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The Nitronox® Scavenger Plus is intended to control the vacuum flowrate for scavenging of waste analgesic gas.

The Nitronox® Scavenger Plus (Scavenger Plus) is used within a nitrous oxide/oxygen conscious sedation system to allow removal of waste analgesic gases through a connected vacuum source. The device is used during a dental or medical procedure in a healthcare facility environment. The device is not intended to be used for general anesthesia. The Scavenger Plus is operated by a licensed healthcare professional during conscious sedation of a patient.

The Scavenger Plus connects the exhalation line of the patient's breathing circuit to vacuum tubing from the vacuum source and controls the vacuum flowrate (i.e., scavenging flowrate). The rate at which the gas is removed (i.e., scavenged) is specified by the Scavenger Plus, which uses a control knob and reservoir bag to limit the amount of vacuum applied to the exhalation line of the breathing circuit.

The document provided is a 510(k) Premarket Notification from the FDA for a medical device called the "Nitronox® Scavenger Plus." This type of submission aims to demonstrate that a new device is as safe and effective as a legally marketed predicate device, rather than proving its absolute safety and efficacy through extensive clinical trials.

The document discusses non-clinical performance data and states that clinical investigation was not required because safety and efficacy were supported by non-clinical testing. Therefore, the information typically associated with a study proving a device meets acceptance criteria for an AI/ML medical device (such as those involving test sets, training sets, expert adjudication, MRMC studies, and detailed ground truth establishment) is not present in this document.

The acceptance criteria described in the document relate to engineering and operational performance of a physical gas-scavenging apparatus, not an AI/ML algorithm.

Here's a breakdown of the relevant information provided, adapted to the questions where possible, and noting where information is absent due to the nature of the device and submission:

Acceptance Criteria and Reported Device Performance

The document describes performance criteria primarily related to pressure limits for gas scavenging.

Study Details (as inferable from the document, with many points being N/A for this type of device/submission)

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

   • Sample Size: Not applicable. This device is a physical gas scavenging apparatus, not an AI/ML algorithm that processes data. Testing was likely done on physical units of the device under controlled conditions. The number of samples/units tested is not specified but would be part of standard engineering verification.
   • Data Provenance: Not applicable in the context of "data" for an AI model. This refers to bench testing performed on the physical device. The location of testing is not specified, but it would be part of the manufacturer's quality system. The testing would be "prospective" in the sense that it was conducted specifically for this submission.

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

   • Not applicable. Ground truth for a physical device's performance usually relates to engineering specifications and physical measurements, rather than expert interpretation of complex data (like medical images). Compliance with standards like ISO 80601-2-13 is verified directly through measurement.

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

   • Not applicable. This is relevant for studies involving human interpretation or subjective assessments. Performance testing for this device is based on objective measurements against engineering specifications.

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 not an AI-assisted device. MRMC studies are used to evaluate diagnostic imaging devices or AI algorithms that assist human readers.

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

   • Not applicable. This is not an algorithm-only device. It's a physical medical device.

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

   • Engineering specifications and objective physical measurements: The "ground truth" for this device's performance is whether its physical output (e.g., pressure) meets predefined engineering and regulatory standards (e.g., ISO 80601-2-13).

7. The sample size for the training set:

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

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

   • Not applicable. No training set for an AI/ML model.

In summary, the provided document details a 510(k) submission for a physical medical device. The "acceptance criteria" and "proof" primarily revolve around bench testing demonstrating compliance with established engineering standards and functional specifications, rather than complex data-driven analyses characteristic of AI/ML device evaluations. The FDA determined that the non-clinical testing was sufficient to establish substantial equivalence to a predicate device, thus no clinical trials were deemed necessary.

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The Dynamic Gas Scavenging System is intended to be used for the scavenging of waste anesthesia machines during the provision of general anesthesia to adults and children.

