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The 3M™ Comply™ 1248 Gas Plasma Chemical Indicator is indicated for use as an internal pack process indicator to indicate exposure to vapor hydrogen peroxide in the STERRAD® 100, STERRAD® 100S, and STERRAD® 50 Sterilization processes.
The 3M™ Comply™ 1248 Gas Plasma Chemical Indicator is indicated for use as an internal pack process indicator to verify exposure to vapor hydrogen peroxide in the STERRAD® 100, STERRAD® 100S, and STERRAD® 50 Sterilization processes. The chemical indicator bar turns from blue to pink after exposure to vapor hydrogen peroxide in these sterilization processes.

The 3M Comply 1248 Gas Plasma Chemical Indicator is a sterilization process indicator and is comprised of a blue chemical indicator ink bar printed on a white plastic strip. A comparison color match is also printed on the plastic strip, below the blue indicator ink bar. The chemical indicator changes color from blue to pink upon exposure to vapor hydrogen peroxide in the STERRAD®100, STERRAD®100S and the STERRAD®50 Sterilization processes.

The provided text describes the acceptance criteria and study results for the 3M™ Comply™ 1248 Gas Plasma Chemical Indicator.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the numerical sample size for the test set (number of indicators tested in each condition). Instead, it uses phrases like "all indicators" or "the Comply™ 1248 Gas Plasma Chemical Indicators" without quantifying.

The data provenance is not explicitly stated as "country of origin" or "retrospective/prospective." However, the tests were conducted by the manufacturer, 3M Company, based in St. Paul, MN, USA. The testing appears to be prospective, specifically designed to demonstrate the device's performance against defined criteria.

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

This type of chemical indicator relies on a direct physical color change, which is then compared to a "comparison color match" printed on the indicator itself. The "ground truth" for the color change is the pre-defined comparison color. Therefore, there is no mention of human experts (like radiologists) being used to establish the ground truth for the color change interpretation in the provided text. The color change is an objective, visual comparison against a standard.

4. Adjudication Method for the Test Set

Not applicable. The "adjudication method" typically refers to how discrepancies in human interpretation of results are resolved. Since the device's performance is based on an objective color change compared to a printed standard, and no human interpretation requiring adjudication is mentioned, this section is not relevant.

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 a chemical indicator, not an AI-assisted diagnostic device that would involve human readers or MRMC studies.

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

The device itself is a "standalone" chemical indicator. Its performance is evaluated based on its physical properties (color change) in response to stimuli, without any "human-in-the-loop" interpretation beyond observing the color and comparing it to the reference. There is no algorithm involved.

7. The Type of Ground Truth Used

The ground truth used is an objective, pre-defined color standard (the "comparison color match" printed on the plastic strip) for evaluating the chemical indicator's color change. Additionally, the ground truth for "pass" or "fail" is tied to exposure to specific sterilization cycles (STERRAD 100, 100S, 50) and also includes conditions where a color change should not occur (absence of H2O2, steam, EO, acid/base sensitivity tests).

8. The Sample Size for the Training Set

Not applicable. This is a chemical indicator, not a machine learning device that requires a "training set."

9. 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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To be used for cleaning and polishing procedures as part of a professionally administered prophylaxis treatment.

3M™ Clinpro™ Prophy Paste is composed of an abrasive, a flavorant, a colorant, and also contains fluoride.

The provided text is a 510(k) summary for a dental product, 3M™ Clinpro™ Prophy Paste. This type of regulatory submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting a full clinical study with specific acceptance criteria, test sets, and expert evaluations as would be expected for a diagnostic AI device.

Therefore, much of the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment cannot be found in the provided text because it's not relevant to this type of device and regulatory submission.

However, I can extract what is available and explain why other information is absent.

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

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

Explanation: The document does not specify quantitative acceptance criteria (e.g., "stain removal must be >X%"). Instead, it states that the device has "similar technological characteristics" and that "comparative results of the bench tests" further validate this similarity. The acceptance criterion is implied to be "demonstrating similar performance" to the predicate devices in these specific bench tests, allowing the FDA to determine substantial equivalence.

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 for Test Set: Not specified.
• Data Provenance: Not specified.
  • The studies mentioned are "bench tests" (laboratory tests), not clinical studies involving human patients or data from a specific origin.

