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The InstaFAN device is intended for sampling targeted submucosal and extramural lesions within or adjacent to the gastrointestinal tract through the accessory channel of a curvilinear echo-endoscope. Use only with EUS endoscopes.

InstaFAN is an endoscopic ultrasound-guided fine needle aspiration/fine needle biopsy device that collects several samples from different locations in a single pass. The InstaFAN can be coupled to the biopsy channel of a Curvilinear Array (CLA) Echoendoscope and delivered to the gastrointestinal tract. The InstaFAN device is comprised of a central single 19-gauge needle and five peripheral 25-gauge needles. The device has a single handle design that contains two moving parts. The distal section of the handle controls the central needle, which can be activated first on its own or together with the proximal section of the handle to deploy all five needles simultaneously. The needles are used to acquire samples from lesions within and adjacent to the digestive system's major lumens that can be identified and targeted using the echoendoscope. Aspiration/biopsy samples are obtained by penetrating the lesion with the needle(s) while applying suction with the syringe.

The provided FDA 510(k) clearance letter for the InstaFAN device explicitly states that "Clinical testing was not required for the subject device; therefore, this section is not applicable." This means the document does not contain information about acceptance criteria, actual device performance (in terms of clinical outcomes), sample sizes for test or training sets, ground truth establishment methods, or details related to multi-reader multi-case (MRMC) studies.

The clearance was based on:

1. Non-Clinical Performance Testing:

   • Verification of needle performance (tensile, elasticity, bend strength).
   • Verification of overall device performance (EUS connection force, bend strength, force required to move needles, insertion force, and needle orientation).
   • The results showed the device met its specifications.

2. Animal Studies:

   • Conducted on the InstaFAN device.
   • Results met the safety and performance criteria to demonstrate substantial equivalence to the predicate.

Therefore, I cannot populate the requested tables or provide details based on a clinical study for this device, as one was not required or described in the provided text for its 510(k) clearance.

If this were a device requiring clinical data, the information you requested would typically be found in dedicated sections of the submission detailing the clinical study protocol, results, and statistical analysis.

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Onera STS 2 measures and records multiple physiological parameters from a patient during a sleep study, which are used by clinicians to decide on the diagnosis of sleep disorders.

Onera STS 2 is intended to be used on a patient who has been prescribed a polysomnography study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson.

The recorded data will be made available to the healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

The device is not a life supporting physiological monitor.

Onera Sleep Test System 2 (Onera STS 2) is a hardware, wearable system for measuring physiological signals during a sleep study. The device can be used in the home (Home Healthcare Environment) as well as in Professional Healthcare Facilities.

The device measures EEG, EOG, EMG, ECG, respiratory signals, cannula based respiratory flow, oxygen saturation, activity, position, ambient light level and sound pressure level.

The ECG signal is not intended for diagnosis of cardiac disorders, except for the manual determination of arrhythmia during polysomnography studies.

The Onera STS 2 does not provide any automated output like heart rate, assessments of arrhythmia, heart rate variability, or other related heart rate measurement functions.

Onera STS 2 consists of five Sensors applied on the forehead, upper chest area, abdomen and lower leg area (both left and right leg).

The Sensors should be placed on intact skin. During the night measurement it is not needed to inspect the application sites. The Sensors encrypt the recorded signals and upload the measurement data during the night to the Patient App installed on the patient's phone via Bluetooth. The Patient App securely transfers the data to the cloud interface for further processing once all data has been uploaded. The output of the system is represented by a file in EDF format which contains the recorded (physiological) signals. EDF files can be read by any application software that accepts such files as input.

It is not possible to relocate the Sensors during a sleep study since the Sensor is single-use and for one sleep study only.

Here's a summary of the acceptance criteria and study information for the Onera STS 2, based on the provided FDA 510(k) clearance letter:

Onera STS 2: Acceptance Criteria and Performance Study Summary

1. Table of Acceptance Criteria and Reported Device Performance

The provided document primarily focuses on the SpO2 measurement accuracy as a key performance metric with specific acceptance criteria.

