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The 3M™ Littmann® Electronic Stethoscope Model 3000 is intended for medical diagnostic purposes only. It may be used for the detection and amplification of sounds from heart, lungs, arteries, veins, and other internal organs with the use of a selective frequency. It can be used on any person undergoing a physical assessment.

The 3M™ Littmann® Electronic Stethoscope, Model 3000 is a healthcare device that picks sounds of the heart, arteries, veins, lung and other internal organs, electronically amplifies, filters, and transfers them to the user's ears via an active speaker and passive sound tubes. The Model 3000 provides two filter frequency modes for auscultation: Bell (20-200 Hz) and Diaphraqm (100-500 Hz). The Model 3000 incorporates embedded software. The embedded software controls all of the various features found in the Model 3000 stethoscope, such as volume control and frequency mode selection. In addition, the embedded software provides digital signal processing (DSP) over the entire acoustic range of the stethoscope: DSP produces the bell and diaphragm frequency response modes that are used to listen to heart, lung, and other body sounds. The Model 3000 does not incorporate any off-the-shelf (OTS) software. The Model 3000 operates on one (1) AAA alkaline battery.

The provided document is a 510(k) Premarket Notification Summary for the 3M™ Littmann® Electronic Stethoscope, Model 3000. It details modifications made to the device's embedded software and asserts its substantial equivalence to a predicate device.

However, the document does not contain information regarding acceptance criteria or a study that proves the device meets specific performance criteria in the way a typical AI/ML medical device submission would. This is because the submission is for a classic medical device (electronic stethoscope) where the focus is on functional equivalence and safety rather than a diagnostic performance study with statistical endpoints.

Specifically, for the questions asked, the submission does not contain the following information:

1. A table of acceptance criteria and the reported device performance.
2. Sample size used for the test set and data provenance.
3. Number of experts used to establish ground truth and their qualifications.
4. Adjudication method for the test set.
5. Information on a multi-reader multi-case (MRMC) comparative effectiveness study or effect size.
6. Information on standalone (algorithm only) performance.
7. The type of ground truth used.
8. The sample size for the training set.
9. How the ground truth for the training set was established.

Analysis of the Provided Text:

The relevant section for performance and equivalence is "6. Comparative Data for Determining Substantial Equivalence of New Device to Predicate Device." It states:

"The Model 3000 as modified in this special pre-market notification submission is composed of the same or substantially equivalent materials, has the same performance features, same intended use, same indications for use, and same labeling as the Model 3000 predicate device cleared under K041934."

This statement indicates that the manufacturer is demonstrating equivalence based on the device having the same performance features as its predicate, rather than presenting new performance data against specific acceptance criteria. The modifications were to embedded software, and the submission explicitly states: "The modifications included in this submission do not affect the device's intended use or indications for use, performance features, labeling or claims."

Therefore, the "study" proving the device meets acceptance criteria, in this context, is the demonstration of substantial equivalence to the predicate device by asserting that the modifications made do not alter its performance features, intended use, indications for use, or labeling. No specific quantitative performance study with a test set, ground truth, or expert review is mentioned because it's not relevant to this type of submission for this particular device modification.

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The 3M™ Littmann ® Electronic Stethoscope Model 3000 is intended for medical diagnostic purposes only. It may be used for the detection and amplification of heart, lungs, arteries, veins, and other internal organs with the use of a selective frequency. It can be used on any person undergoing a physical assessment.

The 3M™ Littmann® Electronic Stethoscope, Model 3000 is a healthcare device that picks sounds of the heart, arteries, veins, lung and other internal organs, electronically amplifies, filters, and transfers them to the user's ears via an active speaker and passive sound tubes. The Model 3000 provides two filter frequency modes for auscultation: Bell (20-200 Hz) and Diaphragm (100-500 Hz). The Model 3000 incorporates embedded software. The embedded software controls all of the various features found in the Model 3000 stethoscope, such as volume control and frequency mode selection. In addition, the embedded software provides digital signal processing (DSP) over the entire acoustic range of the stethoscope; DSP produces the bell and diaphragm frequency response modes that are used to listen to heart, lung, and other body sounds. The Model 3000 does not incorporate any off-the-shelf (OTS) software. The Model 3000 operates on one (1) AAA alkaline battery.

The provided text describes the 3M™ Littmann® Electronic Stethoscope, Model 3000, and its submission for 510(k) clearance. The document focuses on establishing substantial equivalence to predicate devices (Model 4000 and Model 2000) rather than providing detailed acceptance criteria and a study to prove they are met.

Therefore, many of the requested details cannot be extracted directly from the given text.

Here's an analysis based on the information available:

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

The document does not explicitly state "acceptance criteria." Instead, it provides a "Comparison of Performance Features" with predicate devices to demonstrate substantial equivalence. These performance features act as de-facto criteria for the new device based on the predicate devices' established performance.

Study Proving Device Meets Acceptance Criteria:

The provided document does not describe a formal clinical study or a specific test report detailing how the Model 3000's performance was rigorously measured against predefined acceptance criteria. Instead, it relies on a comparative analysis with predicate devices to establish substantial equivalence based on similar design and performance features. The underlying assumption is that because the predicate devices were cleared, and the new device is "substantially equivalent" in its relevant performance aspects, it also meets the necessary safety and effectiveness requirements.

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

Not applicable. No specific test set or clinical study is described. The comparison is based on the device's inherent design and specifications relative to the predicate devices.

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

Not applicable. Expert-established ground truth for a test set is not mentioned as part of this 510(k) submission, which focuses on substantial equivalence to existing devices.

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

Not applicable. No test set or human adjudication method is described.

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 device is an electronic stethoscope, not an AI-assisted diagnostic tool.

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

Not applicable. This device is not an algorithm that performs standalone analysis. It is a tool for human practitioners.

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

Not applicable. The submission relies on a comparison of device specifications and intended use against predicate devices, not on a ground truth for diagnostic accuracy. The "truth" in this context is established by the functional parameters matching or being acceptably similar to those of a previously cleared device.

8. The sample size for the training set

Not applicable. No training set is mentioned as this is not an AI/machine learning device.

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

Not applicable. No training set is mentioned.

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