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Luja Set is indicated for use by patients with urine retention and patients with post void residual volume (PVR) due to neurogenic and non-neurogenic voiding dysfunction. The catheter is inserted into the urethra to reach the bladder allowing urine to drain.

The product is indicated for male patients only (adults and pediatric above the age of 1 years).

The medical device is an intermittent, ready-to-use, sterile, hydrophilic-coated catheter with integrated urine bag. It contains a catheter with a flexible tip that facilitates passage through the sphincter in the urethra. The catheter is shielded by a sleeve, which serves as protection from the user's hands during insertion. Several small holes (micro-holes) by the straight tip, create a draining zone, which allow the urine to flow from the bladder out through the catheter to a urine bag. The drainage end of the catheter is attached to a urine bag with a tear off section to open the bag for emptying. The catheter is sterilized by radiation. The Luja Set is available in sizes: CH10, CH12, CH14, and CH16.

The provided FDA 510(k) Clearance Letter for the Luja Set indicates that it is a Special 510(k) Notification. This type of submission is used when a modification is made to a manufacturer's own legally marketed device (the predicate device) where the modification does not require a new intended use and the methods for evaluating the changes are well-established.

Crucially, the provided document describes the device itself (a urological catheter), its intended use, and its similarities/differences to a predicate device (Luja Coudé) and a reference device (SpeediCath Flex Set). It details the non-clinical performance testing performed (flow rate and kink stability), but it DOES NOT contain the actual acceptance criteria or the specific results proving those criteria were met.

The document states: "Bench performance testing was conducted to verify the proposed subject devices met the pre-determined acceptance criteria per specified requirements. Testing was performed on final, finished, and sterilized devices as described in the applicable submission sessions." However, the "applicable submission sessions" are not included in this document.

Therefore,Based on the provided document, I cannot fulfill most of the detailed requests regarding acceptance criteria and study particulars because the document does not contain the acceptance criteria or the specific performance data.

Here's what I can extract and state based only on the provided text, along with what cannot be determined:

Acceptance Criteria and Device Performance

• Acceptance Criteria: Not explicitly stated in the provided document. The document only mentions that "the proposed subject devices met the pre-determined acceptance criteria per specified requirements."
• Reported Device Performance: Not explicitly stated in the provided document. The document mentions that "Risk assessment was conducted, and two performance risks were identified: flow rate and kink stability. To support the flow rate and kink stability testing, the SpeediCath Flex Set (K222059) was used as a reference device." However, the actual performance data (e.g., specific flow rates achieved, quantitative kink stability metrics) are not provided.

Study Details (Based on available information and inferences from a 510(k) for a physical medical device)

The information provided is for a physical medical device (urological catheter), not an AI/Software as a Medical Device (SaMD). Therefore, many of the typical questions regarding AI/ML clinical validation studies (like multi-reader multi-case studies, expert adjudication, ground truth establishment for AI models, training set details) are not applicable to this type of device and submission.

Here's a breakdown based on the context of the device:

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

   • Acceptance Criteria: Not listed in the provided document.
   • Reported Device Performance: Not listed in the provided document. The document only states that testing was performed for "flow rate and kink stability."

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

   • Sample Size: Not specified.
   • Data Provenance: Not applicable in the context of a physical device's non-clinical bench testing. This typically refers to clinical data. The testing mentioned (flow rate, kink stability) is bench testing on the device itself.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

   • Not Applicable. This question is relevant for AI/ML or imaging-based devices where human expert readings establish ground truth. For a physical device like a catheter, "ground truth" is established through standardized physical measurements and engineering specifications, not expert consensus interpreting data.

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

   • Not Applicable. See point 3.

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

   • No. This is a physical medical device, not an AI/SaMD. MRMC studies are not relevant here.

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

   • Not Applicable. This is a physical medical device.

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

   • For this device, "ground truth" for non-clinical testing is based on engineering specifications, physical measurements, and adherence to international standards (e.g., ISO 20696:2018 for urethral catheters, ASTM F623-19 for Foley Catheters, as cited). It's not a diagnostic ground truth from patient data like pathology or expert consensus.

8. The sample size for the training set

   • Not Applicable. This device does not involve a "training set" in the context of machine learning.

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

   • Not Applicable. This device does not involve a "training set" in the context of machine learning.

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