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The Intuitive Surgical EndoWrist® Stapler 45 Reloads and other Stapler Accessories are intended to be used with the da Vinci System (Model 154000) for resection, transection and/or creation of anastomoses in General, Thoracic, Gynecologic, and Urologic surgery. The device can be used with staple line or tissue buttressing material (natural or synthetic).

The Intuitive Surgical EndoWrist Stapler 45, Stapler 45 Reloads and Accessories is a reusable surgical stapler system designed for use exclusively with the Intuitive da Vincio Surgical System (Model IS4000). It is intended for resection, transection and/or creation of anastomoses in General, Thoracic, Gynecologic, and Urologic surgery by placing multiple staggered rows of implantable staples in the target tissues (stapling) followed by cutting of the target tissue along the middle of the staple line (transection).

The implantable staples, trade name Stapler 45 Reloads, are provided in a separate single use cartridge and are available in the following three configurations to accommodate tissues of various thickness:

• 2.5 mm staple size single use reload (White Reload) .
• . 3.5 mm staple size single use reload (Blue Reload)
• 4.3 mm staple size single use reload (Green Reload)

Accessories, including cannulae, obturators, a cannula seal, and a cannula reducer, are provided to support the interface of the EndoWrist Stapler 45 with the da Vinci Surgical System (Model IS4000).

Here's a breakdown of the acceptance criteria and study information for the EndoWrist® Stapler 45 and Stapler 45 Reloads, based on the provided 510(k) Summary:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes the performance data in a qualitative manner, focusing on the types of tests conducted rather than specific quantitative acceptance criteria or numerical results. The primary "performance" stated is that the device "is substantially equivalent to the predicate device and that the design output meets the design input requirements."

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

• Animal Survival Studies: The document states that these studies involved "side-by-side comparison between subject and predicate devices."
  • Small bowel anastomoses: Not specified, but involved both subject and predicate devices.
  • Gastrectomy: Not specified, but involved both subject and predicate devices.
  • Lung Resection: Not specified, but involved both subject and predicate devices.
  • Pneumonectomy: Not specified, but involved both subject and predicate devices.
• Staple formation and transection testing: Not specified.
• Buttress material compatibility testing: Not specified.
• Burst pressure testing: Not specified.
• Human Factors and Usability Testing: Not specified for the number of users (surgeons and operating room staff) or the number of scenarios/cases.
• Data Provenance: The studies are described as "animal cadaver models" for some tests, and "summative usability validation studies... conducted in a simulated operating room." There is no mention of country of origin, retrospective, or prospective nature for the animal or bench testing data. Usability testing appears prospective given the "simulated operating room" setting.

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

• Animal Studies: The report mentions "animal cadaver models" and "various reloads and buttress materials" but does not specify the number of experts or their qualifications for establishing the "ground truth" (e.g., successful anastomosis, proper staple line, lack of leaks). It can be inferred that veterinary or surgical experts would assess the outcomes.
• Human Factors/Usability Testing: The "users (surgeons and operating room staff)" likely served as the evaluators of the device's usability, functioning as the "experts" in this context. Their specific qualifications (e.g., years of experience) are not provided.

4. Adjudication Method for the Test Set:

Not explicitly stated. For the animal studies, it's implied that specific criteria related to surgical outcomes (e.g., successful anastomosis, lack of complications) were assessed. For usability, it's likely a qualitative assessment based on observation and feedback from the participating users.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC comparative effectiveness study was not conducted. This type of study typically evaluates diagnostic devices where multiple readers interpret cases. The device in question is a surgical stapler, and the performance evaluation focused on its mechanical function and surgical outcomes in animal models and human factors in simulated environments.

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

This question is not applicable as the device is a mechanical surgical instrument, not an AI algorithm. Its performance is always "human-in-the-loop" as it is operated by a surgeon.

7. The Type of Ground Truth Used:

• Animal Studies: The ground truth would be based on physiological or anatomical outcomes (e.g., successful healing of anastomoses, absence of leaks, proper lung function) assessed post-procedure or during follow-up. This implicitly relies on expert assessment of biological outcomes.
• Bench Testing: Ground truth would be based on engineering specifications and measurements (e.g., staple dimensions, force required for transection, burst pressure).
• Human Factors/Usability Testing: Ground truth was user feedback and observations of safe and effective execution of tasks in a simulated environment by surgeons and operating room staff.

8. The Sample Size for the Training Set:

The document does not mention a "training set" in the context of machine learning or AI. This device is a mechanical surgical stapler, and its development would typically involve iterative design, prototyping, and testing, rather than an AI training/test set paradigm.

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

Not applicable, as there is no mention of a training set for an AI algorithm.

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