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The Smith & Nephew Control Digital Operating Room System is indicated for use with compatible endoscopic and surgical equipment for centralized control of these devices and display of device status. The control system provides centralized touch panel and voice control of medical devices for use by the surgeon and O.R. staff.

The proposed Smith & Nephew Control Digital Operating Room System is a computer based system that enables centralized status display and control of multiple medical and non-medical devices through touch panel activation or through an optional voice recognition feature. The primary system consists of a Medical Device Controller, Medical Device Hub, Primary Touch Panel Interface (TPI-P), Surgical Touch Panel Interface (TPI-S), Ethernet Router and AVB network hub and AVB Power Supply. Optional components include: speech recognition engine, a wireless microphone for speech recognition, a wireless touch screen interface that can be bagged and placed in the sterile field, a display controller which allows device settings and conditions to be displayed on the surgeon's monitor.

Here's an analysis of the provided text regarding the Smith & Nephew Control Digital Operating Room System, addressing the requested information:

1. Table of Acceptance Criteria & Reported Device Performance

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

This information is not provided in the document. The submission references "performance testing" but does not detail the methodology, sample sizes, or data provenance (e.g., country of origin, retrospective/prospective nature) for any specific tests performed beyond adherence to general safety and EMC standards.

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

This information is not provided in the document. The submission focuses on substantial equivalence to predicate devices and adherence to regulatory standards, not on clinical-performance-based ground truth established by experts.

4. Adjudication Method for the Test Set

This information is not provided in the document. Given the nature of the device (a control system for existing medical devices) and the focus on substantial equivalence to predicate devices and adherence to regulatory standards, a formal adjudication method for a "test set" in the sense of clinical image or data interpretation is unlikely to have been a primary component of this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not provided and is not applicable to this device. The Smith & Nephew Control Digital Operating Room System is a control system for medical devices, not an AI-powered diagnostic or interpretive tool that would involve "human readers" or "AI assistance" in the typical MRMC study context.

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

This information is not provided and is not entirely applicable in the context of an algorithm's interpretive performance. The device itself is a standalone system for controlling other medical devices. Its "performance" would be assessed in terms of its ability to correctly send commands and display status, which is inherent in its function. No separate "algorithm-only" study examining diagnostic accuracy (as typically implied by this question) would be relevant here.

7. The Type of Ground Truth Used

The "ground truth" used for this submission appears to be:

• Adherence to recognized voluntary standards: IEC 60601-1, IEC 60601-1-1, IEC 60601-1-2, UL 60601-1, CAN/CSA 22.2 No. 601.1 regarding safety and EMC.
• Functional equivalence to predicate devices: The ability of the system to provide "centralized and remote control of medical devices in the O.R." in a manner deemed equivalent to existing, legally marketed systems (Olympus EndoALPHA, HERMES, Sidne™). This implies that the accepted functionality of the predicate devices serves as a benchmark for "ground truth" performance.

No pathology, expert consensus on diagnostic outcomes, or patient outcomes data is mentioned as ground truth.

8. The Sample Size for the Training Set

This information is not provided in the document. As this is a control system for operational devices rather than a machine learning algorithm that is "trained" on data to perform a specific task (e.g., image classification), the concept of a "training set" in the context of AI/ML is not applicable here. Its development would involve software engineering and hardware testing, not a data-driven training process.

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

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

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The SIOS product is intended to optimize procedures in the operating room by providing consistent preoperative, intra-operative and post-operative equipment control, image and data handling, and networking capabilities.

The SIOS product is limited to use with the following products:

• (1) Wolf Endocam 3CCD Endocam 5507,
• (2) Wolf Light Source Auto-CP 5131,
• (3) Wolf Insufflator Laparo CO2 Pacu 2332, and
• (4) Maquet OR Table ALPHAMAQUET 1150.

The Siemens Integrated Operating System (SIOS) is a system capable of networking select medical and non-medical equipment in the operating room (OR) and allowing trained medical personnel direct control of the equipment using remote control (i.e. voice command, touch screen console). The device combines a number of individual functional units through a standard interface to a centralized computer control station.

The provided text is a 510(k) summary for the Siemens Integrated Operating System (SIOS), which is an older document (dated December 15, 1999, with a corrected letter on July 27, 2015). This type of submission focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed standalone performance studies with acceptance criteria as would be expected for a novel AI/ML-driven device today.

Therefore, the document does not contain the detailed information required to populate a table of acceptance criteria, reported device performance, sample sizes for test/training sets, ground truth establishment methods, or information about expert adjudication, MRMC studies, or standalone performance. The SIOS is described as a system for controlling existing medical and non-medical equipment in an operating room and networking capabilities, not a diagnostic or AI-driven interpretative device that would typically undergo such performance evaluations.

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

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

• Cannot be provided. The document does not define specific performance acceptance criteria (e.g., sensitivity, specificity, accuracy for a diagnostic task) for the SIOS. Its purpose is to control other devices and handle data.

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

• Cannot be provided. The document does not describe any specific test set or data used for performance evaluation in the context of a clinical study or diagnostic accuracy assessment. The submission focuses on the functionality and safety of the control system itself.

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)

• Cannot be provided. Since no specific test set requiring expert ground truth is mentioned, this information is not available.

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

• Cannot be provided. This information is not relevant or present in the document given the nature of the device and the 510(k) submission type.

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

• Cannot be provided. An MRMC study is not mentioned. The SIOS is an integrated operating system for control and data handling, not a device that assists human readers in interpreting medical images or data.

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

• Cannot be provided. The SIOS is a system for controlling other devices; it doesn't have an "algorithm-only" performance that would be evaluated in this context. Its function is to facilitate human operators' control of other equipment.

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

• Cannot be provided. No ground truth is established as the device is not making diagnostic or interpretative claims.

8. The sample size for the training set

• Cannot be provided. Training sets are typically associated with machine learning or AI models, which are not described for the SIOS in this document.

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

• Cannot be provided. As no training set is mentioned, this is not applicable.

Summary from the provided document:

The Siemens Integrated Operating System (SIOS) is a control and networking system for operating rooms. The 510(k) submission (K994231) demonstrates its substantial equivalence to predicate devices (HERMES™ Operating Room Control Center and Accessories by Computer Motion, and EndoALPHA™ Integrated Endosurgery System by Olympus). The "study" referenced in this context is the general comparison to these predicate devices, focusing on the technological characteristics and intended use rather than
quantitative performance metrics of a diagnostic or AI algorithm. The core functionality and safety were deemed equivalent by the FDA based on the comparison of features and intended use.

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