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The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological procedures.

The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic electrosurgical procedures.

The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological and hysteroscopic electrosurgical procedures.

Indications for Use in UROLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological procedures.

Indications for Use in GYNECOLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic hysteroscopic electrosurgical procedures

Indications for Use in UROLOGY and GYNECOLOGY: The KARL STORZ bipolar resectoscopes with HF cable are intended for use by qualified surgeons for cutting, ablation, vaporization, and/or coagulation of tissue during various endoscopic urological and hysteroscopic electrosurgical procedures.

Resectoscopes are used for endoscopically controlled ablation of tissue. They are used for examination, diagnosis and/or therapy in conjunction with endoscopic accessories in medical disciplines such as Urology and Gynecology. A resectoscope is a combined cystoscope (urology) or hysteroscope (gynecology) and electrosurgical instruments and consists of a sheath, obturator, working element and HF electrode.

This document describes the KARL STORZ Bipolar Resectoscopes with HF cable (K221893). It is important to note that this device is not an AI/ML powered device, therefore, many of the typical acceptance criteria and study details related to AI performance, such as sample sizes for test and training sets, expert qualifications, and adjudication methods, are not applicable.

Here's an analysis of the provided information:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a traditional medical device and not an AI/ML powered device, the "acceptance criteria" are based on compliance with recognized standards and design specifications, rather than quantitative performance metrics like sensitivity or specificity.

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

Not applicable for a non-AI/ML medical device. Testing was primarily bench testing to verify engineering specifications and compliance with standards. There is no "test set" in the context of image or data analysis.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. Ground truth, in the context of AI, refers to expert-labeled data. For this device, "ground truth" would be established by engineering specifications and objective measurements against those specifications.

4. Adjudication Method

Not applicable. This is relevant for studies involving human interpretation or labeling of data, which is not the case here.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. This a traditional medical device, not an AI-assisted device, therefore, no such study was conducted to evaluate human reader improvement with AI.

6. Standalone Performance Study

Yes, in a sense. The non-clinical performance data (electrical safety, biocompatibility, and various performance tests) represent the "standalone" performance of the device without human interaction being a variable in the performance assessment itself (though human surgeons use the device). The tests verify the device's inherent functional characteristics and safety.

7. Type of Ground Truth Used

For non-clinical testing of a traditional medical device, the "ground truth" used would be:

• Engineering Specifications: Pre-defined technical requirements for the device's dimensions, material properties, electrical characteristics, mechanical strength, and functional performance.
• Recognized Standards: International (e.g., IEC, ISO) and national standards that set minimum safety and performance requirements for medical devices of this type.
• Comparative Performance to Predicate Device: The performance of the legally marketed predicate device (K210651), which serves as a benchmark for substantial equivalence.

8. Sample Size for the Training Set

Not applicable. This device does not involve machine learning; therefore, there is no "training set."

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

Not applicable. As there is no training set for a machine learning model, establishing ground truth for such a set is irrelevant.

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