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This device is to be used to protect and retract an incision in the abdominal wall. This is accomplished by placing one o-ring through the incision into the peritoneum cavity while the other o-ring remains outside of the incision. The outside o-ring is then rolled down against the skin. This lines the wound to protect against contamination and holds the incision open.

The PROTECTOR® Retractor is a sterile, disposable device. The PROTECTOR® Retractor consists of an open-ended cylinder with a flexible o-ring at each end. The PROTECTOR® Retractor with a drape is the same configuration, except that it has a drape that is an integral part of it.

This 510(k) summary provides limited information regarding detailed acceptance criteria and a formal study proving device performance against specific metrics. It primarily focuses on demonstrating substantial equivalence to predicate devices through a combination of lab testing, pig studies, and clinical observations.

However, based on the provided text, I can infer and extract some information, although it will be less structured than requested for typical AI/ML device evaluations.

Here's an attempt to answer your questions based on the provided text:

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

Based on the document, explicit quantitative acceptance criteria are not stated. The performance assessment is qualitative and comparative.

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

• Test Set Sample Size:
  • Pilot Clinical: 41 subjects
  • Pivotal Clinical: "presently in a pivotal clinical." (Ongoing, so the "to date" results are based on an unspecified number of subjects from this ongoing study).
  • Lab Testing: "on a fake abdominal wall" (sample size not specified).
  • Pig Studies: (sample size not specified).
• Data Provenance: Not specified (e.g., country of origin). The clinical studies are described as "pilot clinical" and "pivotal clinical," indicating they are prospective clinical trials.

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)

The document does not mention the use of experts to establish "ground truth" in the sense of independent review for diagnostic accuracy, as might be typical for AI/ML devices. The "ground truth" here seems to be the direct observation of the device's function and safety by clinical staff during the pilot and pivotal clinical studies. The qualifications of these clinical staff are not detailed.

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

No formal adjudication method is described for the clinical data. The summary states "The results of the pilot clinical... is that the PROTECTOR® Retractor works safely and effectively," suggesting direct clinical observation and judgment.

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. This is a medical device for surgical retraction and wound protection, not an AI/ML diagnostic imaging device. Therefore, an MRMC study and effects on human reader performance are not applicable or described.

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

Not applicable. This is a physical medical device, not an algorithm. Performance is inherently "standalone" in that its physical function is evaluated, but it is always used "with human-in-the-loop" during surgery.

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

The "ground truth" for demonstrating the device's function appears to be:

• Direct observation of physical performance in lab tests ("fake abdominal wall").
• Direct observation of physical performance in animal studies ("pig studies").
• Direct observation of clinical function (wound protection, wound retraction) and safety in human subjects during pilot and pivotal clinical studies. This would likely involve surgeon's assessment and patient outcomes.

8. The sample size for the training set

Not applicable. This is a physical 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, as there is no "training set" for a physical device.

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