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A chemical indicator for monitoring all cycles within the STERRAD® 100S (Standard & Long), 200, 100NX (Standard, Duo, Flex & Express), NX (Standard & Advanced), STERIS® V-PRO® 1 Plus (Lumen & Non-lumen), V-PRO® maX (Flexible, Lumen & Non-lumen) and Sterilucent™ PSD-85 (Lumen & Non-lumen). The VH2O2 Indicators are intended to be used by health care providers with sterilization wraps, cassettes, or pouches to distinguish between processed and unprocessed units. Colors other than blue such as yellow/green should be treated as a process failure.

The Crosstex VH2O2 Chemical Indicators are intended for use as process indicators for all vaporized hydrogen peroxide cycles in the STERRAD® 100S, 200, 100NX (Standard, Duo, Flex & Express), NX (Standard & Advanced), STERIS® V-PRO® 1, V-PRO® 1 Plus, V-PRO® maX, and Sterilucent™ PSD-85 sterilization processes. The Crosstex VH2O2Chemical Indicators are intended to be used by health care providers with articles such as sterilization wraps, containers, cassettes, or pouches to distinguish between processed and unprocessed units. Chemical indicators change to a color of blue after exposure to vaporized hydrogen peroxide. Colors other than blue such as yellow/green should be treated as a process failure.

This document describes the Crosstex VH2O2 Chemical Indicators, a device designed to monitor vaporized hydrogen peroxide sterilization cycles. The information provided outlines the device's acceptance criteria and the studies conducted to prove its performance.

Acceptance Criteria and Reported Device Performance

Detailed Study Information:

1. Sample size used for the test set and the data provenance:
   The document does not specify a distinct "test set" sample size in terms of number of indicators. The testing involves subjecting the indicators to specific sterilization cycles (e.g., STERRAD® 100NX™ DUO) and then evaluating their performance, color change, and stability. The data provenance is not explicitly stated in terms of country of origin, but the testing was conducted by Crosstex International, Inc., a U.S. company. The studies appear to be prospective, laboratory-based tests designed to evaluate the physical and chemical properties of the indicators under controlled conditions.

2. 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 device (chemical indicator) does not typically involve human expert interpretation for "ground truth" establishment in the way an AI diagnostic algorithm would. The "ground truth" for these tests is based on objective, measurable changes in the indicator's color and stability following exposure to defined sterilization conditions, and compliance with established international standards (ISO 11140-1:2014). The assessment would likely be performed by trained laboratory personnel or quality control specialists rather than medical experts.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
   Not applicable. The assessment criteria are objective (e.g., "Color change to blue," "No significant color change"). There is no mention of a subjective evaluation process requiring adjudication.

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:
   Not applicable. This device is a chemical indicator, not an AI-assisted diagnostic tool for human readers. Its function is to provide a direct visual indication of sterilization processing, not to interpret complex medical images or data.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
   This device is not an algorithm. Its performance is observed directly by human users (healthcare providers) who visually assess the color change of the indicator. The "standalone" performance here refers to the intrinsic chemical and physical response of the indicator itself, which is what the non-clinical tests evaluate.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
   The ground truth is based on the objective physical and chemical reaction of the indicator when exposed to vaporized hydrogen peroxide under specific, controlled sterilization conditions, as defined by international standards (ANSI/AAMI/ISO 11140-1:2014) and verified by direct observation in laboratory settings.

7. The sample size for the training set:
   Not applicable. This device is a physical chemical indicator, not a machine learning or AI algorithm that requires a training set.

8. How the ground truth for the training set was established:
   Not applicable, as there is no training set for this type of device.

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A chemical indicator for monitoring all cycles within the STERRAD® 100S (Standard & Long), 200, 100NX (Standard, Flex & Express), NX (Standard & Advanced), STERIS® V-PRO™ 1, V-PRO" 1 Plus (Lumen & Non-lumen), V-PRO® maX (Flexible, Lumen & Non-lumen) and Sterilucent™ PSD-85 (Lumen & Non-lumen). The VH2O2 Indicators are intended to be used by health care providers with sterilization wraps, containers, cassettes, or pouches to distinguish between processed and unprocessed units. Colors other than blue such as yellow/green should be treated as a process failure.