Note: While other parameters are listed as "Identical" to the predicate, specific numerical acceptance criteria for those parameters are not explicitly stated in this document beyond their qualitative equivalence.

2. Sample Size and Data Provenance for the Test Set

• Sample Size: 12 healthy subjects
  • 9 male, 3 female
  • Aged between 23 and 46 years old
• Data Provenance: The study was conducted in an "independent research laboratory." The country of origin is not explicitly stated in the provided text. The study involved "induced hypoxia," indicating a prospective, controlled experimental design.

3. Number and Qualifications of Experts for Ground Truth

• The document does not mention the use of experts to establish ground truth for the SpO2 accuracy test.
• The ground truth for SpO2 was established by "laboratory co-oximeter" measurements of arterial hemoglobin oxygen (SaO2) values from blood samples.

4. Adjudication Method for the Test Set

• The document does not describe any adjudication method. The SpO2 accuracy was determined by direct comparison of the device's SpO2 measurements to SaO2 values from a laboratory co-oximeter.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or described in this document. The device primarily measures physiological parameters, and the study focused on the accuracy of these measurements rather than human reader interpretation with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

• Yes, a standalone performance study was conducted for SpO2 measurement accuracy. The device's SpO2 readings were directly compared to reference SaO2 values without human intervention in the SpO2 measurement process itself. The Onera STS 2 is described as measuring and recording parameters, with the output as an EDF file to be read by other software. The SpO2 accuracy assessment is specifically for the device's measurement capability.

7. Type of Ground Truth Used

• Objective Measurement (Laboratory Co-oximeter): For SpO2 accuracy, the ground truth was established by arterial hemoglobin oxygen (SaO2) values determined from blood samples using a laboratory co-oximeter, which is considered a gold standard for blood oxygen saturation.

8. Sample Size for the Training Set

• The document does not provide information regarding the sample size for a training set. This is likely because the performance study described (SpO2 accuracy) is a validation of the device's sensor capabilities, not an evaluation of a machine learning algorithm that would typically require a training set. The device outputs raw physiological signals in EDF format for clinicians to interpret, rather than providing automated diagnoses based on an internal algorithm.

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

• As no training set is mentioned or implied for the device's core functionality (measuring and recording parameters for clinician interpretation), this information is not applicable and not provided in the document.

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Under the direction of a healthcare professional, the Rx product is indicated for the management of partial and full thickness wounds, post-surgical wounds, 1st and superficial 2nd degree burns, diabetic foot ulcers, venous stasis ulcers, and pressure ulcers.

Bonvadis® is a non-sterile water based, preserved, semi-viscous formulation, for prescription use. Bonvadis® contains methyl and propyl parabens which act as preservatives to inhibit the growth of microorganisms within the product before opening and between uses.

Bonvadis® is multiple use and supplied in a 15 g aluminum tube.

The formulation is to maintain a moist wound environment, the moist wound environment being conducive for wound healing.

Ingredients: Purified water, liquid petrolatum, white petrolatum, propylene glycol, cetyl stearyl alcohol, span 60, tween 60, Centella Asiatica extract, Mexican Mint extract, Methyl Paraben, and Propyl Paraben.

The provided FDA 510(k) clearance letter and summary for Bonvadis® do not contain any information regarding clinical performance studies, such as those involving human readers or expert panels, nor do they specify acceptance criteria for such studies.

The acceptance criteria mentioned in the document are primarily related to non-clinical performance tests proving the device's physical properties, safety, and functionality.

Here's the information that can be extracted or deduced from the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

As no clinical performance acceptance criteria or corresponding results are provided in the document, the table below focuses on the non-clinical tests mentioned. The document states that the results "meet the criteria" or "demonstrated that the device is as safe, effective, and performs as well as the predicate devices," implying successful completion of these tests against internal or regulatory standards, though specific numerical criteria are not detailed.

