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This product is intended for the aspiration and preparation of medical fluid, not including injection.

The Filter Needle for Single Use is a single use, irradiation sterilized device that is designed to be used for use in conjunction with luer taper infusion sets conforming to EN ISO 80369-7 for the extraction, filtration and configuration of medicinal solutions and is not intended for injection purposes. Filter Needle for Single Use consists of cap, needle cannula, needle hub, sheath and filter. The cap, needle hub and sheath are made of polycarbonate (PC), the needle tube is made of medical stainless steel (SUS304), and filter is made of polyamide (PA).

The needle holder is a 6% standard tapered connector with good connectivity to the infusion apparatus.

The provided text describes the 510(k) premarket notification for a "Filter Needle for Single Use" (K233277) and its substantial equivalence to a predicate device. However, it does not contain information about a study proving that an AI/Software as a Medical Device (SaMD) meets acceptance criteria, nor does it refer to performance metrics typically associated with AI/SaMD (e.g., sensitivity, specificity, AUC).

The document focuses on the substantial equivalence of a physical medical device (a filter needle) based on material, design, performance, biocompatibility, sterilization, and shelf-life testing, primarily against established international standards.

Therefore, I cannot extract the requested information regarding AI/SaMD acceptance criteria and studies from this document. The tables and study details you've asked for (e.g., sample size for test set, data provenance, number of experts, MRMC studies, standalone performance, ground truth establishment for training and test sets) are relevant to the validation of AI/SaMD, but are not present in this clearance document for a conventional medical device.

To directly answer your request based on the provided text, I must state that the information is not available.

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Cathivex®-GV filter units are in-line 0.22um, sterilizing-grade filters for use with intravenously administered aqueous solutions. The filters remove particulates, microbial contamination, and air bubbles in applications where venting and low protein binding membranes are required or desired.

Cathivex®-GV filter units are sterile, non-pyrogenic, single-use filter devices intended for sterile filtration of aqueous solutions for intravenous infusions. Cathivex®-GV filter units are designed with a Female Luer Lok™ inlet and a Male Luer Lok™ outlet. Cathivex®-GV filter units contain a 0.22um Durapore® hydrophilic filter membrane constructed from polyvinylidene fluoride (PVDF) and a 0.03um hydrophobic vent membrane constructed from polytetrafluoroethylene (PTFE). The filter membrane is designed to remove particles, microorganisms, microprecipitates and undissolved powders which are larger than 0.22 um. The vent membrane is designed to prevent air locks and air emboli by automatically venting air introduced upstream. The filter housing material is molded from PVC.

The provided text describes the regulatory clearance of a medical device, the Cathivex®-GV Filter Units, not an AI/ML powered device. As such, the requested information regarding AI/ML-specific acceptance criteria, study methodologies, and expertise for ground truth is not applicable to this document. The document focuses on performance data for a non-AI medical device.

However, I can extract the information relevant to a traditional medical device's performance criteria and testing, as presented in the document:

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

The document states: "The following performance data were provided in support of the substantial equivalence determination. All specified performance requirements were met." It then lists the tests performed, implying that meeting the requirements of these tests constitutes the acceptance criteria. Specific numerical acceptance criteria values are not provided in this summary, only the categories of tests.

2. Sample size 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 exact sample sizes for each test in the summary. It mentions that Merck Millipore Ltd. is located in Ireland, implying that the testing was conducted either there or overseen by them, but doesn't explicitly state the country of origin of the raw data. The studies are described as "bench testing" and "performance data provided in support of the substantial equivalence determination," which generally implies prospective testing conducted for regulatory submission.

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 question is not applicable as this is a physical medical device, not an AI/ML powered device where expert ground truth is typically established for image or data interpretation. The "ground truth" for this device would be defined by validated physical and biological measurement standards and laboratory procedures.

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

Not applicable as this is a physical medical device. Decisions would be based on objective passes/fails against pre-defined test specifications, not on expert adjudication of interpretations.

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-powered device, so MRMC studies and human reader improvement with AI assistance are irrelevant.

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

Not applicable. This is not an AI-powered device. The device's performance (e.g., filtration efficacy, burst strength) is tested directly, not via an algorithm.

