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The OpClear® Platform consists of a reusable control unit and a range of disposable sterile single-use accessories intended to remove visual obstructions on the distal window of laparoscopes, such as condensation, blood and other tissue particulates, therefore maintaining a clear image of the surgical site.

The OpClear ®Platform is indicated for use in abdominal laparoscopy.

OpClear® Platform is a laparoscopic lens cleaning device which is intended to be used during any laparoscopic surgical procedure where there is a potential for contamination of the distal lens. Consisting of a reusable control unit and a range of sterile, invasive, single use disposables, it is intended to maintain surgical vision by removing contaminants such as condensation, blood, peritoneal fluid, smoke, fat and tissue smears that have contaminated the distal lens of the laparoscope during surgical procedures.

OpClear® Platform is composed of a control unit and a range of disposable accessories as shown below.

OpClear® Disposables

| OpClear Part # | Diameter | Angle | Working
Length |
|----------------|----------|-----------|-------------------|
| CS-10-00-300 | 10 mm | 0° | 300 mm |
| CS-10-30-300 | 10 mm | 30° / 45° | 300 mm |
| CS-10-00-315 | 10 mm | 0° | 315 mm |
| CS-10-30-315 | 10 mm | 30° / 45° | 315 mm |
| CS-10-00-330 | 10 mm | 0° | 330 mm |
| CS-10-30-330 | 10 mm | 30° / 45° | 330 mm |
| CS-05-00-290 | 5 mm | 0° | 290mm |
| CS-05-30-290 | 5 mm | 30° / 45° | 290mm |
| CS-05-00-300 | 5 mm | 0° | 300mm |
| CS-05-30-300 | 5 mm | 30° / 45° | 300mm |
| CS-05-00-315 | 5 mm | 0° | 315mm |
| CS-05-30-315 | 5 mm | 30° / 45° | 315mm |

This document describes the OpClear® Platform, a laparoscopic lens cleaning device. The submission is a 510(k) for substantial equivalence to an existing predicate device (OpClear® System, K171637). The information provided focuses on the device's technical specifications and comparison to the predicate, rather than a clinical study evaluating its performance against specific acceptance criteria.

Therefore, I cannot fully address all aspects of your request, particularly those related to a clinical study and its acceptance criteria, as such a study is not detailed in the provided text. However, I can extract information related to non-clinical testing and the comparison between the device and its predicate.

Here's a breakdown of what can and cannot be answered based on the provided text:

What can be extracted:

• Acceptance Criteria (Implied Non-Clinical): The document implies that the "suitability" and "performance" of the OpClear® Platform in a simulated abdominal cavity environment were validated by comparing them to the predicate device. However, specific numerical acceptance criteria for performance (e.g., minimum clarity achieved, cleaning time) are not explicitly stated.
• Reported Device Performance (Non-Clinical): The document states that "The performance of the predicate device, OpClear® System and the subject device, OpClear® Platform, have been validated using the same bench model." It then concludes that "The proposed device has the same principles of operation and technological characteristics as the predicate device" and "does not adversely affect safety or effectiveness." This indicates that its performance in the simulated environment was considered comparable or equivalent to the predicate. Specific metrics are not provided.
• Sample Size for Test Set: For non-clinical testing, it mentions "a simulated human abdominal cavity environment." The "sample size" for this bench model is not quantifiable in terms of patient numbers.
• Data Provenance: The "test" (non-clinical validation) was conducted in a "laboratory." No country of origin for the "data" (results of the bench testing) is specified, nor is whether it was retrospective or prospective.
• Adjudication Method: Not applicable for non-clinical bench testing.
• MRMC Comparative Effectiveness Study: Not described. The document focuses on non-clinical bench testing and a comparison to a predicate device for substantial equivalence, not a clinical MRMC study.
• Standalone Performance: The non-clinical testing appears to evaluate the device's functional performance in a simulated environment, which could be considered a form of standalone testing, but no specific metrics are given.
• Type of Ground Truth (Non-Clinical): The ground truth for the non-clinical testing was based on the performance of the predicate device in the same simulated environment, implying that the predicate's performance was the established baseline for "clearness" or "effectiveness" in that setting.
• Sample Size for Training Set: Not applicable. This device is hardware for cleaning, not an AI/ML algorithm that requires a training set in the typical sense.
• How Ground Truth for Training Set was Established: Not applicable.

What cannot be extracted (due to lack of information in the document):

• Explicit numerical acceptance criteria for clinical performance.
• Detailed clinical performance metrics (e.g., success rates, cleaning duration in vivo).
• Sample size for a clinical test set (as no clinical study is described).
• Number of experts, qualifications of experts, or adjudication methods for establishing ground truth in a clinical context.
• Effect size of human readers improving with AI vs. without AI assistance (as no AI component or human reader study is discussed).

Based on the provided text, here is the information that can be extracted, primarily pertaining to the non-clinical validation:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Description: Non-clinical bench testing was performed using "a simulated human abdominal cavity environment."
• Sample Size: Not quantifiable in terms of patient samples; it's a simulated environment. The number of tests performed within this simulation is not specified.
• Data Provenance: The testing was conducted in a "laboratory." The country of origin is not specified, nor is whether the data was retrospective or prospective.

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

• Not applicable for this non-clinical bench testing. The "ground truth" for comparison was the performance of the predicate device in the same simulated environment.

4. Adjudication Method for the Test Set

• Not applicable for this non-clinical bench testing.

