Search Results

The AutoCap RX Integrated Biopsy Cap and Guidewire Locking Device is intended to facilitate placement of the guidewire and lock it into place during ERCP procedures. The device access for endoscopic device passage and exchange, helps maintain insufflation, minimizes leakage of biomaterial from the biopsy port throughout the ERCP procedure, and provides access for irrigation.

The AutoCap RX is an integrated biopsy cap and guidewire locking device that fits on the biopsy port of an endoscope. The device is an accessory to be used with endoscopic devices to facilitate device passage, maintain insufflation, and lock the guidewire(s) in place during ERCP procedures. The AutoCap RX combines the locking device and the biopsy cap of the predicate, RX Locking Device and Biopsy Cap (K010610), into one integrated unit.

The provided document is a 510(k) Premarket Notification for a medical device called AutoCap RX. It is a regulatory submission to the FDA demonstrating substantial equivalence to a predicate device. This type of document focuses on engineering and performance validation rather than clinical studies with human participants comparing AI performance.

Therefore, the requested information regarding AI-specific criteria (such as multi-reader multi-case studies, AI effect size, ground truth establishment for AI training sets, etc.) is not applicable to this document.

However, I can extract information related to the device's acceptance criteria and the engineering study that proves it meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the successful completion of specified bench tests, demonstrating the device's ability to perform its intended functions. The performance is reported as "passing."

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

The document does not specify exact sample sizes for each bench test (e.g., number of devices tested for bile leakage). It states that "All testing was passing."

• Sample Size: Not explicitly stated as a number of devices/tests for each criterion, but implied to be sufficient for engineering validation.
• Data Provenance: The tests are "non-clinical performance bench testing" and "simulated use testing." This indicates in-vitro laboratory testing, not human patient data. The country of origin for the data is not specified, but the submission is to the U.S. FDA, implying the tests were conducted to meet U.S. regulatory standards. The data is prospective in the sense that it was generated specifically for this regulatory submission.

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

• Number of Experts: Not applicable. The "ground truth" for these engineering bench tests is defined by objective physical measurements and functional performance criteria as specified in the test protocols, not by expert interpretation of clinical images or data.
• Qualifications of Experts: Not applicable for establishing ground truth in this context. The testing would have been performed by qualified engineers or technicians adhering to established testing standards.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. Adjudication methods (like 2+1 or 3+1) are used for resolving discrepancies in expert interpretations, typically in clinical studies or image review. For bench testing, the results are typically quantitative measurements or pass/fail determinations based on predefined specifications, not subjective interpretation requiring re-adjudication.

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

• MRMC Study: No, an MRMC study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, which is not the subject of this 510(k) submission.

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

• Standalone Performance: No, a standalone algorithm performance evaluation was not done. The AutoCap RX is a mechanical/physical device, not an AI algorithm.

7. The Type of Ground Truth Used

The "ground truth" for this device's performance is based on engineering performance specifications and physical measurements demonstrating the device's ability to facilitate guidewire placement, lock guidewires, maintain insufflation, minimize leakage, and allow for device passage/exchange. It also includes biocompatibility testing against ISO 10993 and sterilization/packaging validation. It is not based on expert consensus, pathology, or outcomes data in a clinical setting.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This is a physical medical device, not a machine learning algorithm that requires a training set.

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

• Ground Truth for Training Set Establishment: Not applicable, as there is no training set for a physical device.

Ask a specific question about this device