Search Results

Bicanalicular intubation is indicated in treatments of epiphora in adults. Indications for bicanalicular intubation performed with the Self-Retaining Bicanaliculus Stent II are:

• . Punctal stenosis
• . Canalicular stenosis within the lacrimal drainage system

The Self-Retaining Bicanaliculus Intubation Set II is a bicanalicular intubation device for the treatment of epiphora in adults. The device consists of two silicone anchors connected to a silicone body that is delivered pre-mounted on two guides and packaged with a disposable dilator. The guides facilitate insertion of the Self-Retaining Bicanaliculus Intubation Set II and are completely removed once insertion of the device is complete. The Self-Retaining Bicanaliculus Intubation Set II comes in three different model lengths (25, 30, or 35 mm depending on length of tube required) and is provided as a sterilized product.

The provided text describes a medical device, the "Self-Retaining Bicanaliculus Intubation Set II," and its substantial equivalence to a predicate device. It includes non-clinical test results and a brief summary of a clinical study, but it does not include the information requested in your prompt regarding acceptance criteria, a study proving the device meets these criteria, or details about AI algorithms.

The device is a physical medical device (lacrimal stent and intubation set), not an AI-powered diagnostic or predictive tool. Therefore, the questions related to AI studies, ground truth establishment for training/test sets, number of experts, adjudication methods, or MRMC studies are not applicable to the information provided.

I can, however, extract the relevant performance information from the clinical study summary provided, although it's not structured around explicit "acceptance criteria" for a new device submission, but rather a comparison to a predicate device.

Here's a breakdown of what can be extracted from the text in relation to your request, with an emphasis that the AI-centric questions are not relevant here:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state "acceptance criteria" in the context of a new device approval challenge. Instead, it presents the results of a comparative clinical study against a predicate device to demonstrate substantial equivalence and performance. The "performance" is based on the success rate of treating epiphora.

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

• Test Set Sample Size: 21 patients (treated with SRS)
• Data Provenance: The study was published in "Clinical Ophthalmology 2012:6, 5-8" by Tabatabaie et al. This suggests a prospective clinical study. The authors' affiliations are not provided in this specific extracted text, so the country of origin is not explicitly stated. Often, authors from countries in the Middle East have names like "Tabatabaie," "Rajabi," "Estraghi," which might indicate a study from that region, but this is an inference based on names, not explicit information.

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)

This question is not applicable. The device is a surgical implant. "Ground truth" in this context would typically refer to clinical outcomes (successful alleviation of epiphora, absence of obstruction, etc.) observed by treating physicians or assessed by follow-up examinations, not expert consensus on an image or data interpretation. The study was a comparative clinical trial, so the "truth" was the observed clinical outcome in patients.

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 are typically used in studies involving subjective interpretation of data (e.g., radiology reads) to establish consensus ground truth. This was a clinical trial observing patient outcomes. The "success" was likely defined by objective clinical criteria and physician assessment.

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

This question is not applicable. This is a physical medical device, not an AI system being evaluated to improve human reader performance.

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

This question is not applicable. This is a physical medical device, not an algorithm.

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

The "ground truth" for the clinical study was outcomes data (successful outcome, device failures, adverse events). Success was defined as "successful outcome" which is typically based on clinical assessment and symptom resolution (e.g., resolution of epiphora).

8. The sample size for the training set

This question is not applicable. This is a physical medical device, not an AI algorithm requiring a "training set."

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

This question is not applicable. This is a physical medical device, not an AI algorithm.

Ask a specific question about this device

The Crawford Bicanaliculus Intubation stents are intended for use for nasolacrimal intubation in patients 12 months of age and older. Indications for nasolacrimal intubation performed with the Crawford Bicanaliculus Intubation are:

• . Canalicular pathologies (e.g., congenital or acquired stenosis, lacerations)
• During dacryocystorhinostomy .
• Congenital lacrimal duct obstruction .

The Crawford Bicanaliculus Intubation is a bicanalicular intubation device that consists of a silicone tube that is attached at each end to a flexible metallic Crawford probe. The Crawford Bicanaliculus Intubation comes in a single length of 310 mm and is provided as a sterilized product.

The provided text describes a 510(k) Summary for the Crawford Bicanaliculus Intubation device. This document focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a clinical study or AI-related metrics.

