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The MaxZero™ extension set with needle-free connector(s) is for single use only. The MaxZero™ extension set with needle-free connector(s) may be used for direct injection, intermittent infusion, continuous infusion or aspiration of drugs, blood and fluids.

The MaxZero™ Extension Sets with Needle-Free Connector(s) are intravascular extension sets intended for single patient use, including pediatrics and immunocompromised patients, for direct injection, intermittent infusion continuous infusion or aspiration of drugs, blood and fluids. The MaxZero™ Extension Sets with Needle-Free Connector(s) are sterile single patient devices that can be used for up to seven (7) days and 200 activations. All extension sets included in this submission are not made from natural rubber latex or DEHP.

The provided text describes a 510(k) premarket notification for a medical device, the MaxZero™ Extension Sets with Needle-Free Connector(s). This type of submission relies on demonstrating "substantial equivalence" to a predicate device, rather than proving independent effectiveness through clinical trials in the same way a new drug or novel medical device might.

Therefore, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the engineering and performance tests performed to demonstrate that the new device (subject device) is as safe and effective as the previously cleared predicate device, despite some differences.

Here's an analysis of the provided information within the framework of your request:

Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated in a quantitative table with corresponding numerical results in the provided document. Instead, the document discusses various performance tests conducted according to established ISO standards and FDA guidance, with a general statement that "All test results met their acceptance criteria." The table provided on pages 5-6 outlines various characteristics of the subject device and compares them to the predicate device, indicating "Equivalence" or "Different" with explanations.

Based on the information, the acceptance criteria are implicitly derived from the relevant ISO standards and FDA guidance documents, which define the expected performance metrics for intravascular administration sets. The "reported device performance" refers to the fact that the device passed these tests.

Implied Acceptance Criteria and Reported Performance (extracted from comparison and performance discussion):

Note: The document explicitly states "Design Control activities have been conducted and have confirmed the different technological characteristics of the proposed device do not raise different questions of safety and effectiveness" for the characteristics where the subject device differs from the predicate (e.g., device length, materials, configurations, physical specifications, filter size, tubing bore, bonding agent, priming volume, vacuum integrity, maximum pressure, shelf life, light resistance of amber tubing). This indicates that the differences were evaluated and found to be acceptable for substantial equivalence.

Study Details (as applicable to a 510(k) for a Class II device)

1. Sample sized used for the test set and the data provenance:

• Sample Size: Not explicitly stated in the provided abstract for each specific test. However, typical non-clinical performance testing for medical devices involved in 510(k) submissions would use a predetermined number of samples for each test type (e.g., n=3, n=5, n=10, or more, depending on the test and statistical rationale).
• Data Provenance: The data is from non-clinical bench testing ("CareFusion performed design verification performance testing"). There is no mention of country of origin for the testing itself, but given it's an FDA submission, the testing would be expected to adhere to international and potentially US-specific standards. The nature of the testing is prospective as it's part of design verification for a new device.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable in this context. This is a non-clinical, engineering/performance study assessing a physical medical device's functional characteristics (e.g., leakage, tensile strength, flow rate, material compatibility). "Ground truth" established by human experts (like radiologists for image analysis) is not relevant to this type of device and study. The "ground truth" here is the pass/fail criteria defined by the recognized consensus standards (e.g., ISO, ASTM, USP) and the device's design specifications.

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

• None. This is not a study involving human interpretation or subjective assessment that would require an adjudication method. The test results are quantitative physical measurements or qualitative pass/fail outcomes against pre-defined engineering and material standards.

4. 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. This is a medical device (intravascular administration set), not an AI/imaging device. Therefore, MRMC studies are not applicable.

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

• Not applicable. As stated, this is a physical medical device, not an algorithm.

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

• The "ground truth" (or more accurately, the acceptance criteria) for this type of device performance study is based on recognized consensus standards (like various ISO standards for medical devices, ASTM standards, USP for particulate matter) and the predicate device's established performance and safety profile. The testing verifies that the subject device meets these established engineering, material, and functional benchmarks.

7. The sample size for the training set:

• Not applicable. There is no "training set" in the context of this traditional 510(k) submission for a physical medical device. This is not an AI/machine learning product. The design and manufacturing process are subject to Quality System (QS) Regulation (21 CFR Part 820), which involves process validation and quality control, but not a "training set" in the computational sense.

8. How the ground truth for the training set was established:

• Not applicable. (See point 7).

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The AirLife Adult Heated Wire Circuit is intended to warm breathing gases before they enter a patient's airway. The AirLife Adult Heated Wire Circuit is used with the adult patient population that requires mechanical ventilation, positive pressure breathing or general medical gases. The product is single use device, non-sterile and used in professional healthcare environments and intra-hospital transport environments under a doctor's supervision and by skilled clinicians. The AirLife Adult Heated Wire Circuit is compatible to the Fisher & Paykel MR850 humidifier.

The heated breathing circuit is intended to deliver and warm breathing gases before they enter the patient's airway. It is provided non sterile for single patient use. The heated breathing circuit is used with Fisher and Paykel heated humidifier.

The provided document is a 510(k) premarket notification for a medical device called the "AirLife Adult Heated Wire Circuit." This type of document is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving a new device's performance against clinical acceptance criteria in the same way a novel device might.