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)

• Number of Experts: Not applicable/Not specified.
• Qualifications of Experts: Not applicable/Not specified.

Explanation: As this involves bench testing of a dental paste (material properties), expert clinical consensus is not the method for establishing "ground truth." The "ground truth" for these tests would be the measured results of the predicate devices for comparison.

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

• Adjudication Method: Not applicable/Not specified.

Explanation: Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where multiple human readers interpret medical images or data to establish a consensus (ground truth). This is not relevant to laboratory bench testing of a dental paste.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• MRMC Comparative Effectiveness Study: No.
• Effect Size: Not applicable.

Explanation: The device is a prophylactic dental paste, not an AI or diagnostic tool that assists human readers. Therefore, an MRMC study is not relevant.

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

• Standalone Performance Study: Not applicable.

Explanation: This is not an algorithm or AI device; it's a physical dental product. Standalone performance refers to the performance of an AI algorithm without human input.

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

• Type of Ground Truth: The "ground truth" for the bench tests would be the measured performance of the predicate devices in stain removal, surface roughness, and relative dentin and enamel abrasion. The new device's performance is compared directly to these established benchmarks.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable.

Explanation: "Training set" refers to data used to train machine learning models. This is a physical product, not an AI model, so there is no training set.

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

• How Ground Truth for Training Set was Established: Not applicable.

Explanation: As there is no training set, this question is not relevant.

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The 3M Littmann™ Electronic Stethoscope is a diagnostic aid and used as part of a physical assessment of a patient by a Health Care Professional. It can be used for the amplification of faint heart, lung and other body sounds as well as normal auscultation and selective frequency filtering. The extended range mode amplifies sounds in a broad frequency range, including a range higher than the traditional diaphragm mode, where some lung and heart sounds may occur, as well as providing low frequency response at a slightly reduced level compared to the bell mode.

The 3M Littmann™ Electronic Stethoscope is a diagnostic aid and used as part of a physical assessment of a patient by a Health Care Professional. It can be used for the amplification of faint heart, lung and other body sounds as well as normal auscultation and selective frequency filtering. The extended range mode amplifies sounds in a broad frequency range, including a range higher than the traditional diaphragm mode, where some lung and heart sounds may occur, as well as providing low frequency response at a slightly reduced level compared to the bell mode.

This 510(k) submission for the 3M Littmann™ Electronic Stethoscope does not provide the detailed acceptance criteria and study data in the format requested. The document describes non-clinical testing for frequency response and gain to establish substantial equivalence to a predicate device, but it does not specify quantitative acceptance criteria or report performance against such criteria in a structured manner.

Here's an breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

No explicit table of acceptance criteria or quantitative performance metrics against these criteria is provided in the document. The submission focuses on demonstrating "substantial equivalence" to a predicate device through non-clinical testing.

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

The document describes non-clinical testing using a "computerized audio analysis system" and a "transducer." This indicates a laboratory setup, not a clinical test set with patient data. Therefore, there's no information about:

• Sample size: Not applicable as it's not a clinical test involving a "test set" of patient data.
• Data provenance: Not applicable. The testing is described as lab-based.

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

Since this was a non-clinical, lab-based test for frequency response and gain, there were no human "experts" establishing ground truth in the clinical sense (e.g., radiologists interpreting images). The ground truth for the frequency response test would be the known input frequencies and amplitudes generated by the swept frequency oscillator.

4. Adjudication Method for the Test Set:

Not applicable. There was no human interpretation or adjudication involved, as it was a non-clinical, instrumental test.

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

No, an MRMC comparative effectiveness study was not done. The testing described is non-clinical, focusing on the device's physical properties (frequency response and gain) compared to a predicate device. It does not involve human readers using the device with or without AI assistance.

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

The device itself is an electronic stethoscope, designed to be used by a human healthcare professional. The "non-clinical testing" described is effectively a standalone performance test of the device's technical specifications (frequency response and gain) in a controlled lab environment. However, the document doesn't present it as an "algorithm only" study in the modern sense of AI device evaluation. It's a characterization of the physical device.

7. Type of Ground Truth Used:

The ground truth for the non-clinical testing was the known, controlled audio frequencies and amplitudes generated by the "frequency oscillator" and presented to the stethoscope via a transducer. This is objective, physical measurement data, not expert consensus, pathology, or outcomes data.

