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The EVA NEXUS™ Ophthalmic Surgical System is indicated for both anterior segment (i.e. phacoemulsification and removal of cataracts) and posterior segment (i.e., vitreoretinal) ophthalmic subretinal microinjection of gases or aqueous fluids.

In addition, the optional laser is indicated for the following:

The EVA NEXUS™ Ophthalmic Surgical System (EVA NEXUS) is a combined anterior and posterior procedure ophthalmic system that is modular in design and is identical in most respects to the recently cleared predicate EVA Ophthalmic Surgical System (K190875). EVA NEXUS (see Figures 1, and 2 for external views) is designed for use in anterior and posterior procedures that require infusion, vitreous cutting, aspiration, illumination, irrigation, lens emulsification and fragmentation, cautery, diathermy as well as photocoagulation.

This document describes the EVA NEXUS™ Ophthalmic Surgical System, a combined anterior and posterior procedure ophthalmic system. The submission (K213467) seeks to demonstrate substantial equivalence to its predicate device, the EVA Ophthalmic Surgical System (K190875), and other components cleared under different K numbers.

The device includes several modifications and new components compared to its predicate, such as a redesigned infusion pole, a second infusion/irrigation port, "Smart IOP" functionality, microinjection capability, a digitally controlled phaco board, increased cutter speed, and a video overlay device.

Here's an analysis of the acceptance criteria and supporting studies based on the provided text:

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

The document does not explicitly present a table of "acceptance criteria" in the typical sense of quantitative thresholds for efficacy or safety endpoints. Instead, it relies on demonstrating substantial equivalence to predicate devices through a combination of bench testing, compliance with international standards, and verification/validation testing. The performance aspects are primarily evaluated by comparison to the predicate device and relevant standards.

However, based on the "Comparison of Technological Characteristics with the Predicate Devices" (Table 5 and subsequent detailed comparisons for individual components like vitrectomy probes, tubing, and laser probes) and "Performance (Bench) Testing" sections, we can infer some performance requirements and reported outcomes:

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

The document primarily describes bench testing and compliance with international standards, rather than clinical studies with human participants. Therefore, concepts like "test set sample size" and "data provenance" (country of origin, retrospective/prospective) are not directly applicable in the way they would be for a clinical trial or AI model validation with patient data.

• Sample Size for Bench Tests: Specific sample sizes for individual bench tests (e.g., number of vitrectomy probes tested for durability, units for electrical safety) are generally not explicitly stated in this high-level summary but would be detailed in the individual RPRT reports (e.g., RPRT 30612000 for vitrectomes). For example, vitrectome durability tests refer to "≥ 150,000 cutting cycles," indicating a performance threshold rather than a sample size of devices.
• Data Provenance: All testing appears to be laboratory/bench data, performed by the manufacturer, D.O.R.C. Dutch Ophthalmic Research Center (International) B.V., located in the Netherlands.

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 product is a surgical system, not a diagnostic AI device that requires expert-annotated ground truth from medical images or similar data. The "ground truth" for its performance is established through adherence to engineering specifications, international medical device standards (e.g., IEC, ISO), and performance equivalence to a legally marketed predicate device.

Therefore, the concept of "experts establishing ground truth for a test set" with specific qualifications (like radiologists) is not applicable here. The "experts" involved would be the engineers, quality control personnel, and regulatory affairs specialists who designed the tests, interpreted the results, and compiled the submission, ensuring compliance with established norms and standards.

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

Not applicable. As noted above, this is not a diagnostic device requiring human adjudication of results from a test set. The evaluation is based on objective measurements against engineering specifications and international standards.

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 diagnostic or interpretation device that would involve human readers or MRMC studies. The device is a surgical system.

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

Not applicable. The EVA NEXUS is a surgical system operated by a human surgeon ("human-in-the-loop" by definition for a surgical tool). It does not function as a standalone algorithm for diagnosis or decision-making.

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

The "ground truth" for the EVA NEXUS Ophthalmic Surgical System is:

• Compliance with established international medical device standards (e.g., IEC 60601 series, ISO 10993 series, ISO 15004-2).
• Engineering specifications and performance metrics derived from device design and functionality.
• Substantial equivalence to legally marketed predicate devices, implying that the predicate's established safety and effectiveness forms the basis for the new device's acceptable performance.
• Successful completion of verification and validation testing against these standards and specifications.

8. The sample size for the training set

Not applicable. The EVA NEXUS is a hardware-based surgical system with embedded software for control; it is not an AI/ML model that undergoes "training" on a "training set" of data in the conventional sense. The software verification and validation activities are for ensuring its functional requirements and safety, not for machine learning model training.

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

Not applicable, as there is no "training set" or "ground truth" for such a set in the context of this device.

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