The Dynamic Gas Scavenging System 2 (DGSS-2) is a waste anesthetic scavenging interface placed between the individual anesthetic workstation and the waste gas evacuation vacuum system in a surgical care facility. Through a sensor and solenoid combination, it allows waste gas exhaust flow to the waste gas vacuum line only in the presence of waste anesthetic gas, and interrupts all exhaust flow when no waste gas is present. The system effectively prevents both positive and negative pressure on the patient breathing circuit, and it is usable over a wide range of anesthetic gas flows. It is designed for use in conjunction with low-flow (

The provided text does not describe a study involving an AI/software device that meets specific acceptance criteria related to accuracy, sensitivity, or specificity in a medical imaging context. Instead, it details a 510(k) submission for a medical device called the "Dynamic Gas Scavenging System 2 (DGSS-2)", which is used to scavenge waste anesthetic gases.

This device is not an AI/software product, nor does the document describe any performance study involving human readers, ground truth establishment by experts, or the use of training and test sets as would be typical for an AI/ML medical device. The "Non-Clinical Performance Data" section on page 9 refers to engineering and quality assurance measures and performance testing against standards, not clinical performance in terms of diagnostic accuracy or reader improvement.

Therefore, I cannot provide the requested information for acceptance criteria and a study proving device performance as outlined in your prompt, because the provided document relates to a physical medical device and its engineering validation, not an AI/software product with the types of performance metrics you specified.

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The MINISCAV™ waste gas evacuation apparatus is intended to remove patients' exhaled waste gases during procedures where analgesia is administered to a patient via inspiration of mixtures oxide and oxygen from a nitrous oxide / oxygen delivery device. Not intended for use with flammable anesthetic gases.

This device is intended for professional use only in healthcare facilities, clinics, and physician and dentist offices.

The MINISCAV™ is a small, portable, vacuum pump that generates a constant vacuum that can be connected via a standard flexible vacuum hose to nitrous oxide / oxygen delivery equipment. The vacuum hose is connected to the "vacuum / suction" nipple on exemplary equipment.

The MINISCAVIM is a diaphragm hermetically sealed pump with a fixed vacuum flow rate. The inlet line is connected to a flowmeter exhaust port of the nitrous oxide / oxygen delivery equipment which has an exhaust port for scavenging gases.

Here's an analysis of the acceptance criteria and study information for the MINISCAV™ device, based on the provided document:

The document describes a 510(k) premarket notification for the MINISCAV™ waste gas evacuation apparatus. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than providing extensive clinical efficacy studies in the same way a PMA would. Therefore, the "study" mentioned here refers primarily to the non-clinical testing performed to show the device meets its performance specifications and is as safe and effective as the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" in a tabulated format for each performance aspect. Instead, it describes various tests and what they demonstrated. I've extracted the implied criteria and the reported performance from the "Non-Clinical Testing Summary" and "Technology, Construction, Performance" sections.

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The ISO-Gard® Mask is intended to scavenge waste anesthetic gases from patients during recovery from general anesthesia and to provide supplemental oxygen.

The ISO-Gard® Mask helps to reduce the amount of anesthetic agents released to the work environment of the healthcare worker.

The ISO-Gard Mask system is an oxygen delivery mask that actively scavenges waste anesthetic gases (WAG) exhaled by patients recovering from surgery in the Post-Anesthetic Care Unit (PACU). Vacuum/suction for scavenging of WAG is provided by the institution's regulated vacuum source. The proposed device allows for the delivery of supplemental / therapeutic oxygen to patients to aid in their recovery while reducing the amount of patient expelled waste anesthetic agents released to the work environment of the healthcare workers. The mask can be used with or without suction / vacuum to function as a standard oxygen mask with an ETCO2 monitoring port.

This document describes the Teleflex Medical, Inc. ISO-Gard Mask (K142138), a gas-scavenging apparatus intended to remove waste anesthetic gases and provide supplemental oxygen to patients recovering from general anesthesia.

Here's an analysis of the provided information regarding acceptance criteria and the supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

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The ISO-Gard® Mask is intended to be used to scavenge waste anesthetic gases from patients during recovery from general anesthesia and to provide supplemental oxygen.

The ISO-Gard® Mask helps to reduce the amount of anesthetic agents released to the work environment of the healthcare worker.