8. Sample Size for the Training Set:

Not applicable. This device is an electronic stethoscope, not an AI/ML algorithm that requires a "training set" in the context of machine learning model development. The document describes a physical product.

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

Not applicable, as there is no training set for an AI/ML algorithm.

Summary of what is available from the provided text:

The provided 510(k) summary focuses on demonstrating substantial equivalence of the 3M Littmann™ Electronic Stethoscope to a predicate electronic stethoscope through non-clinical testing of its physical characteristics (frequency response and gain).

• Acceptance Criteria (Implicit): The implicit acceptance criteria were that the frequency response and gain of the new device should be "substantially equivalent" to the predicate, with intentional differences designed for improvement (e.g., improved bell mode, reduced noise in diaphragm mode, reduced masking in extended range mode).
• Study: A non-clinical study using a computerized audio analysis system.
  • A frequency oscillator swept frequencies from 10 to 5000 Hz.
  • The stethoscope was placed on a transducer receiving these frequencies.
  • A calibrated microphone in the eartip measured the stethoscope's response.
  • The computer recorded and stored this response.
  • This was performed for each of the three frequency response modes.
• Conclusion: The manufacturer concluded that the device performs "as well as, and in many cases substantially better than the predicate electronic stethoscope" based on these measurements, justifying the intentional design differences.

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The product is intended for use in infection control practices to minimize contamination caused by exhaled microorganisms. In addition, the device is intended to reduce potential exposure of the wearer to blood and body fluids.

The 1830/1830FS is a flat, pleated, tie-on mask consisting of inner and outer cover webs with two different filter webs sandwiched in between. It covers the nose and mouth of the wearer, and is held in place by tie strings and a malleable plastic coated wire nose piece.

The provided text describes testing conducted for a surgical mask (3M 1830/1830FS) for 510(k) clearance, intending to demonstrate substantial equivalence to predicate devices. The "acceptance criteria" and "device performance" in this context refer to the performance standards met by the new device during testing, rather than a clinical study of AI performance.

Here's the information extracted and formatted:

Acceptance Criteria and Device Performance

Study Details (as applicable to a medical device clearance, not AI)

Given that this document is for a 510(k) clearance of a surgical mask from 1997, it does not involve AI, diagnostic algorithms, or clinical studies of human readers using AI. Therefore, many of the requested points are not applicable.

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

   • The document does not specify the sample sizes for the individual performance tests (e.g., number of masks tested for BFE, PFE, or fluid resistance).
   • The data provenance is not explicitly stated beyond being part of a 3M product submission in the United States (K965043). The tests are standard industry tests.

2. 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 performance study, not a study requiring expert consensus for ground truth on medical images or diagnoses.

3. Adjudication method for the test set:

   • Not applicable. This type of performance testing for a physical device does not typically involve expert adjudication in the same way clinical studies with human assessors do.

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 submission is for a surgical mask, not an AI-powered diagnostic device.

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

   • Not applicable. No algorithm is involved. The performance tests are for the physical properties of the mask.

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

   • The "ground truth" for these tests is defined by the standardized methodologies of the tests themselves (e.g., measuring filtration efficiency using specified particle challenges, or fluid resistance under controlled pressure).

7. The sample size for the training set:

   • Not applicable. This device does not use a "training set" in the context of machine learning.

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

   • Not applicable. There is no training set for an AI algorithm.

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The ECG lead wire is intended only for the purpose of connecting an ECG monitoring electrode to either an ECG monitor trunk cable or directly into a monitor or transmitter and conducting the patients ECG signal.

This device is a patient lead wire. These patient lead wires are manufactured from a variety of electronic conductors, electronic insulating materials, patient end termination and patient lead wire connectors. This variety of materials and assembly configurations is needed to allow for designs that would be disposable, reusable, x-ray translucent or non x-ray translucent. These materials are all typically and commonly used by other companies participating in the market.

The provided text describes a 510(k) submission for 3M Red Dot™ ECG Lead Wires and does not contain information about acceptance criteria or a study proving device performance against such criteria. The document focuses on the device description, regulatory classification, and predicate devices.

Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them, as this information is not present in the provided text.

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