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StitchKit® Suture Delivery Canister facilitates minimally invasive robotic surgery by transporting suture to the operative field and removing used needles after suturing. The suture contained within the device is intended for soft tissue approximation where use of the specific absorbable or non-absorbable sutures contained within it is appropriate.

StitchKit® is a sterile, single-use plastic canister that is provided pre-loaded with suturing materials with attached needles. The device facilitates endoscopic robotic surgery by introducing multiple strands of suture to the surgical site at one time and allowing for the safe retrieval of the needles. The canister is sized to be passed through a ≥12 mm trocar or passed through an incision sized for an 8 mm trocar under direct endoscopic visualization. As suturing is completed with each strand, the used needle is placed into a compartment within the canister for safekeeping until the entire canister is removed either through the ≥ 12 mm trocar or through the 8mm trocar incision in tandem with the 8mm trocar, also under direct endoscopic visualization using the attached retrieval string. It is supplied sterile.

The provided text describes a 510(k) premarket notification for a medical device called StitchKit®. This document primarily focuses on demonstrating substantial equivalence to a predicate device, specifically for a minor modification related to the device's insertion and removal method (allowing use through an 8mm trocar incision in addition to a 12mm trocar).

Crucially, this document does NOT describe the acceptance criteria or a study proving the device meets performance criteria for a complex AI/ML medical device. The device in question is a suture delivery canister, a physical surgical tool, not an AI or imaging device. Therefore, many of the requested points related to AI/ML device validation (like expert adjudication, MRMC studies, ground truth for training/test sets, effect size of human reader improvement with AI assistance, and standalone AI performance) are not applicable to this submission.

The "clinical data" mentioned (retrospective case review n=422) is cited in the context of supporting the modification to the instructions for use, not for establishing the core performance of an AI algorithm. The performance data section refers to "functional performance test consisting of simulated surgical testing in an animal model" to demonstrate compatibility with the new insertion/removal technique, which is a physical device test, not an AI/ML study.

Therefore, I cannot fulfill most of your request for an AI/ML device, as the provided document pertains to a physical surgical device and its minor instruction for use modification.

However, I can extract the safety and efficacy information relevant to this device (the StitchKit® suture delivery canister) as presented in the document, acknowledging that it doesn't align with the detailed AI/ML validation questions.

Based on the provided document for the StitchKit® Suture Delivery Canister (a non-AI device):

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

The document does not specify formal, quantitative acceptance criteria for device performance in the typical sense of accuracy, sensitivity, or specificity, as it's a physical tool. Instead, the "performance" demonstrated relates to its functional compatibility with a new surgical technique.

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

• Test Set (for the modification validity):
  • Sample Size: n=422 (Cited as a "retrospective case review clinical study").
  • Data Provenance: Conducted by "an academic medical center." The country of origin is not specified but is implicitly in the US due to FDA submission. The study was retrospective.
• Functional Performance Test: Conducted in an "animal model." Sample size for this specific test is not provided.

3. 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, not an AI/ML diagnostic or image analysis device where "ground truth" would be established by experts interpreting medical data. The "ground truth" for the retrospective case review would likely be the surgical outcomes or successful use reported in the patient records.

4. Adjudication method for the test set

• Not Applicable. As above, no expert adjudication process is described or relevant for this type of device and study.

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. No MRMC study was done, as this is not an AI-assisted diagnostic device.

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

• Not Applicable. No standalone algorithm performance was evaluated, as this is not an algorithm-based device.

7. The type of ground truth used

• For the retrospective case review (n=422), the "ground truth" would be derived from clinical records and surgical outcomes related to the use of the device in actual patient cases, rather than expert interpretation of images or pathology. The document doesn't explicitly state how "success" or "performance" was quantified from these cases, but it supports the safety/effectiveness of the device, particularly with the proposed instruction modification.
• For the animal model functional test, the "ground truth" was direct observation of the device's physical handling and compatibility with the 8mm trocar site.

8. The sample size for the training set

• Not Applicable. There is no "training set" as this is not an machine learning model.

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

• Not Applicable. No training set was used.

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StitchKit® Suture Delivery Canister facilitates minimally invasive robotic surgery by transporting suture to the operative field and removing used needles after suturing. The suture contained within the device is intended for soft tissue approximation where use of the specific absorbable or non-absorbable sutures contained within it is appropriate.

StitchKit® is a suture delivery canister which facilitates endoscopic robotic surgery by introducing multiple strands of different suturing materials to the surgical site at one time and allowing for the safe retrieval of the needles. It is sized to be passed through a ≥12 mm trocar. As suturing is completed with each strand, the used needle is placed into a disposal compartment within the canister for safekeeping until the entire canister is removed through the trocar using the attached retrieval string. It is supplied sterile. Each StitchKit® contains strands of existing legally-marketed Suturing Materials, cleared for use within the device.

The provided document is a 510(k) summary for the StitchKit® Suture Delivery Canister, which is a Class II medical device. This document details the device's indications for use, technological characteristics, and substantiates its substantial equivalence to predicate devices, rather than presenting a study to prove acceptance criteria in the typical sense of a human-in-the-loop AI effectiveness study.

The device itself is a delivery system for existing sutures and not an AI-powered diagnostic or assistive device. Therefore, many of the requested criteria related to AI performance, AI effect size on human readers, expert ground truth, and training data are not applicable to this submission.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the StitchKit® are based on demonstrating substantial equivalence to legally marketed predicate devices. The performance data provided focuses on the physical and chemical properties of the device and its included sutures.

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

The document does not specify a "test set" in the context of an AI study. Instead, it refers to various forms of performance testing on the device and its components. The document doesn't provide specific sample sizes for these tests (e.g., number of sutures tested for tensile strength or number of canisters tested for pyrogenicity). The provenance of the data (e.g., country of origin, retrospective/prospective) is also not specified, as this type of information is typically not included in a 510(k) summary for a physical device.

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

Not applicable. As this is not an AI or diagnostic device, there is no "ground truth" established by experts in the context of image interpretation or clinical diagnosis. The performance criteria are based on objective physical/chemical tests.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

Not applicable. As there are no expert interpretations or subjective assessments requiring adjudication, no such method was used.

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 StitchKit® is a physical surgical delivery device and does not involve AI or human readers for diagnostic assistance. Therefore, an MRMC study and AI effect size are irrelevant.

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

Not applicable. This device does not involve an algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The "ground truth" for this device's performance validation is based on established engineering and material science standards (e.g., USP standards for suture properties, LAL pyrogen testing standards, physicochemical analysis). It's not clinical "ground truth" derived from patient outcomes or expert consensus on a diagnosis.

8. The Sample Size for the Training Set

Not applicable. There is no AI component requiring a training set.

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

Not applicable. There is no AI component requiring a training set and associated ground truth.

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