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to engineering and performance tests against recognized standards for breathing circuits and humidifiers, not clinical performance measures like sensitivity, specificity, or reader agreement for an AI diagnostic device.

Here's the breakdown of the information based on the document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance statistics in a pass/fail format typical for a clinical study of an AI device. Instead, it lists the performance characteristics tested and the standards they comply with, implying that meeting these standards constitutes the acceptance criteria. The "reported device performance" is implicitly that the device did meet these standards, as stated in the conclusion.

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

This document does not specify a "test set" in the context of clinical data for AI benchmarking. The tests performed are engineering and performance evaluations of the device itself (e.g., length, resistance, leakage). The document does not provide details on the sample size (number of devices tested), the provenance of the data (country of origin), or whether the testing was retrospective or prospective. These are typically internal validation tests by the manufacturer.

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. This device is not an AI diagnostic tool that requires expert human interpretation to establish ground truth for a test set. The "ground truth" here is defined by the technical specifications outlined in the referenced ISO and IEC standards.

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

Not applicable. There is no human adjudication process involved as this is a technical device performance evaluation against standards.

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 is not an AI-assisted diagnostic device, and therefore, no MRMC study or assessment of human reader improvement with AI assistance was conducted or reported.

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

Not applicable. This is a physical medical device (heated wire circuit), not an algorithm.

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

The "ground truth" for this device's performance is established by the technical specifications and test methodologies outlined in the referenced international standards (e.g., ISO 5367, ISO 8185, IEC 60601-1, ISO 10993 series). The device's performance is measured against these quantitative and qualitative criteria defined by the standards.

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. There is no training set for this type of device.

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The heated breathing circuit is intended to deliver and warm breathing gases before they enter the patient's airway. The heated breathing circuit is used with Fisher and Paykel heated humidifier MR850. The AirLife Infant Single Limb Heated Wire Circuit is intended for use with pediatic population, specifically the neonate (birth to 1 month of age) and infant (greater than 1 month to 2 years of age) pediative subgroups. The product is single use device, non-sterile and used in professional healthcare environments and intra-hospital transport environments under a supervision and by skilled clinicians.

The heated breathing circuit is intended to deliver and warm breathing gases before they enter the patient's airway. It is provided non sterile for single patient use. The heated breathing circuit is used with Fisher and Paykel heated humidifier MR850.

The provided text describes a 510(k) premarket notification for a medical device called the "AirLife Infant Single Limb Heated Wire Circuit." It focuses on demonstrating substantial equivalence to a predicate device. The information required for outlining acceptance criteria and a study proving a device meets them is not fully contained within this document because it is a submission for substantial equivalence, not a detailed clinical study report for a novel device.

However, based on the provided text, I can infer and extract some relevant details pertaining to performance testing and general acceptance principles for this type of device.

Here's an attempt to answer your request using the available information, with clear indications of where information is directly stated versus inferred as typical for a 510(k) submission:

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

The document lists performance characteristics and the relevant standards they were tested against. For a 510(k) submission demonstrating substantial equivalence, the "acceptance criteria" are implied to be meeting the requirements set forth in these standards. The "reported device performance" is a general statement of compliance, rather than specific numerical results.

Regarding the study proving the device meets acceptance criteria:

The document broadly states: "The following tests were performed for the proposed device to support the substantial equivalence decision," and "The test results demonstrate that the device is as safe and effective as the predicate and therefore substantially equivalent to the predicate device." This indicates that a series of performance bench tests were conducted to verify compliance with the listed international standards (ISO, IEC, AAMI). These are typically laboratory-based engineering and material tests, not clinical studies involving human subjects in an "AI" context.

2. Sample size used for the test set and the data provenance

• Sample Size: Not specified in the provided document. For engineering/bench tests, sample sizes would typically be determined by the specific standard's requirements (e.g., n=3, n=5, n=10 per test), but these details are not present.
• Data Provenance: The tests were performed by the manufacturer, CareFusion Inc., in support of their 510(k) submission to the FDA. The country of origin of the data would be the location where CareFusion conducted these tests, which is not explicitly stated but can be inferred as the US based on the company's US address. The data is retrospective in the sense that the tests were completed before the submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This is not applicable to this type of device and study. The testing described involves physical and electrical performance verification against defined standards, not evaluation by human experts or clinical ground truth.

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

This is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies where expert consensus is needed for image interpretation or diagnosis. Bench testing against standards does not typically involve such 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

This is not applicable. This device is a heated breathing circuit, not an AI-powered diagnostic or assistive tool. Therefore, no MRMC study or AI-related comparative effectiveness was conducted or reported.

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

This is not applicable. This device does not involve any algorithms or AI for standalone performance evaluation.

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

The "ground truth" for this device's performance testing is adherence to the technical specifications and safety requirements outlined in the referenced international standards (e.g., ISO, IEC, AAMI). For biocompatibility, it's the results of specific biological assays. For mechanical and electrical properties, it's measurement against defined limits.

8. The sample size for the training set

This is not applicable. The device is a physical medical device (breathing circuit), not a machine learning model. Therefore, there is no "training set" in the context of an AI/ML algorithm.

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

This is not applicable. As stated above, there is no training set for this device.

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