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

Not applicable/Not provided for clinical performance. The document exclusively refers to non-clinical tests on the device itself (e.g., stability, physical properties, biocompatibility). There is no mention of a "test set" of patient data or images.

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

Not applicable/Not provided. As there are no clinical performance studies or test sets involving patient data, no experts were used to establish ground truth for such a purpose.

4. Adjudication method for the test set

Not applicable/Not provided. No adjudication method is mentioned as there were no clinical performance studies requiring expert review of data.

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/Not provided. This device is a topical wound dressing, not an AI-assisted diagnostic or treatment planning tool. Therefore, an MRMC study related to human readers and AI assistance is irrelevant and not mentioned.

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

Not applicable/Not provided. This device is a physical product (wound dressing), not a software algorithm.

7. The type of ground truth used

Not applicable/Not provided for clinical performance. For the non-clinical tests, the "ground truth" refers to established scientific and regulatory standards (e.g., USP monographs for microbial limits, pH, preservative efficacy) against which the device's physical and chemical properties were measured.

8. The sample size for the training set

Not applicable/Not provided. This refers to clinical or AI model training data, neither of which are mentioned or relevant to the non-clinical tests described for this wound dressing.

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

Not applicable/Not provided. As there is no mention of a training set for an AI model or clinical study, this information is not available.

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Oneday Implant Abutment is indicated for use in partially or fully edentulous mandibles and maxillae, in support of single or multiple unit restorations including; cemented retained, or overdenture restorations, and final or temporary abutment support for fixed bridgework. It is intended for delayed loading. Implants with diameters larger than 5 mm are intended to be used in the molar region.

The Oneday Implant Abutment is a material for dental surgery and is an abutment used to support and maintain prosthetic restored teeth in case of partial or total loss of teeth. It is used in combination with a fixture implanted in the jawbone.

This document describes a 510(k) premarket notification for the "Oneday Implant Abutment," a dental device. The primary purpose of a 510(k) submission is to demonstrate that a new device is "substantially equivalent" to a legally marketed predicate device, meaning it has the same intended use and the same technological characteristics, or if there are differences, those differences do not raise new questions of safety and effectiveness.

The provided text details the device description, indications for use, comparison to predicate devices, and non-clinical test data. It is crucial to understand that this document does NOT describe the acceptance criteria and a study proving a device meets those criteria in the context of clinical performance or AI/software validation. Instead, it describes mechanical, material, and biocompatibility testing for a physical dental implant component to demonstrate its substantial equivalence to an existing device.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC study, standalone performance, ground truth establishment for AI systems, training set sample size) are not applicable to this type of device submission. This is a traditional medical device submission, not a submission for a software-as-a-medical-device (SaMD) or an AI/ML-driven device that would involve performance metrics related to diagnostic accuracy or clinical outcomes.

Here's an analysis of the provided information relative to your request:

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

The acceptance criteria here are standards for mechanical performance, biocompatibility, and sterilization, rather than performance metrics for an AI algorithm.

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

• Sample Size: The document does not specify exact sample sizes for the non-clinical tests (e.g., number of abutments tested for fatigue, sterilization, or biocompatibility). This information is typically detailed in the full test reports referenced in the submission, not summarized in the 510(k) summary letter.
• Data Provenance: The tests are non-clinical (laboratory-based) performed on "subject device" or "worst-case test article" samples. There is no patient data involved for these tests. The country of origin for the data generation (the testing laboratories) is not specified in this summary. These are prospective tests performed specifically for this submission.

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

• This is not applicable. The "ground truth" for mechanical testing, sterilization, and biocompatibility is based on established ISO and ANSI standards. There are no "experts" establishing a "ground truth" in the clinical imaging or diagnostic sense. The evaluations are objective measurements against predefined thresholds.

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

• This is not applicable. Adjudication methods are typically used in clinical studies, particularly for subjective assessments (e.g., image interpretation). These are objective non-clinical tests.

