and the distant analyzer, such as the capnograph monitor, along this tube, the patient's breath is continuously sampled.

The provided text is a 510(k) premarket notification for a medical device: a CO2 Sampling Line. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than proving clinical efficacy or the performance of a novel AI algorithm. Therefore, the document primarily describes non-clinical performance testing of the physical CO2 Sampling Line device itself, not an AI model.

Many of the requested details about acceptance criteria for AI models, such as sample sizes for test/training sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, and standalone AI performance, are not applicable to this type of device submission. The device is a physical medical instrument, not an AI or software as a medical device (SaMD).

However, I can extract the acceptance criteria and performance data that are relevant to this physical device based on the provided text.

Acceptance Criteria and Device Performance for CO2 Sampling Line

The device under review is a CO2 Sampling Line, a physical medical instrument. The acceptance criteria and performance are related to its physical and material properties, rather than the performance of an AI algorithm.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and data provenance:
This document describes non-clinical performance testing of a physical device. "Test set" in the context of AI models (i.e., a dataset used to evaluate model performance) is not applicable here. The testing involves physical samples of the CO2 Sampling Line device. The document does not specify the exact number of device samples used for each physical or biological test, but it states "Testing data and results are included in this submission, and demonstrated that the CO2 Sampling Line meets all the pre-determined testing and acceptance criteria." Data provenance is from the manufacturer's internal testing as part of their 510(k) submission, implied to be conducted in China (country of origin of the submitter). The data is retrospective in the sense that it was collected prior to the submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. Ground truth as typically understood for AI models (e.g., expert labels on medical images) is not relevant to the physical characteristics of a CO2 sampling line. The "ground truth" for the device's performance is established by standardized testing protocols (e.g., ISO standards) and measurable physical properties.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not applicable. Adjudication methods are typically used for establishing consensus among human reviewers/experts on data labels for AI model evaluation. For physical device testing, the results are derived from objective measurements per specified test methods.

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 not an AI or software that assists human readers.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
Not applicable. This is not an AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
The "ground truth" for this physical device is defined by international standards (e.g., ISO, ASTM for materials and performance) and pre-determined engineering specifications. For biocompatibility, it's established by recognized biological testing protocols (e.g., ISO 10993 series) against endpoints like cytotoxicity, irritation, and sensitization.

8. The sample size for the training set:
Not applicable. This device is not an AI model that requires a training set.

9. How the ground truth for the training set was established:
Not applicable. No training set for an AI model is involved.

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