The ISO-Gard Mask system is an oxygen delivery mask that actively scavenges waste anesthetic gases (WAGS) exhaled by patients recovering from surgery in the Post-Anesthetic Care Unit (PACU). Vacuum/suction for scavenging of WAGS is provided by the institution's regulated vacuum source. The proposed device allows for the delivery of supplemental / therapeutic oxygen to patients to aid in their recovery while reducing the amount of patient expelled waste anesthetic agents released to the work environment of the healthcare workers. The mask can be used with or without suction / vacuum to function as a standard oxygen mask with an ETCO2 monitoring port.

ISO-Gard® Mask Acceptance Criteria and Study Details

1. Table of Acceptance Criteria and Reported Device Performance

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

The provided document does not specify the sample size used for the test set.

The data provenance is not explicitly stated as retrospective or prospective, nor does it specify the country of origin. However, the tests are described as nonclinical performance testing and simulated conditions, suggesting laboratory-based studies rather than patient data.

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

The document does not mention the use of experts to establish ground truth for the test set. The performance tests appear to be based on objective measurements against established technical standards for oxygen delivery, scavenging efficacy, and ETCO2 waveform characteristics, rather than expert judgment.

4. Adjudication Method for the Test Set

Since there is no mention of experts or human interpretation in establishing the ground truth for the test set, there is no adjudication method described (e.g., 2+1, 3+1, none). The tests rely on quantifiable measurements.

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

There is no indication that a multi-reader multi-case (MRMC) comparative effectiveness study was conducted. The device is a physical mask for gas scavenging and oxygen delivery, not an imaging or diagnostic AI tool that would typically involve human readers.

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

This question is not applicable. The ISO-Gard® Mask is a medical device for gas delivery and scavenging, not an algorithm or AI system. Therefore, a "standalone algorithm performance" study is not relevant. The performance tests evaluate the physical functioning of the device.

7. Type of Ground Truth Used

The ground truth for the performance tests appears to be based on objective technical standards and measurements:

• For Oxygen Delivery: Comparison against "a standard medium concentration oxygen mask" and measurements of delivered oxygen percentage.
• For Scavenging: Measurement of N₂O levels compared against "a standard medium concentration oxygen mask."
• For ETCO₂: Evaluation of generated traces/waveforms for distinctness and consistency.

8. Sample Size for the Training Set

The document does not mention a training set. This is expected as the ISO-Gard® Mask is a physical medical device and not an AI or machine learning system that requires training data.

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

This question is not applicable as there is no mention of a training set for this device.

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The ISO-GARD® ClearAir™ Mask is intended to be used to scavenge waste anesthetic gases from patients during recovery from general anesthesia and to provide supplemental oxygen.

The ISO-GARD® ClearAir™ Mask helps to reduce the amount of anesthetic agents released to the work environment of the healthcare worker.

The ISO-GARD® ClearAir™ mask system is an oxygen delivery mask that actively scavenges waste anesthetic gases ("WAGS") exhaled by patients recovering from surgery in the Post-Anesthetic Care Unit ("PACU"). Vacuum/suction for scavenging of WAGS is provided by the institution's regulated vacuum source. The proposed device allows for the delivery of supplemental / therapeutic oxygen to patients to aid in their recovery while reducing the amount of patient expelled waste anesthetic agents released to the work environment of the healthcare workers.

The mask can be used with or without suction / vacuum to function as a standard oxygen mask with an ETCO2 monitoring port.

The ISO-GARD® ClearAir™ mask is offered in several configurations, the differences being some of the components.

The provided document describes a 510(k) premarket notification for the ISO-GARD® ClearAir™ mask. This device is an oxygen delivery mask that actively scavenges waste anesthetic gases (WAGS) and provides supplemental oxygen. The submission is a comparison to legally marketed predicate devices, not a study presenting novel acceptance criteria.

The document explicitly states: "There is no pass / fail criteria for the ISO-GARD® ClearAir™ mask. The testing performed is for disclosure only." This indicates that the study was not designed to meet specific, pre-defined acceptance criteria with pass/fail thresholds. Instead, the testing aimed to characterize the device's performance and demonstrate substantial equivalence to predicate devices.