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. The device is a physical dental implant abutment, not an AI-powered diagnostic or assistive tool. No MRMC study would be performed for this type of device.

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

• This is not applicable. There is no algorithm or software for which standalone performance would be relevant for this physical device.

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

• For the non-clinical tests, the "ground truth" is defined by the objective pass/fail criteria specified by the referenced ISO/ANSI standards for mechanical properties, sterility assurance levels, and biocompatibility endpoints. There is no clinical "ground truth" in the sense of pathology or outcomes data for this specific submission, as it relies on non-clinical testing for substantial equivalence.

8. The sample size for the training set:

• This is not applicable. This is a physical medical device, not a software/AI product requiring a training set for model development.

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

• This is not applicable. See point 8.

In summary: The provided document is a 510(k) summary for a physical medical device, the Oneday Implant Abutment. It demonstrates substantial equivalence primarily through comparisons of design, materials, intended use, and adherence to established performance standards through non-clinical (laboratory) testing. It does not involve AI/ML technology or associated validation studies typically seen in software medical device submissions, and therefore, many of the detailed questions regarding AI performance criteria and study design are not relevant to this specific document.

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The Oneday Mini Implant System is intended for two-stage surgical procedures in the following situations and with the following clinical protocols:

• The intended use for the 3.0mm, 3.3mm diameter Oneday Mini Implant is limited to the replacement of maxillary lateral incisors and mandibular incisors.

• Immediate placement in extraction situations with a partially or completely healed alveolar ridge.

• It is intended for delayed loading.

The Oneday Mini Implant System is used to replace missing teeth in various situations ranging from a single tooth loss to the complete loss of incisors teeth. This system is restricted to substitute the maxillary lateral incisors and mandibular incisors. It is two stage endosseous screw type implant with internal hexagonal connection. This system consists of the fixture, cover screw, and various abutments. Only the subject abutments can be used with the subject fixtures. The Fixture is made of Pure Titanium of ASTM F67 and the surface of the fixture is treated with the SLA(Sand-blasted, Large grit, Acid-etched surface). Fixture is provided sterile.

This document is a 510(k) summary for the Oneday Mini Implant System, primarily focused on demonstrating substantial equivalence to a predicate device (UF(II) Narrow Implant System by DIO Corporation, K161987) rather than proving performance against specific acceptance criteria for an AI/ML device.

Therefore, many of the requested details related to AI/ML device acceptance criteria, study design (like MRMC, training/test set ground truth, expert adjudication), and performance metrics (e.g., AUC, sensitivity, specificity) are not present in this document because it is for a traditional dental implant device, not an AI/ML powered device.

However, I can extract the information relevant to a traditional medical device's acceptance criteria and performance proof, focusing on the equivalence to a predicate device.

Acceptance Criteria and Study for the Oneday Mini Implant System (A Traditional Medical Device)

1. Table of Acceptance Criteria and Reported Device Performance:

For a traditional medical device like a dental implant, "acceptance criteria" are typically demonstrated through various non-clinical tests (mechanical, material, sterilization, biocompatibility) and comparison to a legally marketed predicate device. The performance is assessed by showing substantial equivalence to this predicate, meaning it is as safe and effective as the predicate.

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

• Test Set (for performance evaluation): For a traditional device showing substantial equivalence, there isn't a "test set" in the sense of a distinct dataset used to calculate performance metrics like sensitivity/specificity for an algorithm. Instead, the "testing" involves performing specific engineering and biological tests (e.g., fatigue testing on a sample of implants, sterilization validation on a sample of devices) and comparing the design specifications and materials to a predicate device.
  • Fatigue Testing: "Fatigue Testing under the worst-case scenario according to ISO 14801:2016." The standard dictates sample sizes.
  • End User Sterilization Validation: Performed on the "subject Healing Abutment Mini with the greatest surface area" to be representative. Standards dictate sample sizes.
  • Data Provenance: The document does not specify the country of origin for the testing data. Test results are generally from controlled laboratory environments using product samples. Most data is "leveraged" from previous 510(k) clearances (K192294 and K161987) for similar devices, suggesting a retrospective use of existing data to support the current claim of equivalence.