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

The "ground truth" for this device's performance testing would be based on established scientific and engineering standards, physical measurements, and biological assays. For instance:

• Bacterial Retention Test: Ground truth is defined by the sterility assurance level (SAL) of 10^-6, determined by standard microbiological methods.
• Filter Integrity/Bubble Point/Water Intrusion tests: Ground truth based on physical principles and instrument readings (e.g., pressure, flow rates) against pre-defined specifications.
• Biocompatibility: Ground truth from standardized assays (e.g., cytotoxicity assays, sensitization studies) following ISO 10993 standards and a comprehensive risk assessment.
• Endotoxin LAL Test: Ground truth from laboratory quantification of endotoxins using Limulus Amebocyte Lysate (LAL) reagents against established limits.

8. The sample size for the training set

Not applicable. This device is not an AI/ML model, so there is no "training set."

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

Not applicable. As there is no AI/ML model, there is no training set and therefore no ground truth establishment for a training set.

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The I.V. extension set with a 0.22 micron air venting filter is indicated for the administration of fluid to a patient's vascular system and for the removal of air and particulate matter.

The MICRO-VOLUME Extension Set product line consists of sterile, single use disposable devices indicated for the administration of fluid to a patient's vascular system and for the removal of air and particulate matter. These intravascular administration sets provide a clinician the ability to increase the distance between the patient and the fluid administration source. The overall set configuration consists of a female Luer connector, non-DEHP microbore tubing, a 0.22 micron hydrophilic filter, and a male Luer lock connector at the distal end of the set. The filter housing also contains a 0.1 micron hydrophobic filter which vents air to the atmosphere. The MICRO-VOLUME Extension Set with a 0.22 micron filter is designed to remove air and particulate matter and has a maximum pressure of 45 psi (2241 kPa). The product is sterile and non-pyrogenic.

The provided 510(k) summary (K113227) is for an intravenous administration extension set, not an AI/ML medical device. Therefore, much of the requested information regarding AI/ML device testing, such as sample sizes for test/training sets, expert ground truth, MRMC studies, and standalone performance, is not applicable to this submission.

The submission focuses on demonstrating substantial equivalence to a predicate device for a physical medical product. The "acceptance criteria" and "study" mentioned refer to non-clinical design verification tests for the physical components of the extension set.

Here's an analysis of the provided information, tailored to the nature of this medical device submission:

1. Table of Acceptance Criteria and Reported Device Performance

The submission states that "All test results meet the acceptance criteria." However, the specific acceptance criteria values for each test are not explicitly detailed in the provided document. The document lists the types of tests conducted.

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

This information is not applicable as the described tests are for physical product components and not for an AI/ML algorithm's performance on a dataset. The tests would involve physical samples of the device components. Data provenance, in this context, would relate to the manufacturing and testing environment, not to patient data.

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

This information is not applicable as the device is a physical product (IV extension set), not an AI/ML device requiring expert consensus for ground truth on patient data. Ground truth for physical tests would involve established engineering standards and validated measurement methods, not clinical experts.

4. Adjudication Method for the Test Set

This information is not applicable for the same reasons as point 3. Physical component tests typically rely on objective measurements against engineering specifications, rather than adjudicating subjective interpretations.

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 information is not applicable as the device is a physical IV extension set, not an AI-assisted diagnostic or treatment device. MRMC studies are specific to evaluating the clinical impact of AI systems on human performance with medical images or data.

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

This information is not applicable as the device is a physical IV extension set and does not involve an algorithm.

7. The Type of Ground Truth Used

For this physical device, the "ground truth" would be established by engineering specifications, international standards (e.g., ISO for Luer connections), and validated laboratory test methods. The tests (Bond Strength, Bond Pressure, ISO Luer, Biocompatibility) aim to ensure the device meets these pre-defined physical and safety criteria.

8. The Sample Size for the Training Set

This information is not applicable as the device is a physical IV extension set and does not involve an AI/ML training set. Design and manufacturing processes would involve samples for quality control and process validation, but this is distinct from AI/ML training data.

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

This information is not applicable for the same reasons as point 8.

