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The Apple Medical OB/Mobius Elastic Retractor is indicated for use to assist in nonurgent cesarean deliveries that are routine procedures. It is intended to provide incision retraction and to protect against wound contamination during a cesarean section. It is indicated for use as a surgical retractor for both vertical and transverse incisions.

The Apple Medical OB/Mobius® Elastic Retractor is a sterile disposable abdominal retractor consisting of two flexible plastic rings connected by a sleeve of soft, high yield strength, clear plastic film. The internal ring has a circular cross-section (o-ring) and the external ring has a cruciform cross-section (quad-ring). The inner diameter of the internal o-ring limits the radius of abdominal retraction. The diameter of the external quad-ring is the same as the diameter of the internal o-ring and the sleeve. When completely unwound, the height of the cylinder is 10.6 inches. When the quad ring is rolled down, the sleeve is wrapped around the circumference of the ring reducing the height of the sleeve by 1.5 inches per rotation. Because the sleeve film is radially unyielding, the reduction in height causes the radial retraction of the incision site.

The provided text describes a 510(k) summary for the Apple Medical OB/Mobius® Elastic Retractor. This is a medical device submission, not an AI/ML device, and therefore the information typically requested in an acceptance criteria and study description for AI/ML devices (like sample sizes for test and training sets, ground truth establishment, expert qualifications, adjudication methods, or MRMC studies) is not applicable or present in this document.

The "Testing" section only states: "The Apple Medical OB/Mobius Elastic Retractor has been clinically evaluated for the cesarean section indication and shown to be substantially equivalent to the predicate mechanical abdominal retractors."

Given the information in the document, here's what can be extracted:

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

The document does not explicitly list acceptance criteria in a quantitative or qualitative manner typical for performance metrics. Instead, the basis for approval is "substantial equivalence" to predicate devices. The performance is indirectly described by its intended use and successful clinical evaluation to achieve substantial equivalence.

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

• Sample Size: Not specified in the provided document.
• Data Provenance: Not specified, other than "clinically evaluated." It does not mention country of origin or whether it was retrospective or prospective.

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

• This information is not provided as the device is a physical retractor, not an AI/ML diagnostic tool requiring expert ground truth establishment in the same way. The "clinical evaluation" would likely involve surgeons and medical staff, but specific numbers and qualifications for ground truth are not detailed.

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

• Not applicable/Not specified for this type of device and submission.

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 physical surgical retractor, 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 is a manual surgical instrument, always used with human involvement.

7. The type of ground truth used:

• Not explicitly defined in terms of "ground truth" as it would be for an AI model. The "clinical evaluation" would have assessed the device's performance against clinical outcomes and the performance of existing predicate devices.

8. The sample size for the training set:

• Not applicable/Not specified. This is a physical device, not an AI model requiring a training set.

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

• Not applicable. This is a physical device.

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The Apple Medical OB Mobius Elastic Retractor is indicated for use to assist in laparotomy procedures. It is intended to provide incision retraction and to protect against wound contamination during open surgery.

The Apple Medical OB Mobius Elastic Retractor is used for laparotomy procedures where a transverse suprapubic incision is made in the abdominal wall allowing access to the peritoneal cavity. Once the incision is made, the internal o-ring is manually collapsed and inserted through the abdominal incision where it is allowed to spring open against the parietal peritoneum. The external quad-ring is then pulled upward placing the cylindrical sleeve in tension and the operator rolls the ring down the sleeve until the ring sits firmly against the skin. The radial force of the two rings act to retract the abdominal wall to the desired circular geometry.

The provided text is a 510(k) summary for the Apple Medical OB Mobius Elastic Retractor. It describes the device, its intended use, and its substantial equivalence to predicate devices based on mechanical properties testing. However, it does not contain information typically found in acceptance criteria or a study proving the device meets said criteria for an AI/ML medical device.

The document states:

• "The Apple Medical OB Mobius Elastic Retractor has been shown to be substantially equivalent to the predicate Alexis™ device through mechanical properties testing."
• "The subject device has the same technological characteristics as the predicate devices. The only changes involve a change to the dimensions and labeling for the OB Mobius device. These changes do not affect the safety and effectiveness of the device."

This indicates a comparison to a predicate device, which is a common pathway for 510(k) clearance, rather than a detailed study with acceptance criteria and performance metrics as would be typical for an AI/ML device.

Therefore, many of the requested details about acceptance criteria, study design, and AI-specific metrics (like sample size for test/training sets, expert ground truth, MRMC studies) are not available in this document.

Here's a breakdown of what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance

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

• Not applicable/Not provided. This is a mechanical device, not an AI/ML device relying on "test sets" of data. The "testing" referred to is mechanical properties testing.

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

• Not applicable/Not provided. This is a mechanical device and does not involve establishing ground truth from experts in the way an AI/ML device would.

4. Adjudication method for the test set

• Not applicable/Not provided. No "test set" or human adjudication is described for a mechanical device.

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

• No. This is a mechanical device, not an AI/ML device. MRMC studies are not relevant here.

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

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

7. The type of ground truth used

• Not applicable. For this mechanical device, the "ground truth" for proving substantial equivalence relates to its physical and mechanical properties being comparable to the predicate device, not to diagnostic outcomes.

8. The sample size for the training set

• Not applicable/Not provided. This is a mechanical device, not an AI/ML device using a "training set."

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

• Not applicable/Not provided. This is a mechanical device, not an AI/ML device.

In summary, the provided document details the regulatory clearance of a physical medical device (an abdominal retractor) based on its substantial equivalence to a predicate device, supported by mechanical properties testing. It does not provide the kind of information requested for an AI/ML device's acceptance criteria and validation study.

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