Therefore, I cannot provide a table of acceptance criteria and reported device performance directly from this document, as such criteria were not defined as "pass/fail" for this submission type. However, I can summarize the performance data disclosed and the nature of the study.

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

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

As mentioned, no explicit "pass/fail" acceptance criteria were set for this device in the context of this 510(k) submission for the performance testing. The reported performance data is primarily for disclosure and comparison.

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

• Test Set Sample Size: The document does not specify a numerical sample size for the "test set" in terms of how many devices were tested or how many test conditions were numerically replicated. It describes performance testing in a "simulation bench set-up."
• Data Provenance: The studies are described as "Non-clinical Performance Testing" and "simulation bench set-up." This indicates a prospective, controlled laboratory setting. The country of origin of the data is not explicitly stated, but the submission is to the U.S. FDA by Teleflex Medical, Inc., located in Research Triangle Park, NC, USA.

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 is not applicable to this submission. The "ground truth" for this device's performance (e.g., oxygen percentage, scavenging effectiveness) would be established through a validated physical measurement system in the benchtop simulation, not through expert consensus or clinical interpretation of data.

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

This information is not applicable. As the testing involved objective physical measurements on a benchtop, there was no need for expert adjudication of results.

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 is a medical device, not an AI-driven diagnostic or image analysis tool. Therefore, MRMC studies and "human reader improvement with AI" are not relevant to this submission.

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 medical device. "Standalone (algorithm only)" is a concept for AI or software devices, not relevant here.

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

The "ground truth" for the performance claims in this submission is based on objective physical measurements from a validated simulation bench set-up. For example, oxygen percentage was measured, and the absence of N₂O was detected. Biocompatibility was assessed against ISO 10993 standards.

8. The sample size for the training set

This information is not applicable. There is no "training set" in the context of this traditional medical device submission. Training sets are typically associated with machine learning or AI algorithm development.

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

This information is not applicable as there is no training set for this device.

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The Waste Gas Scavenger is designed for use with vacuum (suction) waste gas disposal systems with anesthesia machines and heart/lung bypass machines.

Active Waste Gas Scavenger

The provided text is a 510(k) premarket notification letter from the FDA regarding a medical device called an "Active Waste Gas Scavenger." It is a regulatory document and does not contain any information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications as would be found in a study report.

Therefore, I cannot provide the requested information based solely on the text provided. This document simply states that the device has been reviewed and determined to be substantially equivalent to legally marketed predicate devices.

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To remove unwanted anesthetic gases from the patient breathing circuit

This device uses two anesthetic vapor adsorbent canisters connected to an anesthesia delivery system to prevent unwanted anesthetic vapors emanating from within an anesthesia gas machine from reaching a patient.

Here's a breakdown of the acceptance criteria and study information for the Vapor-Clear device, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

The provided document describes non-clinical bench testing to demonstrate the substantial equivalence of the Vapor-Clear device to its predicate.

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

   • Test Set Sample Size: Not explicitly stated as a "sample size" in terms of patient data. The testing involved multiple units of the Vapor-Clear device and utilized two modern anesthesia gas machines (Draeger Apollo and Ohmeda Aestiva) for the residual vapor scavenging test. "A single Vapor-Clear canister" was used for the removal capacity test. "Product containing activated charcoal that has been aged for 71 months" was tested for product life testing.
   • Data Provenance: The data is from non-clinical bench testing. The country of origin is not specified but is implied to be related to the manufacturer (Axon Medical Inc., Park City, Utah, USA) and the FDA submission process. This is retrospective in the sense that the studies were completed before the 510(k) submission.

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

   • Number of Experts: Not applicable. The ground truth for this non-clinical testing was established through direct measurement using analytical instruments (e.g., anesthetic gas analyzer capable of detection 99% removal) was determined by comparing measured input and output concentrations.

3. The sample size for the training set:

   • Training Set Sample Size: Not applicable. This device is a physical medical device and does not involve AI or machine learning models that require a training set.