The SPSmedical VH2O2 Indicators are single use process indicators which are cleared for use in verifying exposure to all vaporized hydrogen peroxide cycles in the STERRAD® 100S, 200, 100NX, NX, STERIS® V-Pro 1, V-Pro 1 Plus, and V-Pro maX Testing has been performed which validated the SPSmedical VH2O2 Indicators for use in the Sterilucent PSD-85 Sterilizer.

Indicators will identify if an item has seen H2O2 during the Sterilucent PSD-85 sterilization processes by changing to a Blue signal color. They provide a visual indication to help distinguish between processed and unprocessed items.

Here's a breakdown of the acceptance criteria and study information for the SPSmedical VH2O2 Indicators, based on the provided document:

This document is a 510(k) Pre-market Notification, which focuses on demonstrating substantial equivalence to an already legally marketed device (the predicate device). Therefore, the "acceptance criteria" and "device performance" are primarily framed in terms of equivalence to the predicate and compliance with relevant standards, rather than specific performance metrics against a clinical gold standard in an AI context. Similarly, the "study" described is a non-clinical verification and validation testing, not a typical clinical trial.

Acceptance Criteria and Reported Device Performance

The core acceptance criterion for this 510(k) submission is that the proposed device (SPSmedical VH2O2 Indicators) is substantially equivalent to its predicate device (SPSmedical VH2O2 Indicators cleared under K110152), particularly for the added indication for use with the Sterilucent PSD-85 sterilizer.

The device's performance is demonstrated through its ability to meet the requirements of relevant standards and its consistent function in specified sterilization processes, mirroring the predicate device.

Study Details

Given this is a 510(k) for a chemical indicator (a relatively low-risk device), the "study" is primarily non-clinical verification and validation testing, not a clinical trial involving human patients or complex data interpretation.

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

   • Test Set Sample Size: "Multiple lots of indicators with various levels of shelf life were included in testing." No specific number is provided, but it implies a sufficient number of indicators for robust testing across different manufacturing batches and ages.
   • Data Provenance: The testing was "performed as a result of a Failure Mode and Effects Analysis (FMEA)" and included "simulated use in the Sterilization processes." This indicates laboratory-based, controlled testing simulating real-world conditions, likely in the US (where the submitter is based and FDA is located). It is retrospective in the sense that the testing was performed on manufactured devices.

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

   • No external human experts were explicitly mentioned for interpreting the results of the chemical indicator itself. The ground truth for a chemical indicator is its visual color change according to a known chemical reaction. The "ground truth" for the test set is established by running controlled sterilization cycles (complete vs. incomplete/failure conditions) and observing if the indicator changes color as expected. This involves standard laboratory practices and instrument calibration.
   • The "experts" would be the scientists or engineers performing the testing and confirming compliance with ISO standards and expected color changes. Qualifications are not specified but would include expertise in sterilization processes and chemical indicator testing.

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

   • Not applicable in the conventional sense for image interpretation or diagnosis. The endpoint is a distinct, observable color change (initial color to blue, or other colors for failure). This is a direct chemical reaction, not a subjective interpretation requiring adjudication.

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 physical chemical indicator, not an AI-powered diagnostic device. Therefore, no MRMC study, human reader improvement with AI, or effect size is relevant or reported.

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

   • Yes, in concept. The "device" in this context is the physical chemical indicator, which performs its function autonomously by reacting to chemical exposure (without human interaction to "run" the function). Its "performance" is its inherent color change. Humans then interpret this change. The testing validates this standalone performance.

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

   • For the chemical indicators, the ground truth for testing performance is derived from:
     • Controlled Sterilization Conditions: Exposure to known complete and incomplete vaporized hydrogen peroxide sterilization cycles, as defined by the sterilizer's parameters and industry standards (e.g., partial cycles simulating failure).
     • Standard Reference: Compliance with requirements of ANSI/AAMI/ISO 11140-1 for Process Indicators. The expected color change (e.g., initial pink/yellow to blue) is the predefined correct response.

7. The sample size for the training set:

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

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

   • Not applicable. (See answer to #7).

