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Carefusion NeutraClear™ Needle-free connector is a bidirectional valve allowing injections and infusions to be given or sample taken via an intravenous line; or samples taken via arterial line. It seals and protects the line when it is not activated. The Carefusion NeutraClear™ needle-free connector may be used with low-pressure power injectors procedures to a maximum pressure of 325psi with a flow at 10mL per second.

Carefusion NeutraClear™ Needle-free connector is a sterile, non-pyrogenic bidirectional needleless injection valve intended for single patient use as an accessory to intravascular administration sets allowing infusions to be given or samples taken via an intravenous line or via arterial line without using a needle, thus eliminating the potential for needle-stick injuries during use. It seals and protects the line when it is not activated. This bidirectional needleless injection valve may be used with low-pressure power injectors to a maximum pressure of 325psi with a flow at 10mL per second. The Carefusion NeutraClear™ can be used for up to 200 activations or 7 days.

The provided document is a 510(k) premarket notification letter and summary for a medical device: the Carefusion NeutraClear™ Needle-free Connector (EL-NC1000). The document describes the device, its indications for use, technological characteristics, and performance data used to demonstrate substantial equivalence to a predicate device (NeutraClear™ EL200).

However, the document does not contain the kind of detailed information about acceptance criteria and study design that would be typical for clinical studies of AI/ML devices, such as:

1. A table of acceptance criteria and reported device performance for specific metrics like sensitivity, specificity, or accuracy.
2. Sample sizes for test sets, data provenance, number/qualifications of experts, or adjudication methods for establishing ground truth in AI/ML performance evaluation.
3. Information on multi-reader multi-case (MRMC) comparative effectiveness studies or standalone algorithm performance.
4. Specifics about training set sample size or how ground truth was established for a training set (as this is not an AI/ML device).

Instead, this document describes the evaluation of a physical medical device (a needle-free connector) through non-clinical performance testing and adherence to recognized standards. The "acceptance criteria" here refer to the successful completion and meeting of requirements outlined in these standards and internal test methods.

Therefore, I will extract the information available in the document regarding the device's performance evaluation, framing it within the context of a physical medical device rather than an AI/ML system.

Acceptance Criteria and Study for Carefusion NeutraClear™ Needle-free Connector (EL-NC1000)

The Carefusion NeutraClear™ Needle-free Connector (EL-NC1000) is a physical medical device, not an AI/ML device. Therefore, the "acceptance criteria" and "study" described in the document refer to non-clinical performance testing against recognized international standards and internal test methods, rather than clinical trials or AI/ML specific performance metrics like sensitivity/specificity derived from ground truth established by experts.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that "The device met the acceptance criteria for all functional, microbial ingress, sterility, biocompatibility and other performance criteria, which verify it to be substantially equivalent to the predicate device." While specific numerical acceptance criteria (e.g., "leakage must be less than X mL/hr") are not explicitly listed in a table, the document refers to recognized standards and internal test methods that define these criteria.

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

This information is not explicitly provided in the document. For non-clinical performance testing of a physical device, sample sizes are typically determined by engineering principles, statistical power for specific tests (e.g., destructive testing, fatigue testing), and regulatory compliance testing requirements for the standards cited (e.g., number of units to test for sterility validation). The data provenance is internal laboratory testing.

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

Not applicable. Ground truth as typically understood in AI/ML (e.g., expert consensus on medical images) does not apply here. The "ground truth" for this device's performance is established by the objective physical and chemical properties of the device and its interaction with fluids and pressure, measured against established engineering and biological safety standards.

4. Adjudication Method for the Test Set

Not applicable, as there is no "ground truth" derived from human interpretation. Performance is assessed through objective measurements and validated test methods.

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

Not applicable. This is a physical medical device, not an AI/ML system requiring human-in-the-loop performance evaluation.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

Not applicable. This is a physical medical device, not an AI/ML system. The "standalone" performance here refers to the device's ability to meet its functional and safety requirements independently, as demonstrated by the non-clinical tests.

7. Type of Ground Truth Used

The "ground truth" for the performance of this physical device is defined by:

• Established engineering principles: Performance under pressure, flow rates, leak resistance, etc.
• Biological safety standards: Biocompatibility, sterility, absence of hemolysis.
• Regulatory standards: Conformity to ISO standards and FDA requirements for medical devices.
• Internal specifications: Defined by the manufacturer for functional parameters.