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

   • Ground Truth for Training Set: Not applicable. As above, no training set was used.

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The Passive Waste Gas Scavenger is intended to be used for the scavenging of waste anesthetic gases from anesthesia machines used during the provision of general anesthesia to adults and children. The Passive Waste Gas Scavenger is designed for use with non-recirculating waste gas disposal systems and is intended for prescription use only.

The Passive Waste Gas Scavenger is intended to be used for the scavenging of waste anesthetic gases from anesthesia machines used during the provision of general anesthesia to adults and children. The Passive Waste Gas Scavenger is designed for use with non-recirculating waste gas disposal systems and is intended for prescription use only. This scavenging approach relies on the pressure of the waste gas to transfer the gas from the scavenger to the exhaust system.

The scavenger body incorporates one 30mm/27mm/19mm horizontal hose terminal to connect the scavenger to the anesthesia machine. The vertically oriented 30mm/19mm hose terminal is intended to connect the scavenger to the exhaust system.

The G. Dundas Passive Scavenger incorporates the same safety systems as predicate devices, providing relief of excess positive pressure and excess negative pressure to the patient through the use of pressure relief valves, in compliance with ASTM 1343-02 -Anesthetic Equipment -- Scavenging Systems for Anesthetic Gases. Although there is no standard for passive waste gas scavenging systems, the G. Dundas Passive Scavenger is designed to fail safe under active waste disposal conditions.

The G. Dundas Passive Scavenger and the predicate devices were tested and found to have similar performance. Testing procedures and data can be found in Section 7 of this application.

The provided text describes a medical device, the "Passive Waste Gas Scavenger," and its 510(k) submission to the FDA. It does not contain information about a study that proves the device meets specific acceptance criteria in the manner typically associated with AI/ML device evaluations (e.g., performance metrics like sensitivity, specificity, or AUC against a ground truth dataset).

Instead, the document focuses on the device's design specifications and functional performance in relation to safety standards for medical gas scavenging systems. The "acceptance criteria" here are defined by the device's operational parameters and compliance with an existing ASTM standard, rather than statistical performance against a diagnostic endpoint.

Therefore, many of the requested categories for AI/ML device studies are not applicable to this submission. I will extract the relevant information and indicate where categories are not applicable.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size (Test Set): Not applicable. The "testing" referred to appears to be engineering and functional validation, not a clinical study on a patient sample. The device's performance is described in terms of its operational parameters under specific flow and pressure conditions.
• Data Provenance: Not applicable. The testing is likely internal engineering validation.

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

• Number of Experts: Not applicable. Ground truth for this type of device is based on established engineering principles and medical device safety standards (e.g., ASTM 1343-02), rather than expert clinical consensus on diagnostic outcomes.
• Qualifications of Experts: Not applicable.

4. Adjudication method for the test set

• Not applicable. There's no indication of a ground truth adjudication process in the clinical sense. Performance is assessed against predefined physical parameters.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

• No, a MRMC comparative effectiveness study was not done. This type of study is typically performed for diagnostic devices where human readers interpret medical images or data.

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

• Not applicable. This is a mechanical medical device, not an algorithm.

7. The type of ground truth used

• Type of Ground Truth: Engineering specifications and established medical device safety standards (specifically ASTM 1343-02 for "Anesthetic Equipment -- Scavenging Systems for Anesthetic Gases"). The performance is measured against these defined physical and safety thresholds.

8. The sample size for the training set

• Not applicable. This is a mechanical medical device, not an AI/ML algorithm that requires a training set.

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

• Not applicable.

Summary of the "Study" mentioned:

The document states, "The G. Dundas Passive Scavenger and the predicate devices were tested and found to have similar performance. Testing procedures and data can be found in Section 7 of this application." This indicates that the "study" was a performance validation by comparing its functional operation to its predicate devices and against the safety requirements outlined in ASTM 1343-02. The described "performance" relates to maintaining specific pressure thresholds within the scavenging system under normal and fault conditions (e.g., positive and negative pressure relief valve activation). The provided data points (3.0 cm H₂O max inlet pressure, $\leq$ 9 cm H₂O positive relief, $\geq$ -2.5 mm H₂O negative relief) are the direct results of this functional testing.