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The SPSmedical SporView® Plus Steam BI Test Pack with STEAMPlus Integrator is indicated for use in routine monitoring and sterilizer qualification testing of steam gravity displacement cycles at 121°C/250°F for 30 minutes exposure time and for use in pre-vacuum steam sterilization cycles at 132°C/270°F for 4 minutes exposure time.

The SporView® Plus BI Test Pack is a single use device designed to assess the effective performance of both gravity displacement and pre-vacuum steam sterilization processes. It consists of layers of paper with a biological indicator and a load record card with chemical integrator placed in the center and all placed within an exterior containment box. A process indicator label placed on the containment box alerts users if a pack has been exposed to the sterilization process. The approximate dimensions of the pack are 4-5/8" x 7/8" x 6-1/4". The load record card is used to record all the detailed information from the sterilization cycle. The subject device replaces the biological indicator in the predicate device with the SporView® 10 Steam Self Contained Biological Indicator.

The document describes substantiation for a 510(k) submission for a medical device called "SporView® Plus BI Test Pack." This device is a biological sterilization process indicator. The submission is not for a new device, but for a modification to an existing one (K051173), specifically replacing the biological indicator within the test pack.

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

Acceptance Criteria and Reported Device Performance

Study Details

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

   • Sample Size: The document does not specify a precise numerical sample size for the test set. It mentions "running test packs and control packs (predicate) within the same cycles" for various conditions (pass, fail, partial).
   • Data Provenance: The testing was non-clinical, conducted by SPSmedical Supply Corp. in Rush, NY, USA. The study followed the FDA Guidance document for Industry and FDA Staff entitled, "Biological Indicator (BI) Premarket Notification [510(k)] Submissions," issued on October 4, 2007.

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

   • This is a non-clinical study involving a biological indicator device. The "ground truth" is established by the known conditions of the steam sterilization cycles (e.g., specific temperature and time exposures designed to cause a "pass" or "fail" condition), and the subsequent growth or non-growth of the bacterial spores. There are no human "experts" establishing ground truth in the context of interpreting images or clinical outcomes.

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

   • Not applicable to this type of non-clinical device testing. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where human interpretation of data (e.g., medical images) requires consensus among multiple readers.

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, a multi-reader multi-case comparative effectiveness study was not conducted. This device is a biological indicator for sterilization processes, not an AI-powered diagnostic or assistive tool for human readers.

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

   • Yes, this is effectively a standalone device performance study. The "algorithm" here is the biological and chemical reaction of the indicator to sterilization conditions. Its performance is evaluated independently of human interpretation, although humans observe the results (e.g., color change, bacterial growth).

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

   • The ground truth is based on pre-defined physical and biological parameters of steam sterilization cycles. The cycles are intentionally set up as "pass" (full sterilization conditions), "fail" (insufficient sterilization conditions), or "partial" (borderline conditions) based on established scientific principles for sterility assurance and industry standards (e.g., AAMI). The "truth" of whether the spores should be inactivated is determined by these controlled cycle parameters, and then the BI's ability to reflect this is assessed.

7. The sample size for the training set:

   • This is not an AI/machine learning device, so there is no training set in the conventional sense. The "training" or development of such a biological indicator involves extensive research into microbial resistance, material science, and sterilization physics, but not data-driven machine learning.

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

   • As stated above, there is no training set for this type of device. The ground truth for biological indicators is established through fundamental microbiology and sterilization science principles.

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The AirView™ II Bowie Dick Test Pack is intended for the daily air removal efficacy testing of prevacuum steam sterilizers. It may also be used after sterilizer installation, relocation, after major repairs and after sterilization process failures.

The AirView" II Bowie Dick Test Pack is designed to detect the presence of residual air in prevacuum steam sterilizers operating at 134°C for 3.5 minutes. The indicator sheet within the AirView II Bowie Dick Test Pack will demonstrate a uniform color change from blue to dark brown black when proper sterilization conditions are met and no air is present. If enough air is present to create a 2°C (+1° /-0°C) temperature difference between the center of the towel pack. as identified in ANSVAAMI/ISO 11140-5, and the drain temperature at the beginning of the final one minute of a three and half minute cycle the AirView" II Bowie Dick Test Pack will demonstrate a non-uniform color change.