Therefore, many of the requested categories (e.g., acceptance criteria, reported performance, sample size for test set, ground truth methods, MRMC studies, standalone performance, training set details) are not applicable or not provided in this type of regulatory submission.

Here's a breakdown based on the information available:

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

2. Sample size used for the test set and the data provenance:

• Not applicable/Not provided. This submission relies on "substantial equivalence" to legally marketed predicate devices, not on a clinical test set with human subjects or data provenance in the way an AI/diagnostic device would. The "tests" mentioned are non-clinical (tensile strength, biocompatibility, sterilization validation).

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):

• Not applicable/Not provided. No clinical test set with ground truth established by experts is described.

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

• Not applicable/Not provided. No clinical test set requiring adjudication is described.

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:

• Not applicable/Not provided. This is a physical medical device (stent/probe), not an AI diagnostic tool. No MRMC studies were conducted or described.

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

• Not applicable/Not provided. This is a physical medical device, not an algorithm.

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

• For the non-clinical tests, the "ground truth" was established by engineering specifications and applicable standards for material properties (tensile strength, biocompatibility) and process validation (sterilization, package integrity). There is no "expert consensus," "pathology," or "outcomes data" in the clinical sense for these tests. The ultimate "ground truth" for regulatory approval is the demonstration of substantial equivalence to already approved predicate devices.

8. The sample size for the training set:

• Not applicable/Not provided. This is a physical medical device. The concept of a "training set" is not relevant here.

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

• Not applicable/Not provided. As above, no training set or corresponding ground truth is relevant for this device.

Ask a specific question about this device

The MASTERKA® is a silicone intubation device indicated for use in the treatment of congenital lacrimal duct obstructions (stenosis of the valve of Hasner) in patients 12 months and older.

The MASTERKA® is a monocanalicular intubation device with self-retaining punctal fixation for the treatment of stenoses that require intubation. The device consists of a silicone tube molded to a fixation head and pre-mounted on an introducer facilitates insertion of the MASTERKA and is completely removed once the intubation of the lacrimal passages has been completed. The MASTERKA® comes in three different lengths (30, 35, or 40 mm depending on the model) and is provided as a sterilized product.

The MASTERKA® Stent, a monocanalicular lacrimal stent, demonstrated its clinical safety and effectiveness through a literature-based study to support its 510(k) clearance by the FDA. The study referenced was a published series by Fayet et al. (2011) that included 68 pediatric cases of congenital lacrimal duct obstructions.

Here's a breakdown of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: 68 cases of congenital lacrimal duct obstructions in patients 12 months and older.
• Data Provenance: The study was a retrospective analysis of clinical data published in the Journal Français d'Ophtalmologie (2011) by Fayet et al. The country of origin of the data is not explicitly stated in the provided text, but the journal name suggests French origin.

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

The document does not explicitly state the number of experts used to establish ground truth or their specific qualifications for this retrospective study. It references a published clinical study by Fayet et al., implying that the clinical outcomes were assessed by ophthalmologists/surgeons involved in the cases. The reference lists four authors: Fayet B, Racy E, Ruban J-M, Katowitz J, who likely served as the experts assessing the outcomes.

4. Adjudication Method for the Test Set

The document does not describe a specific adjudication method (e.g., 2+1, 3+1). As a retrospective published study, the clinical outcomes would have been determined by the treating physicians and reported in the publication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study was a single-arm series evaluating the performance of the MASTERKA® device, with a comparison to predicate devices being made qualitatively based on similar complication types and rates in literature.

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

This question is not applicable to the MASTERKA® Stent. This is a medical device (stent), not an AI algorithm. Therefore, no standalone algorithm performance was assessed.

7. The Type of Ground Truth Used

The ground truth was based on clinical outcomes data, specifically defined as "absence of epiphora and mucous discharge" for success, and reported complications like "early tube loss" and "keratitis." These outcomes were observed and documented by clinicians in the course of patient care.

8. The Sample Size for the Training Set

This is not applicable as the clinical evaluation was based on a published study assessing the device's performance, not training a machine learning model.

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

This is not applicable as the clinical evaluation was based on a published study assessing the device's performance, not training a machine learning model.

Ask a specific question about this device