(59 days)
The OMNI™ Surgical System is a manually operated device for delivery of small amounts of viscoelastic fluid, for example Healon® or Healon GV® from Abbott Medical Optics (AMO), Amvisc® from Bausch & Lomb, or PROVISC® from Alcon, during ophthalmic surgery. It is also indicated to cut trabecular meshwork tissue during trabeculotomy procedures.
The Sight Sciences OMNI™ Surgical System ("OMNI") is a sterile, single use, manually operated instrument used by ophthalmologists to deliver small, controlled amounts of viscoelastic into the anterior segment of the eye during ophthalmic surgery. It is also indicated to cut trabecular meshwork tissue during trabeculotomy procedures. The OMNI is designed to function with commonly used viscoelastic fluids made commercially available by companies such as Abbott Medical Optics (AMO), Bausch & Lomb, and Alcon. The OMNI dispenses fluid on the principle of exchanging volumes much like a syringe. The handheld instrument includes a cannula, microcatheter, internal reservoir and plunger tube, and finger wheels. The finger wheels on the handle of the device are used advance and retract the microcatheter. In addition, when the device is being used to deliver viscoelastic, retraction of the microcatheter causes the plunger tube to advance into the viscoelastic fluid reservoir thereby dispensing viscoelastic fluid.
The provided document is a 510(k) summary for the OMNI Surgical System, a medical device. It describes the device, its intended use, and comparisons to predicate and reference devices. However, it does not contain the detailed clinical study information typically provided for AI/ML-driven devices to demonstrate performance against acceptance criteria.
The document states:
- Performance Data: "The OMNI's descriptive characteristics are well-defined and adequate to ensure equivalence to the predicate devices. Additionally, the following performance testing and inspection was conducted on the OMNI device: dimensional and visual inspections, visual inspection of labeling and component inspections, mechanical testing of joint strength and actuation force, simulated use testing, and human cadaver eye performance testing. Acceptance criteria was based on predicate VISCO360's dispensing performance, intrinsic strength of the materials, and the load and conditions to which the OMNI would be subjected during use. Testing demonstrated that the OMNI performs as intended and is functionally equivalent to the predicate devices."
Based on this, here's what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
Note: The document describes "performance testing" and "acceptance criteria based on predicate VISCO360's dispensing performance, intrinsic strength of the materials, and the load and conditions to which the OMNI would be subjected during use." However, it does not provide specific numerical acceptance criteria or detailed quantitative performance results in the format typically expected for AI/ML device evaluations (e.g., sensitivity, specificity, AUC). Instead, it makes a general statement of functional equivalence.
| Acceptance Criteria (Not explicitly stated numerically, but inferred from text) | Reported Device Performance (Summary Statement) |
|---|---|
| Equivalence to predicate VISCO360's dispensing performance | Functionally equivalent to the predicate devices. |
| Intrinsic strength of materials met | Performed as intended. |
| Withstood load and conditions during simulated use | Performed as intended. |
| Dimensional and visual inspections within specifications | Performed as intended. |
| Labeling and component inspections within specifications | Performed as intended. |
| Mechanical testing of joint strength and actuation force met | Performed as intended. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not specified in the provided text. The phrase "human cadaver eye performance testing" indicates a form of testing but doesn't quantify the sample size.
- Data Provenance: "Human cadaver eye performance testing." This implies the data was collected in a laboratory setting using cadaveric eyes. The country of origin is not specified, but the submission is to the U.S. FDA. Retrospective/prospective is not applicable as this is a device performance test on cadavers, not a clinical data study.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified.
- Self-correction: For this type of mechanical device testing, "ground truth" would likely be established by engineering measurements and observations rather than expert clinical consensus as might be the case for image-based AI/ML devices.
4. Adjudication Method for the Test Set
- Adjudication Method: Not applicable/not specified. The testing described (dimensional, mechanical, simulated use, cadaver eye performance) would involve objective measurements and observations against pre-defined engineering or performance specifications, not a consensus-based adjudication process.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
- MRMC Study: No, an MRMC comparative effectiveness study was not done.
- Effect Size: Not applicable. This device is a manually operated surgical tool, not an AI/ML algorithm intended to assist human readers in interpretation tasks.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study was Done
- Standalone Study: No, this is not an AI/ML algorithm. The device is a physical, manually operated surgical instrument.
7. The Type of Ground Truth Used
- Type of Ground Truth: For the mechanical and simulated use testing, the ground truth would be based on engineering specifications, direct measurements, and observations of physical performance (e.g., dispensing volume accuracy, force required for actuation, structural integrity, cutting efficacy in cadaveric tissue) rather than clinical outcomes, pathology, or expert consensus on diagnostic interpretations.
8. The Sample Size for the Training Set
- Sample Size for Training Set: Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning. The device design and verification would rely on engineering principles, material science, and iterative testing/refinement.
9. How the Ground Truth for the Training Set was Established
- How Ground Truth was Established: Not applicable, as there is no training set in the AI/ML sense. Device design and validation would follow standard medical device development processes.
§ 880.5725 Infusion pump.
(a)
Identification. An infusion pump is a device used in a health care facility to pump fluids into a patient in a controlled manner. The device may use a piston pump, a roller pump, or a peristaltic pump and may be powered electrically or mechanically. The device may also operate using a constant force to propel the fluid through a narrow tube which determines the flow rate. The device may include means to detect a fault condition, such as air in, or blockage of, the infusion line and to activate an alarm.(b)
Classification. Class II (performance standards).