Functionality-The AirView™ II Bowie Dick Test Pack is designed for routine testing of 134°C ' (273°F) prevacuum steam sterilizers. The Bowie Dick test is part of the daily release criteria for any prevacuum steam sterilizer. It may also be used after sterilizer installation, relocation, malfunction, after major repairs and after sterilization process failures. The AirView™M II Bowie Dick Test Pack should always be run in an empty chamber.

Scientific Concepts-The Bowie Dick Test should be run only after the chamber has been preheated. It is a means of detecting air leaks in gaskets or chamber piping, poor air removal and subsequent steam penetration. The AirView™ II Bowie Dick Test Pack has proven safe and effective as a replacement for the standard Bowie Dick Towel Pack through validated performance testing.

Physical Characteristics-The AirView™ II Bowie Dick Test Pack consists of layers of paper with an air removal indicator placed in the center of the stack all placed within an exterior containment box. A process indicator label placed on the containment box alerts users if a pack has been exposed to the sterilization process. The approximate dimensions of the pack are 3-3/4" x 5/8" x 5". The air removal indicator within the AirView™ II Bowie Dick Test Pack should be retained as a permanent record while the remainder of the pack can be discarded with regular waste according to local legislation, recycling land filling or incineration. None of the AirView™ II Bowie Dick Test Packs components are made from lead.

Performance Characteristics-The AirView™ II Bowie Dick Test Pack performs substantially equivalent to the AAMI Standard Towel Pack when tested in conformance with the FDA guidance document for Chemical Indicators and ANSI/AAM1/ISO 11140-5.

Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions "multiple lots of indicators" were used for testing. However, it does not explicitly state a specific numerical sample size for the test set.

The provenance is implied to be laboratory-based testing conducted by the manufacturer (SPSmedical Supply Corp.) in the U.S.A., following FDA guidance. It's a prospective study designed to validate the device's performance.

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

Not applicable. This device is a chemical indicator, and its "ground truth" is established through physical and chemical reactions under controlled sterilization conditions, rather than expert interpretation of complex data (like medical images). The "ground truth" for pass/fail cycles is defined by temperature differences and air removal efficacy within the sterilizer, measured by instrumentation, not human experts.

4. Adjudication Method for the Test Set:

Not applicable. The "adjudication" is based on the visual color change of the indicator and objective physical measurements (temperature, vacuum) within the sterilizer during the validation process. The determination of "uniform" vs. "non-uniform" color change for pass/fail conditions is a direct observation of the indicator's performance against predefined criteria, not a consensus among experts.

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

No, an MRMC comparative effectiveness study was not done. This type of study is typically relevant for interpretative devices where human readers are involved (e.g., AI-assisted diagnosis). The AirView™ II Bowie Dick Test Pack is a chemical indicator that produces a direct visual result.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done:

Yes, the testing described is a standalone performance assessment of the device itself. The chemical indicator operates independently to display a visual outcome (color change) based on environmental conditions within the sterilizer. There is no "human-in-the-loop" component in its direct function, although a human is required to interpret the final visual output.

7. The Type of Ground Truth Used:

The ground truth used is primarily physical and chemical measurements under controlled conditions, established by:

• Defined sterilizer cycle parameters (e.g., 134°C for 3.5 minutes).
• Objective measurements of air removal and steam penetration (e.g., temperature differences within the test pack and at the drain, vacuum levels).
• Compliance with recognized standards (ANSI/AAMI/ISO 11140-5).

Specifically, "pass cycles" and "fail cycles" were experimentally created and defined by these physical conditions.

8. The Sample Size for the Training Set:

Not applicable. This device is a passive chemical indicator, not an AI/ML algorithm that requires a "training set" in the conventional sense. The "training" or development of the indicator's chemical formulation would involve laboratory research and development, but not a data-driven training set like those for AI.

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

Not applicable, as explained in point 8. The "ground truth" for the development of such an indicator would be established through chemical principles and laboratory experiments to ensure the indicator ink responds predictably and accurately to specific sterilization parameters (temperature, steam, air presence).

