K Number
K130375
Date Cleared
2013-12-04

(293 days)

Product Code
Regulation Number
N/A
Panel
OP
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

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
Device Description

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.

AI/ML Overview

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.

MetricAcceptance Criteria (Implicit from Predicate Comparison)Reported Device Performance (Self-Retaining Bicanaliculus Intubation Set II - SRS)
Short-term Success Rate (1 week post-op)Comparable to or better than Crawford Stent (88.2%)95.2% (20/21 patients)
Long-term Success Rate (at last reported visit, 5-8 months post-tube removal)Comparable to or better than Crawford Stent (76.4%)76.2% (12/14 partial; 4/7 complete obstructions)
Device Failures/Adverse EventsNo device failures or adverse events.No device failures or adverse events reported.

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.

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