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The Visibly Digital Acuity Product (VDAP) is a web-based, self-quided software application intended for use by adults, ages 22 to 40, who have the capability to perform a self-test at home, to aid in the evaluation of visual acuity with or without correction. The software allows users to view and respond to displayed optotypes and uses the responses to categorize a patient's visual acuity into one of two categories, with an individual output for each eye:

• . TRUE - visual acuity that is consistent with normal vision
• FALSE visual acuity that is not consistent with normal vision .
  The Visibly Digital Acuity Product recommendations are intended to be supportive recommendations that will be used by an eye care provider, along with the patient's medical history and profile, prior corrective evewear prescriptions, and subjective vision data. The Visibly Digital Acuity Product does not provide screening or diagnosis of eye health or other disease, nor is it intended to replace an in-person eye exam.

The Visibly Digital Acuity Product is a web-based, software application intended for use by adults, at home, to aid in the evaluation of visual acuity with or without correction. The standalone software application allows the user to interface with the software via a web browser on two internet-enabled devices:

• A computer screen (the Display) which displays optotypes. O
• A touchscreen mobile device (the Remote) which operates as a remote control and o interface for the user to respond to prompts related to the optotypes appearing on the Display while standing 10 feet away.
  The software allows users to view and respond to displayed optotypes and uses the responses to categorize a user's vision acuity into one of two buckets: (1) TRUE - visual acuity that is consistent with normal vision (2) FALSE - visual acuity that is not consistent with normal vision.

Here's a breakdown of the acceptance criteria and the study proving the Visibly Digital Acuity Product (VDAP) meets them, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the primary and secondary endpoints described in the "Performance Data" section. There aren't explicit numeric acceptance criteria stated for all metrics (e.g., sensitivity, specificity), but a performance goal is given for reproducibility.

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The CVA-1000 is intended for use under the direct supervision of an ophthalmologist or optometrist in the measurement of vision at fixation in one or both eyes, with or without optical correction.

The CVA-1000 instrument is a standalone device consisting of a computer processing unit with data storage, two LCD monitors, a physician viewed monitor and a patient viewed monitor, and connected keyboard and mouse for physician interaction with a response pad for patient interaction. The instrument provides an evaluation of vision at fixation of one or both eyes under different conditions of contrast and lighting assisting the ophthalmologist or optometrist in evaluating the effects of prescribed refractive instruments such as spectacles or contact lenses and of pharmaceutical treatment or surgical procedures on the central vision of one or both eyes.

The instrument may be used in either of two methods of operation: Chart Panel or Interactive Central Vision Panel.

Here's a breakdown of the acceptance criteria and the study details for the Vimetrics Central Vision Analyzer 1000 (CVA-1000), based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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The Topcon Model BV-1000 Automated Subjective Refraction System provides sphere, cylinder, and axis measurements of the eye. The BV-1000 assists the eyecare professional in evaluating pre and post operative eye procedures and is used as an aid in prescribing eyeglasses and contact lenses.

The Topcon Model BV-1000 is a safe and effective instrument. In essence, it is a combination of three Class I devices:

1. Ophthalmic Refractometer ... an AC-powered device that consist of a fixation system, a measurement and recording system and an alignment system.
2. Visual Acuity Chart ... a device, with a Landolt "C" chart in graduated sizes to test visual acuity
3. Onthalmic Motorized Refractor ... a device that incorporates a set of lenses of various dioptric powers intended to measure the refractive power of the eyc.
   The BV-1000 is designed to perform binocular, simultaneous auto-refraction. It incorporates subjective refinement steps after the objective measurements have been obtained. The BV-1000 reduces the amount of time that eyecare professionals need to spend in refracting their patients as a substantial portion of the traditional refraction can be accomplished in the "pre test" room.

The provided document is a 510(k) summary for the Topcon Model BV-1000 Automated Subjective Refraction System. Based on the information available, a detailed description of acceptance criteria and the study proving it is not present in the typical format of an AI/ML device study.

This document describes a medical device from 2003, which predates the widespread regulatory framework for AI/ML medical devices. Therefore, the information requested, particularly regarding AI-specific criteria like training sets, ground truth establishment for AI, MRMC studies for AI assistance, and standalone AI performance, will not be found in this document.

However, I can extract information related to the device's performance specifications and how it was compared to predicate devices, which serves as a form of "acceptance criteria" and "study" in the context of a 510(k) submission from that era.

Here's the breakdown of what can be inferred and what is not available based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as pass/fail thresholds against which the device was tested. Instead, it demonstrates substantial equivalence by comparing the BV-1000's performance specifications, particularly its measurement ranges, with those of legally marketed predicate devices. The implicit acceptance criteria are that the device's performance falls within a comparable and safe range to these predicates.

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

• Sample Size: Not explicitly stated. The document focuses on performance specifications and comparison to predicates, not a clinical trial with a specific patient sample size for testing.
• Data Provenance: Not specified. Given it's a 510(k) from 2003, such details were often less rigorously documented in the summary unless critical for equivalence demonstrations (e.g., specific clinical study data if equivalence was not clear from technological comparison). It's likely based on internal testing and engineering assessments rather than a large clinical test set described in this summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• This information is not available and is not relevant for this type of device and submission from this era. "Ground truth" in the context of refractive measurements is often established by established clinical methods (e.g., best-corrected visual acuity determined by an optometrist/ophthalmologist) or comparison to existing gold-standard devices. Experts would be involved in designing and interpreting the performance data, but not typically in the "ground truth" establishment as understood in AI/ML validation studies.

4. Adjudication method for the test set

• Not applicable/Not available. Adjudication methods are typically associated with resolving discrepancies in expert labeling or diagnoses, especially in AI/ML studies. This document doesn't describe a study design that would necessitate such a method.

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

• No, this device is not an AI-assisted device. Therefore, an MRMC study comparing human readers with and without AI assistance was not conducted and is not applicable. The device's purpose is to assist eyecare professionals by providing objective measurements and streamlining subjective refinement, not to provide AI diagnostics or interpretations.

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

• Not applicable. This device is a piece of hardware that takes measurements. It is not an algorithm designed to perform diagnostics "stand-alone." Its output (sphere, cylinder, axis measurements) still requires interpretation and use by an eyecare professional. The "Automated Subjective Refraction System" name implies it automates parts of the subjective refraction process, but the human is still in the loop for the overall prescription.

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

• For a device like this, ground truth would implicitly be established through comparison to established clinical methods and predicate devices. For example, the accuracy of its refractive measurements would be compared against the results obtained by experienced clinicians using traditional phoropters or other auto-refractors considered gold standards at the time. The document doesn't detail the specific ground truth process but relies on the device producing measurements within expected clinical ranges, comparable to predicates.

8. The sample size for the training set

• Not applicable/Not available. This is not an AI/ML device, so there is no "training set" in the sense of data used to train a machine learning model. The device's "training" would be its engineering design, calibration, and validation against physical measurement standards and clinical performance expectations.

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

• Not applicable. As a non-AI/ML device, there is no "training set ground truth" as understood in current AI/ML terminology.

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