8. Sample Size for the Training Set

Not applicable. This is a physical medical device, not an AI/ML model that requires a training set.

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

Not applicable. This is a physical medical device, not an AI/ML model.

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Carefusion NeutraClear™ Needle-free connector is a single use, sterile, non-pyrogenic device intended for use as an accessory to intravascular administration sets for the administration or withdrawal of fluids from a patient through a cannula placed in the vein or for withdraw of fluids through the artery. Carefusion NeutraClear™ Needle-free connector may be used with low-pressure power injectors with a flow at 10ml/s, in state of connection.

Carefusion NeutraClear™ Needle-free connector is a bidirectional needleless injection valve. The Carefusion NeutraClear™ Needle-free connector is a single use, sterile, non-pyrogenic device intended for use as an accessory to intravascular administration sets for the administration or withdrawal of fluids from a patient through a cannula placed in the vein or for withdraw of fluids through the artery. Carefusion NeutraClear™ Needle-free connector may be used with low-pressure power injectors with a flow at 10 ml/s, in state of connection.

Carefusion NeutraClear™ Needle-free connector is intended for single patient use in intravenous and blood administration sets without need for needles, thus eliminating the potential for needle-stick injuries during use. The subject device is not intended to treat existing infections. The device is not intended to have any effect on contaminated infusion solutions.

This document describes the regulatory submission (510k) for the Carefusion NeutraClear™ Needle-free connector. This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than providing extensive independent clinical effectiveness studies typical for novel devices.

Therefore, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the testing performed to demonstrate that the modified device (with minor changes compared to the predicate) performs as intended and is as safe and effective as the predicate. The document doesn't detail a traditional clinical study but rather a series of performance and safety tests.

Here's a breakdown of the requested information based on the provided text:

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

The document does not explicitly list "acceptance criteria" alongside "reported device performance" in a quantitative table for each test. Instead, it states that various tests were performed and that the device met the acceptance criteria for all of them. The "reported device performance" is summarized as having met these criteria.

(Note: The specific quantitative results or acceptance thresholds for each test are not detailed in this summary.)

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

The document does not specify the sample sizes used for the individual performance tests (microbial ingress, hemolysis, priming volume/flow rate, etc.). It also does not explicitly state the country of origin of the data or whether the studies were retrospective or prospective. Given the nature of a 510(k) summary for minor device modifications, these details are often kept in the full submission, not the summary.

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)

This type of information (experts, ground truth for test sets) is typically relevant for studies evaluating diagnostic or AI-driven devices, where human expertise is used to define a "correct" answer against which the device is measured. For a medical device like a needle-free connector, which undergoes performance and safety testing, "ground truth" is established by adherence to recognized standards and objective measurements performed in a laboratory setting, not by human expert interpretation. Therefore, this information is not applicable and not provided in the document.

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

Similar to point 3, adjudication methods are relevant for subjective assessments or when discrepancies arise in human interpretation (e.g., in reading medical images). Performance testing of a physical medical device against predefined standards does not involve an adjudication method by human experts. Therefore, this information is not applicable and not provided in the document.

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

MRMC studies and the concept of "human readers improving with AI assistance" are specific to AI/CAD devices. The Carefusion NeutraClear™ Needle-free connector is a physical medical device, not an AI or diagnostic tool. Therefore, an MRMC comparative effectiveness study was not performed, and this information is not applicable.

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

This question is also specific to AI/algorithm performance. The device in question is a physical needle-free connector. Therefore, a standalone algorithm performance study was not performed, and this information is not applicable.

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

The "ground truth" for evaluating the performance of this device is based on objective measurements and adherence to recognized performance standards and guidance, such as ISO 8536-4:2010, ISO 594-2:1998, ISO 8536-10:2004, ISO 10993-1:2009, ISO 11135-1:2007, and ISO 10993-7:2008. These standards define the acceptable physical, mechanical, and biological properties and performance characteristics of such devices. For example, for microbial ingress, the ground truth is whether microorganisms can penetrate the device under specific test conditions, as defined and measured by the test method.

8. The sample size for the training set

The concept of a "training set" is relevant for machine learning or AI models. This device is a physical product, not an AI system. Therefore, there is no training set, and this information is not applicable.

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

As there is no training set for this type of device, this question is not applicable.

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