Summary for K113227 (MICRO-VOLUME Extension Set):

This 510(k) submission is for a conventional Class II medical device – an intravenous administration extension set. The "acceptance criteria" and "study" refer to a series of non-clinical, benchtop, and biocompatibility tests designed to demonstrate the physical and safety performance of the device and its substantial equivalence to a predicate device. The document states that all conducted tests met their respective acceptance criteria, confirming the device's appropriate design for its intended use. There is no AI/ML component to this device, so questions related to AI/ML specific testing methodologies are not relevant.

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The ArteriA Blood Filter is intended for use as an accessory in the administration of blood, blood components or solutions into a patient's vascular system through a venous access device.

The ArteriA Blood Filter device is a blood transfusion filter and drip chamber connected to flexible medical grade tubing having a connector on each end. The input side to the dripchamber/filter has a three-way stopcock valve that has both a male and female Luer connections available for use. The outlet of the drip-chamber/filter has a male Luer connector that facilitates connection to a venous access device such as a catheter or sheath. It may also be connected to another stopcock.

The provided text is for a 510(k) premarket notification for a medical device called the "ArteriA Blood Filter," which is a blood administration filter. It describes the device, its intended use, and states its substantial equivalence to a predicate device.

*However, this document does not contain any information regarding acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert involvement for the purpose of demonstrating performance.

The 510(k) summary provided here focuses on administrative details, device description, intended use, and comparison to a predicate device to establish substantial equivalence based on design, materials, and function, rather than a detailed performance study proving specific acceptance criteria.

Therefore, I cannot populate the requested table and answer the study-related questions based on the provided text. The document states: "The basic technologies, design and function of ArteriA Medical Science, Inc.'s ArteriA Blood Filter are substantially equivalent in design, materials of construction, and intended us to the predicate device." This indicates that the regulatory submission primarily relied on demonstrating equivalence to an already approved device rather than a de novo performance study against specific acceptance criteria.

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Removal by in-line filtration of inadvertent contaminants (including bacteria, particulates, and entrained air) from infused intravenous fluids.

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The provided text is a 510(k) clearance letter from the FDA for a medical device called "Pall Supor AEF™ Filter." This type of document does not contain the information requested in the prompt regarding acceptance criteria, device performance studies, sample sizes, expert qualifications, or ground truth establishment relevant to AI/ML device performance.

The 510(k) clearance process is primarily about demonstrating substantial equivalence to a predicate device already on the market, not about establishing specific performance metrics through detailed studies as would be required for an AI/ML diagnostic or assistive device.

Therefore, I cannot provide the requested information from the given text.

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The 0.2 µ Bacterial Filter can be used with administration sets or extension sets for removal of particulate matter during the administration of fluids or medications.

The purpose of this submission is to offer an 0.2 u Bacterial Filter with standard luer connections for use with administration sets or extension sets used with fluid delivery devices. The subject device is intended to be "added-on" to an administration set or extension set.

The filter is an air-eliminating filter and is circular in shape with a center vent. The inlet of the filter is a standard female luer and the outlet of the filter is a standard male luer. The filter membranes are enclosed within a plastic case which is approximately 1.22 in. (width) x 1.85 in. (length).

The provided 510(k) summary for the 0.2 µ Bacterial Filter by SIMS Deltec, Inc. primarily describes a device comparison rather than a detailed study with acceptance criteria and specific performance metrics in the way a diagnostic AI/ML device would be evaluated. This medical device submission is from 1997, and the regulatory requirements and types of studies for devices like this were different than those for modern AI-driven devices.

Here's an analysis based on the provided text, highlighting the information that is present and noting what is absent:

1. Table of Acceptance Criteria and Reported Device Performance:

The submission does not contain a table with explicit acceptance criteria (e.g., a specific bacterial retention rate or flow rate threshold) and reported device performance results against those criteria. Instead, it makes a general statement about functional testing and biocompatibility.

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

• Sample Size: Not specified. The document mentions "Functional testing was performed on the filter," but does not provide details on the number of filters tested or the amount of fluid/particulate matter used.
• Data Provenance: Not specified. The testing was presumably conducted by SIMS Deltec, Inc., but the location of the testing or origin of materials is not detailed. It is retrospective, as the testing was completed prior to submission.