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The single-use Nasal Scavenging Circuit is intended to be used in conjunction with a conscious sedation system for the delivery of medical gases to the patient, and for the removal of expired, excess and unused gases from the treatment location.

The single-use Nasal Scavenging Circuit is designed for the removal of patient expired and excess gases during conscious sedation procedures.

This document describes a 510(k) premarket notification for a medical device called the "Nasal Scavenging Circuit." This type of submission focuses on demonstrating that a new device is "substantially equivalent" to a legally marketed predicate device, rather than proving its independent safety and effectiveness through extensive clinical trials as would be required for a Premarket Approval (PMA) application.

Therefore, the study conducted is not a traditional performance study comparing specific metrics against pre-defined acceptance criteria in the way an AI/ML device would be. Instead, the "study" is a set of non-clinical bench tests designed to show that the new device does not raise new issues of safety or effectiveness compared to its predicate.

Here's an analysis based on the provided text, addressing your specific questions to the best extent possible given the nature of a 510(k) submission for this type of device:

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

The device's technological characteristics, indications for use, and performance specifications are stated to be the same as the predicate device (Fraser Harlake Dental Anti-Pollution System (K833692)), implying that it performs at least as safely and effectively as the predicate.

Adherence to pertinent sections of voluntary standards (NIOSH Publication No. 94-129, ISO 5356-1, ISO 5367, ANSI Z79.11-1982, CGA V-5) for design indicates meeting established safety and performance benchmarks for components and functionality. |
| Effectiveness: Device performs its intended function for removal of expired/excess gases. | "The indications for use, the technology, and the performance specifications are the same for the Nasal Scavenging Circuit and the predicate device." This statement is the core of the substantial equivalence claim, meaning its effectiveness is considered equivalent to the predicate.

The bench testing would have demonstrated functional performance, such as gas flow, scavenging efficiency, and connection integrity, consistent with the predicate device and relevant voluntary standards, though specific numerical performance metrics are not detailed in this summary. |
| Substantial Equivalence: Device does not raise new issues of safety or effectiveness. | The FDA’s letter confirms that the device is "substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices," based on the provided data from the manufacturer. |

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

• Sample Size: Not applicable in the context of human data. The "test set" consisted of physical devices subjected to non-clinical bench testing. The number of units tested is not specified in this summary.
• Data Provenance: The testing was "bench testing" meaning it was conducted in a laboratory setting. The location of MINRAD Inc. (Orchard Park, New York, USA) suggests the testing likely occurred in the USA or a facility associated with the company.
• Retrospective or Prospective: Not applicable for bench testing. It's a controlled experimental evaluation of the physical device's performance.

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

• Not applicable. This is a physical device being evaluated for substantial equivalence through non-clinical bench testing, not an AI/ML diagnostic device requiring expert interpretation of clinical data to establish ground truth. The "ground truth" (or performance standard) would be defined by the technical specifications of the predicate device and the relevant voluntary standards.

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

• Not applicable. Adjudication methods like "2+1" typically apply to expert reviews of clinical cases (e.g., in radiology studies) where there might be disagreement among reviewers on a diagnosis or finding. This submission involves bench testing of a physical device. Performance would be an objective measurement against a standard, not a subjective 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

• No. An MRMC study is not relevant for this device. This is a physical gas scavenging circuit, not an AI/ML-driven diagnostic tool that assists human readers in interpreting data.

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

• Not applicable. This device is a physical product, not an algorithm or AI system.

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

• The "ground truth" for this 510(k) submission is effectively the performance and safety profile of the predicate device (Fraser Harlake Dental Anti-Pollution System (K833692)) and adherence to relevant voluntary standards (e.g., NIOSH, ISO, ANSI, CGA V-5). The bench tests verify that the new device meets or is equivalent to these established engineering and safety standards.

8. The sample size for the training set

• Not applicable. This device does not involve machine learning or AI, so there is no "training set."

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

• Not applicable. No training set exists for this type of device submission.

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