3. Number of Experts and Qualifications for Ground Truth:

• Not applicable in the context of this 510(k) summary for a traditional medical device. Ground truth for device performance is established through adherence to recognized international standards (e.g., ISO, ASTM) for material properties and mechanical testing, and through comparison to a device already cleared by the FDA (the predicate). There is no "expert panel" establishing a clinical ground truth for a diagnostic output as there would be for an AI/ML imaging device.

4. Adjudication Method for the Test Set:

• Not applicable. There is no "adjudication" of results in the sense of reconciling differing expert opinions, as this is not an AI/ML diagnostic device with human readers. Testing results are objective measurements against pre-defined engineering and biological standards.

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

• No, an MRMC study was not done. This type of study is relevant for diagnostic devices, particularly AI/ML-powered ones, to assess the impact of the AI on human reader performance. This document is for a physical medical implant.

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

• No, a standalone evaluation was not done. This concept applies to AI/ML algorithms that might provide a diagnostic output without human intervention. This document is for a physical medical implant.

7. The type of ground truth used:

• The "ground truth" for the Oneday Mini Implant System is based on:
  • Adherence to recognized international standards: e.g., ISO 14801:2016 for fatigue, ISO 11137 for sterilization, ISO 10993 for biocompatibility, etc.
  • Demonstrated equivalence to a legally marketed predicate device: The predicate device (UF(II) Narrow Implant System, K161987) has already been determined to be safe and effective by the FDA. The substantial equivalence argument posits that since the new device is fundamentally similar and meets performance parameters, it is also safe and effective.

8. The sample size for the training set:

• Not applicable. There is no "training set" as this is not an AI/ML device.

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

• Not applicable. There is no "training set" as this is not an AI/ML device.

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Onera STS measures and records multiple physiological parameters from a patient during a sleep study which are used by clinicians to make a decision on the diagnosis of sleep disorders.

Onera STS is intended to be used on a patient, who has been prescribed a sleep study by a healthcare professional. The device is designed to be used under the direction of a physician or trained technician but applied by a layperson. The recorded data will be made available to a healthcare professional to assist in the diagnosis of sleep disorders.

The device is intended to be used for adults.

Onera STS is a wearable system for measuring (physiological) signals during a sleep study. The device can be used in home (Home Healthcare Environment) as well as Professional Healthcare Facilities, to perform the sleep study.

Onera STS consists of four sensors applied on the forehead, upper chest area, abdominal and lower leg area.

The sensors measure EEG, EOG, EMG, ECG, bioimpedance based respiratory effort, bioimpedance based respiratory flow, cannula based respiratory flow, oxygen saturation, activity, position, and sound pressure level.

The study preparation and data retrieval are done in a professional/clinical environment by the trained operator. The device is provided to the user by the trained operator.

The device is not a life supporting physiological monitor.

The provided text is a 510(k) summary for the Onera Sleep Test System (Onera STS). It details the device, its intended use, and a comparison to a previously cleared predicate device (K210593). The primary change in this submission (K223573) is an extension of the device's use time from 8 hours to 16 hours.

It's crucial to understand that this document is a premarket notification asserting substantial equivalence, not a detailed clinical study report proving performance against specific acceptance criteria for diagnostic accuracy. The FDA's review for a 510(k) focuses on safety and effectiveness in comparison to a predicate device, rather than requiring new, full-scale clinical trials for every parameter.

Therefore, the information regarding acceptance criteria and performance studies within this document is limited to demonstrating that the change (extended wear time) does not introduce new safety or effectiveness concerns, and that the device still meets regulatory standards. There is no information provided about a study that assesses the device's diagnostic accuracy or performance against specific, quantifiable "acceptance criteria" for detecting sleep disorders. The device is described as measuring and recording parameters for clinicians to use, not as an automated diagnostic tool itself.

