Search Results

An ossicular replacement prosthesis is a device intended to be implanted for the functional reconstruction of segments of the ossicular chain and facilitates the conduction of sound wave from the tympanic membrane to the inner ear. Ossicular replacement prostheses are indicated for the functional restoration of the ossicular chain when a conductive hearing loss is present. Indications for use include:
(a) Chronic middle ear disease,
(b) Otosclerosis.
(c) Congenital fixation of the stapes,
(d) Secondary surgical intervention to correct for a significant and persistent conductive hearing loss from prior otologic surgery, and
(e) Surgically correctible injury to the middle ear from trauma.

The family of K-Helix Partial Ossicular Replacement Prostheses consists of:

• K-Helix Piston
• K-Helix PORP
  The Grace Medical Partial Ossicular Replacement Prostheses are manufactured from the same materials as the predicate devices:
  (i) Nitinol (ASTM F2063-05)
  (ii) Unalloyed titanium (ASTM F67)
  (iii) Titanium alloy (ASTM F136)

This 510(k) summary describes a medical device, not an AI/ML powered device. As such, the typical acceptance criteria and study designs applicable to AI/ML devices (e.g., performance metrics, sample sizes for test/training sets, expert adjudication, MRMC studies) are not relevant here.

The K-Helix Partial Ossicular Replacement Prostheses (K-Helix Piston and K-Helix PORP) gained clearance through a substantial equivalence pathway, meaning the manufacturer demonstrated that the new device is as safe and effective as a legally marketed predicate device.

Here's the information derived from the provided text, framed within the context of a traditional medical device submission:

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device, "acceptance criteria" and "reported device performance" are based on demonstrating substantial equivalence to predicate devices, rather than statistical performance metrics as seen with AI.

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

This submission does not discuss a "test set" or clinical data in the way an AI/ML device would. The equivalence is based on design, materials, intended use, and manufacturing processes compared to existing predicate devices. There is no mention of a clinical study with a specific sample size for demonstrating performance.

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. Ground truth, in the AI/ML sense, is not established for this type of device submission. The FDA's review relies on comparing the device's technical specifications and intended use against predicate devices.

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

Not applicable.

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. This is not an AI-assisted device.

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

Not applicable. This is a physical medical implant.

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

Not applicable in the AI/ML context. The "ground truth" for this submission is established by the safety and effectiveness profile of the predicate devices and the demonstration that the new device shares fundamental scientific technology and intended use.

8. The sample size for the training set

Not applicable. There is no AI/ML algorithm requiring a training set.

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

Not applicable. There is no AI/ML algorithm requiring a training set.

Ask a specific question about this device