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The following Crosstex® Isofluid Plus Surgical Masks are intended for use in infection control practices to minimize contamination caused by inhaled and exhaled microorganisms and reduce the potential exposure of the wearer to blood and body fluids. (non-sterile)

• Crosstex® Isofluid Plus Surgical Earloop Face Mask Blue .
• Crosstex® Isofluid Plus FogFree Surgical Earloop Face Mask Blue .
• Crosstex® Isofluid Plus FogFree Surgical Earloop Face Mask with Splash Visor Blue .

The Crosstex Isofluid Plus Surgical Masks are constructed of a cellulose inner facing, a 100% Spundonded porypropyitent elastic loops. The nose piece for the polypropyiene inter firedia, with non facil cae no fog strip (if applicable) is made of melt blow polypropylene.

The provided text describes the acceptance criteria and performance of Crosstex® Isofluid Plus Surgical Masks, focusing on non-clinical tests to demonstrate substantial equivalence to a predicate device.

Here's the information extracted and organized:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The "Acceptance Criteria" column is derived from the reported performance of the predicate device, as the submission states that the new device meets "all relevant requirements of the aforementioned test standards" and is "substantially equivalent." Typically, substantial equivalence is established by meeting or exceeding the performance of the predicate device for relevant parameters.

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

The document does not explicitly state a separate "test set" in the context of a dataset for an AI/ML device. Instead, the performance evaluation is based on bench testing of the physical masks.

• Fluid Resistance (ASTM 1862): "32 of 32 pass at 80mm Hg" for the new device, suggesting a sample size of 32 units tested. The predicate device had "30 of 32 pass at 80mm Hg," also implying 32 units tested for the predicate.
• Other tests (PFE, BFE, Flammability, Delta-P): Specific sample sizes are not explicitly stated for these tests within the provided text, but they would typically involve multiple samples to ensure statistical validity.
• Data Provenance: The data provenance is from non-clinical laboratory bench testing conducted to evaluate the physical and performance characteristics of the surgical masks. There is no information about the country of origin of the data beyond the submitter's identification in New York, USA. The nature of these tests makes them prospective in the sense that they are performed on manufactured products for regulatory submission.

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

This information is not applicable to this submission. The device is a physical surgical face mask, and its performance is evaluated through standardized bench tests (e.g., fluid resistance, particulate filtration). There is no "ground truth" in the context of expert consensus, pathology, or clinical outcomes that would require human experts to interpret data for the test set.

4. Adjudication Method for the Test Set

This information is not applicable as the evaluation relies on objective, standardized physical performance tests rather than subjective human interpretation requiring 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 information is not applicable. This submission is for a physical medical device (surgical face mask), not an AI/ML-driven diagnostic or image analysis system. Therefore, an MRMC study and the concept of "human readers improving with AI" are irrelevant to this device.

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

This information is not applicable. This is a physical product, not an algorithm.

7. The Type of Ground Truth Used

The "ground truth" for the performance evaluation of these surgical masks is established by standardized laboratory test methods (e.g., ASTM 1862 for fluid resistance, ASTM F2299 for particulate filtration, ASTM F2101 for bacterial filtration, 16CFR1610 for flammability, and Mil M36954C for Delta-P). These methods define objective criteria and measurements to determine the performance against established industry standards and the predicate device's performance.

8. The Sample Size for the Training Set

This information is not applicable. There is no "training set" as this is a physical device, not an AI/ML algorithm.

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

This information is not applicable. As there is no training set, there is no corresponding ground truth for it.

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The following Crosstex® Surgical Masks are intended for use in infection control practices to minimize contamination caused by inhaled and exhaled microorganisms and reduce the potential exposure of the wearer to blood and body fluids.

• Crosstex® Surgical Earloop Mask White ●
• Crosstex® Surgical Earloop No Fog Mask White .
• Crosstex® Surgical Earloop No Fog Mask with Splash Visor White .

The Crosstex Surgical Masks are constructed of a cellulose inner facing, a 100% spunbonded polypropylene white outer facing, a 100% meltblown polypropylene filter media, with white non-latex elastic loops. The nose piece for the Crosstex Surgical Masks is aluminum wire while the no fog strip (if applicable) is made of melt blow polypropylene.