Given this context, I will address your points based on the available information in the provided text.

Acceptance Criteria and Device Performance (Based on provided 510(k) Summary)

The FDA 510(k) summary primarily focuses on demonstrating that the modified device (Onera STS with 16-hour wear time) is substantially equivalent to its predicate device (Onera STS with 8-hour wear time) and that the change does not introduce new safety or effectiveness concerns. There are no explicit "acceptance criteria" for diagnostic accuracy or performance of the device in the context of detecting sleep disorders presented in this document. The "performance testing" mentioned is related to meeting general safety and performance standards, and verifying that the extended wear time does not degrade existing performance or safety.

Table of Comparison (Not "Acceptance Criteria" for Diagnostic Performance):

The table below summarizes the comparison between the proposed device and the predicate, highlighting the only stated difference: extended use time. This is a demonstration of substantial equivalence rather than meeting specific diagnostic acceptance criteria.

Study Details (Based on provided 510(k) Summary)

The provided document describes a 510(k) "premarket notification" which asserts substantial equivalence, not a dedicated clinical study for diagnostic accuracy. Therefore, information related to diagnostic performance studies, AI algorithms, human readers, or specific "acceptance criteria" for disease diagnosis is largely absent.

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

   • As explained above, the "acceptance criteria" discussed are for substantial equivalence and compliance with general safety and performance standards for a medical device (e.g., biocompatibility for extended wear, electrical safety, EMC).
   • The reported performance for the primary change (extended wear time) is implied by the statement: "The extension is supported by new skin irritation testing and 16-hour wear time testing as part of design verification and validation activities." This testing demonstrated that the device performs safely and effectively for the increased duration. No quantitative performance metrics related to diagnostic accuracy (e.g., sensitivity, specificity for detecting specific sleep disorders) are provided, as the device records data for clinicians to use for diagnosis, it does not autonomously diagnose.

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

   • The document states: "No clinical data was required to support equivalence." This means a dedicated clinical test set for diagnostic accuracy was not part of this 510(k) submission.
   • The extended wear time and skin irritation testing would have involved engineering and biocompatibility testing, likely using a limited number of human subjects or in-vitro/in-vivo models. Specific sample sizes and provenance for these verification/validation activities are not detailed in this summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • Not applicable/Not provided. Since "No clinical data was required," there was no clinical test set for which ground truth needed to be established by experts for diagnostic performance.

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

   • Not applicable/Not provided.

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. The document does not describe the device as incorporating AI for automated diagnosis or interpretation to assist human readers. The device records physiological parameters for clinicians to interpret.

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

   • Not applicable. The device's stated function is to "measure and record multiple physiological parameters... which are used by clinicians to make a decision on the diagnosis of sleep disorders." It is not presented as a standalone diagnostic algorithm.

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

   • Not applicable for diagnostic ground truth. The "ground truth" for this 510(k) was the predicate device's cleared performance and safety standards, combined with verification and validation of the extended wear time not introducing new risks.

8. The sample size for the training set:

   • Not applicable. This device is not described as involving machine learning or AI that would require a "training set" for diagnostic functions.

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

   • Not applicable.

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This Nitrile patient examination glove is a disposable device intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner, and has also been Tested for Use with Chemotherapy Drugs, the Opioid Fentanyl citrate, simulated Gastric Acid, and Fentanyl in Gastric Acid.

Violet Nitrile Powder Free Patient Examination Glove, Non-Sterile, Tested for Use With Chemotherapy Drugs, the Opioid Fentanyl Citrate, simulated Gastric Acid, and Fentanyl In Gastric Acid

This document describes the Violet Nitrile Powder Free Patient Examination Glove. However, it is a 510(k) premarket notification for a medical device (a glove), not an AI/ML medical device. Therefore, the requested information regarding acceptance criteria and studies related to AI/ML device performance (sample size for test/training sets, data provenance, ground truth establishment, MRMC studies, standalone performance) is not applicable to this document.