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

Not applicable. This device is a filter, and its performance is evaluated through physical and biological testing (e.g., filtration efficiency, biocompatibility), not through expert interpretation of data.

4. Adjudication Method for the Test Set:

Not applicable. As noted above, this device is not evaluated by human experts interpreting data.

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

No, an MRMC study was not done. This type of study is relevant for diagnostic devices where human readers interpret medical images or data. The 0.2 µ Bacterial Filter is a physical device, not an interpretative diagnostic tool.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Not applicable. This is not an AI/ML algorithm. The performance of the filter itself, as a physical object, is what was tested.

7. Type of Ground Truth Used:

The "ground truth" for this device would be established by validated laboratory methods for assessing filtration efficiency (e.g., bacterial retention tests, particulate removal tests) and standardized biocompatibility assays. The document states:

• "Functional testing was performed on the filter to establish its operating parameters."
• "Biocompatibility testing was conducted on the filter."
  This implies that the ground truth was based on these specific, objective laboratory measurements.

8. Sample Size for the Training Set:

Not applicable. This device is not an AI/ML algorithm, so there is no training set in the conventional sense. The "training" or development of the filter would involve engineering design and material selection, followed by testing.

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

Not applicable, as there is no training set. The design of the filter (likely based on material science and fluid dynamics principles) would be iterated and refined through a series of internal tests, but these are not explicitly detailed as "ground truth" establishment for a training set.

Summary of the Study and Device Proof:

The submission outlines that the device meets its intended purpose based on functional testing and biocompatibility testing. The core of the proof is the demonstration that:

• Functional Testing: The filter "functions according to specification," meaning it effectively removes particulate matter as advertised. While specific percentages or particle sizes are not given, the claim of a "0.2 µ Bacterial Filter" implies it can filter particles down to that size, which would have been demonstrated by the functional tests.
• Biocompatibility Testing: The filter "meets the biocompatibility requirements," indicating it is safe for human contact and use without adverse biological reactions.

The submission specifically states: "Clinical studies were not deemed necessary regarding the filter due to its similarity in materials, design and function to current commercially available filters and extension sets with in-line filters." This is a key point, as it allowed SIMS Deltec, Inc. to rely on substantial equivalence to predicate devices rather than conducting extensive clinical trials, which would typically be required for novel device types or those with significant differences in performance or safety. The 510(k) process is fundamentally about demonstrating substantial equivalence to a legally marketed predicate device. By showing similar materials, design, and function, they could leverage the established safety and effectiveness of the predicate.

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Per FDA Safety Alert: Hazards of Precipitation Associated with Parental Nutrition, issued April 18, 1994, an IV filter is indicated for use when infusing either central or peripheral parenteral nutrition admixtures. Both pore sizes of filters are being offered. a 0.22um air eliminating filter for nonligid containing admixtures, and a 1.2um air eliminating filter for lipid containing admixtures.

Not Found

This document is a 510(k) summary for a medical device called AutoPrime™ I.V. Filter and set. It does not contain the information requested in your prompt regarding acceptance criteria and study details for a device's performance, especially for AI/algorithm-based devices.

The document focuses on:

• Device Identification: Trade name, common name, classification, contact person.
• Predicate Device Comparison: Stating that the AutoPrime™ is as safe and effective as two other named I.V. administration sets.
• Intended Use: Filtering intravenous solutions, specifically mentioning parenteral nutrition admixtures based on an FDA Safety Alert.
• Technological Characteristics: Comparing the 0.22um and 1.2um filters to their predicate counterparts, noting similarities in bacterial/Candida retention claims and materials of construction.
• Lack of Bench Test Data Requirement: Stating that bench test data is "not required due to there being no technological differences that raise issues of safety or efficacy."

Therefore, I cannot provide the requested information (acceptance criteria, device performance table, sample sizes, ground truth details, expert qualifications, adjudication methods, MRMC studies, standalone performance, training set details) from this document. This document is a regulatory submission focused on demonstrating substantial equivalence to predicate devices, not on detailed performance validation studies as typically conducted for novel AI/machine learning devices.

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