This document describes a 510(k) summary for Crosstex Surgical Masks, focusing on non-clinical performance tests rather than an AI-powered diagnostic device. Therefore, many of the requested categories related to AI studies, ground truth, and expert adjudication are not applicable.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

This information is not applicable as the study involves functional testing of a physical medical device (surgical masks), not an AI algorithm processing data. No "test set" in the context of data for an AI model is used. The testing would be performed on samples of the manufactured masks.

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

This information is not applicable. "Ground truth" in the context of AI models refers to definitively labeled data. For performance testing of a physical device like a mask, the "ground truth" is established by adherence to standardized testing protocols and measurements, not expert consensus on data points. The laboratories conducting these tests are assumed to be accredited and their personnel qualified to perform the specific tests.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods like 2+1 or 3+1 are used in AI studies where multiple human readers interpret data to establish a consensus ground truth. For device performance testing, the results are typically quantitative measurements comparing against established standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for comparing the diagnostic performance of human readers with and without AI assistance, which is outside the scope of this device (surgical masks).

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

This information is not applicable. The device is a surgical mask, not an algorithm.

7. The Type of Ground Truth Used

The "ground truth" for the device's performance is established by objective measurements against recognized industry standards and test methods. For example, the Bacterial Filtration Efficiency (BFE) test produces a quantitative percentage that is compared to an accepted threshold. This is distinct from expert consensus, pathology, or outcomes data which are typically used for diagnostic devices.

8. The Sample Size for the Training Set

This information is not applicable. There is no "training set" as this is not an AI or machine learning device.

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

This information is not applicable. There is no "training set" for this device.

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The following Crosstex® Surgical Masks are intended for use in infection control practices to minimize contamination caused by inhaled and exhaled microorganisms and reduce the potential exposure of the wearer to blood and body fluids.

• Crosstex® Isolite® Earloop Face Masks Blue, Pink .
• Crosstex® Isofluid® Earloop Face Masks Blue, Pink, White, Green .
• Crosstex® Isofluid FogFree® Earloop Face Masks Blue, Peach .
• Crosstex® Isofluid FogFree® Face Masks with Splash Visor Blue, Peach ●
• . Crosstex® Procedural Earloop Face Masks - Blue, Pink, Yellow
• Crosstex® Ultra Fluid Resistant No-Fog® Earloop Face Masks Blue .
• Crosstex® Ultra Fluid Resistant No-Fog® Face Masks with Splash Visor Blue ●

The seven (7) Crosstex® Surgical Masks are constructed of either an inner/outer facing of tissue or 100% spunbonded polypropylene, a 100% meltblown polypropylene filter media, with white elastic loops and/or a fogfree strip. The nose piece for all seven (7) Crosstex® Surgical Masks is 27 gauge aluminum wire, some have an anti-fog strip, with the Crosstex® Ultra Fluid Resistant No Fog® having a vapor barrier. All of the materials used in the construction of the Crosstex® Surgical Masks are being used in currently marketed devices (see predicate information).

This 510(k) summary (K082258) describes the Crosstex® Surgical Masks. The document does not describe an AI/ML device, and therefore the standard questions about acceptance criteria, study design, and ground truth for such a device are not applicable.

The submission is for surgical masks and primarily relies on non-clinical performance testing to demonstrate substantial equivalence to predicate devices.

Here's the information as it relates to the provided document:

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

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

This information is not provided in the 510(k) summary. The document mentions "Performance Testing" but does not detail the specific sample sizes used for each test or the provenance of the test data.

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 is not applicable as the device is not an AI/ML diagnostic tool that requires expert-established ground truth from a test set. The evaluation is based on objective physical and biological performance tests.

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

This is not applicable as there is no mention of human adjudication in the context of establishing ground truth for a test set.

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 as the device is not an AI/ML system and therefore no MRMC study was conducted.

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

This is not applicable as the device is not an AI/ML algorithm.

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

The "ground truth" in this context is the results of standardized laboratory performance tests (e.g., BFE, fluid resistance, flammability) against established benchmarks or predicate device performance. It's not based on expert consensus, pathology, or outcomes data in the way an AI diagnostic tool would be.

8. The sample size for the training set

This is not applicable as there is no AI/ML model that requires a training set.

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

This is not applicable as there is no AI/ML model that requires a training set.

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