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

• No, an MRMC comparative effectiveness study was not described or presented in this document. The submission focuses on substantial equivalence based on technical characteristics and non-clinical bench testing.

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

• The non-clinical "Summary of Non Clinical Testing" describes the device's functional performance in a simulated environment. This can be considered a form of standalone performance evaluation for the device's physical function (cleaning capability), but it's not "algorithm only" and doesn't involve "human-in-the-loop" as in AI-assisted diagnosis.

7. The Type of Ground Truth Used

• For the non-clinical testing, the "ground truth" was established by comparing the performance of the new OpClear® Platform to the legally marketed predicate device (OpClear® System) within the simulated abdominal cavity environment. The predicate's validated performance implicitly served as the acceptable standard.

8. The Sample Size for the Training Set

• Not applicable. The OpClear® Platform is a hardware device for laparoscopic lens cleaning; it does not involve AI/ML algorithms that require a "training set" in the computational sense.

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

• Not applicable, as there is no training set for an AI/ML algorithm.

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The use of the SDC4K Information Management System with Device and Voice Control Package is to allow for voice control and remote control of medical device settings by surgeons or operating room personnel, thereby eliminating the need to manually operate those devices compatible with the SDC4K Information Management System with Device and Voice Control Package or to rely on verbal communication between the surgeon and other operating room personnel in order to adjust the surgical equipment. It also has additional digital documentation functionality capture, transfer, store and display medical device data (non-medical device function), which is independent of the functions or parameters of any attached Stryker device.

The SDC4K Information Management System with Device and Voice Control Package is a network compatible hardware platform that carries out Medical Device Data System (MDDS) functionalities and allows the user to control the state, selection, and settings of compatible connected endoscopic and general surgery devices both wired and wirelessly.

The SDC4K Information Management System with Device and Voice Control Package consists of the following components:

• 1. SDC4K Console which includes:
  • a) Class I Medical Device Data System (MDDS) functionality
  • b) Optional Device Control feature
  • c) Optional Voice Control feature
• 2. Device Control Package (software activation USB dongle and a handheld Infrared (IR) remote control)
• 3. Voice Control Package (software activation USB dongle and a wireless headset and base station)
• 4. Connected OR Spoke (Class I MDDS)

The SDC4K console carries out the Medical Device Data System (MDDS) functionalities (i.e. Class I device function or Non-medical function) and can be marketed as a standalone device. When upgraded with the Device Control and/or Voice Control package, the SDC4K Console extends its functionality to control compatible devices from its touchscreen graphical user interface (GUI), spoken commands via headset (voice control input), and an IR remote control or directional keypad from a camera head (device control input). The received user commands are then processed and communicated with the connected controllable devices, allowing the user to control the state, selection, and settings of those devices. In addition, the SDC4K Information Management System with Device and Voice Control Package also provides compatibility with the Connected OR Spoke (also referred to as "Spoke") which is a standalone Class I Medical Device Data System. Once the SDC4K is connected to the Spoke, Device Control can be extended to compatible devices connected to the Spoke.

The provided FDA 510(k) summary for the SDC4K Information Management System with Device and Voice Control Package outlines its performance data through various tests. However, it does not include a detailed table of acceptance criteria and reported device performance for specific functional metrics, nor does it describe a study design that would prove the device meets such criteria in terms of accuracy or clinical effectiveness.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Connected OR Hub with Device and Voice Control, K212055) by verifying compliance with recognized standards.

Here's an attempt to answer your questions based only on the provided text, highlighting what is included and what is explicitly not included:

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

The document provides a table of tests conducted and their outcomes, indicating "Pass" for each. These are related to safety, EMC, software validation, usability, and bench performance based on specifications and intended use. Specific quantitative performance metrics (e.g., accuracy, latency, success rate for voice control commands) against defined acceptance criteria are not provided.

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

The document does not specify sample sizes for any test sets mentioned (e.g., for usability or bench performance). It also does not mention data provenance, as the tests are primarily engineering and compliance-based rather than involving patient data or clinical studies. The document explicitly states: "the subject device does not require clinical studies to support the determination of substantial equivalence."

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 in the document. The tests described are largely against technical standards and internal specifications, rather than requiring expert consensus on a "ground truth" derived from clinical data.

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

Adjudication methods are not described, as the type of studies conducted (compliance and engineering tests) typically do not involve such processes.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned and is not applicable to this device, as it is an information management and control system, not an AI-assisted diagnostic or interpretative tool. The document states "the subject device does not require clinical studies to support the determination of substantial equivalence."

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

The device itself (SDC4K Information Management System with Device and Voice Control Package) includes human interaction (remote control, voice control, GUI). Therefore, a "standalone algorithm only" performance without human-in-the-loop is not directly relevant or described. The performance bench tests would assess the functionality of the system components and their integration, but not in a purely algorithmic, non-interactive context.

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

The concept of "ground truth" as typically understood in the context of diagnostic or AI performance evaluation (e.g., against pathology reports or clinical outcomes) is not applicable to the type of testing described. The "ground truth" in this context would be the successful execution of device commands, adherence to electrical safety, EMC, software, and usability standards, and meeting internal device input specifications.

8. The sample size for the training set

This information is not applicable and not provided. The device is an information management and control system, not a machine learning or AI algorithm that relies on a "training set" for its core function (beyond potentially voice recognition models, which are likely integrated commercial solutions and their training data is not discussed here).

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

This information is not applicable and not provided for the reasons stated in point 8.

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