The document focuses on the glove's performance with various chemotherapy drugs and fentanyl, and provides test results based on ASTM D6978-05 (2019) for breakthrough times.

Here is the information from Section {2} that is relevant to the glove's performance:

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

The document does not explicitly state "acceptance criteria" in a separate section. However, the reported "Minimum Time Breakthrough" values serve as the device's performance against the challenge of different chemicals. The implicit acceptance criterion for a protective glove would be a sufficiently long breakthrough time. The significant warnings for Carmustine and Thiotepa suggest that their breakthrough times are below a desired protective threshold for those specific chemicals.

Warnings:

• Carmustine and Thiotepa: Have extremely low permeation times of 23.2 min and 67.0 min respectively.
• Not for Use With: Carmustine or Thiotepa.

2. Sample size used for the test set and the data provenance: Not applicable to an AI/ML device. The data shown is chemical permeation testing data for a physical product (glove). The standard ASTM D6978-05 specifies the testing methodology, including sample sizes for physical testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable to an AI/ML device. The "ground truth" here is the chemical breakthrough time, which is measured mechanically/chemically according to a standard.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable to an AI/ML device. This refers to human expert judgment in AI model validation.

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/ML device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI/ML device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The ground truth for the glove's performance is experimentally measured chemical breakthrough time as per the ASTM D6978-05 standard.

8. The sample size for the training set: Not applicable. This is not an AI/ML device.

9. How the ground truth for the training set was established: Not applicable. This is not an AI/ML device.

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This Nitrile patient examination glove is a disposable device intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner, and has also been Tested for Use with the Opioid Fentanyl citrate, simulated Gastric Acid, and Fentanyl in Gastric Acid.

Black Nitrile Powder Free Patient Examination Glove, Non-Sterile, Tested for Use With Chemotherapy Drugs, the Opioid Fentanyl Citrate, simulated Gastric Acid, and Fentanyl In Gastric Acid

This document is a 510(k) premarket notification decision letter from the FDA for a medical device: "Black Nitrile Powder Free Patient Examination Glove". It does not describe an AI/ML powered device, therefore, the requested information regarding acceptance criteria and study details for an AI-based device is not applicable and cannot be extracted from this document.

The document focuses on:

• The FDA's determination of substantial equivalence for the glove to legally marketed predicate devices.
• The regulatory classification and applicable regulations for the device.
• A table of test results for the glove's resistance to various chemotherapy drugs, fentanyl citrate, and simulated gastric acid, along with breakthrough times. This is performance data for the physical glove, not an AI model.

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A Nitrile patient examination glove is a disposable device made of nitrile rubber intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner.

BLUE NITRILE POWDER-FREE PATIENT EXAMINATION GLOVE, NON STERILE

This document is a 510(k) clearance letter from the FDA for a Blue Nitrile Powder-Free Patient Examination Glove, Non-Sterile. It is a regulatory clearance for a medical device and, as such, does not contain the type of information typically found in acceptance criteria or study results for AI/ML-based medical devices.

Therefore, I cannot provide the requested information, which includes:

1. A table of acceptance criteria and the reported device performance: This document is not for an AI/ML device, so no such performance data is present.
2. Sample size used for the test set and the data provenance: Not applicable to a physical glove.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

The document discusses the regulatory process for this type of Class I, reserved medical device, referencing general controls, good manufacturing practices, labeling requirements, and reporting of adverse events. It explicitly states the "Indications for Use" for the glove: "A Nitrile patient examination glove is a disposable device made of nitrile rubber intended for medical purposes that is worn on the examiner's hand or finger to prevent contamination between patient and examiner." This is a description of the intended use of a physical product, not a software algorithm.

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