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Indication for Use: To be used by medical professionals to expose the interior of the vagina to facilitate visualization during gynecological and obstetrical procedures.

The Vag O Speculum is a non-metal hand-held device used to expose the interior of the vagina.

1. Acceptance Criteria and Reported Device Performance:

The provided document describes a vaginal speculum, a non-AI/ML device. Therefore, the concept of "acceptance criteria" based on performance metrics like sensitivity, specificity, or AUC, as typically applied to AI/ML diagnostic devices, does not directly apply here. Instead, acceptance for this type of device is usually based on demonstrating substantial equivalence to a legally marketed predicate device.

The "acceptance criteria" implicit in this 510(k) submission are that the Vag O Speculum is substantially equivalent to the predicate device, the Kleenspec (Welch Allyn Vaginal Speculum), in terms of intended use, technological characteristics (being a non-metal, hand-held device to expose the interior of the vagina), and safety and effectiveness.

The reported device performance, in this context, is that the FDA reviewed the submission and determined the device is substantially equivalent to legally marketed predicate devices, allowing it to be marketed.

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

This is not applicable as the submission is for a physical medical device (vaginal speculum), not an AI/ML diagnostic or predictive algorithm that would require a test set of data. The "test" here refers to demonstrating substantial equivalence, likely through design comparisons, material specifications, and potentially some limited performance testing (e.g., strength, fit) which are not detailed in this summary.

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

Not applicable. Ground truth, in the context of expert consensus, is irrelevant for a physical device like a vaginal speculum. Substantial equivalence is assessed by the FDA against existing regulatory standards and predicate devices.

4. Adjudication method for the test set:

Not applicable. There is no "test set" in the AI/ML sense, and thus no adjudication method for it.

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/ML device, so no MRMC study or assessment of human reader improvement with AI assistance would have been performed.

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

Not applicable. This is not an algorithm.

7. The type of ground truth used:

For a physical device like a vaginal speculum, the "ground truth" to determine marketability is primarily based on:

• Predicate device comparison: The device must be demonstrated to be as safe and effective as a legally marketed predicate device.
• Regulatory compliance: Adherence to general controls provisions of the Federal Food, Drug, and Cosmetic Act (e.g., annual registration, listing of devices, good manufacturing practice, labeling, prohibitions against misbranding and adulteration).
• Design and manufacturing specifications: The device's design, materials, and manufacturing processes must ensure safety and functionality for its intended use.

8. The sample size for the training set:

Not applicable. There is no "training set" for a physical device like this.

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

Not applicable. There is no "training set" for a physical device.

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The Quanti-Test System is an allergen delivery system which, through a skin prick test, places antigen into the epidermis to indicate a sensitivity to allergens.

The Quanti-Test System is an allergen delivery system.

The provided documents are FDA 510(k) letters related to the Quanti-Test System, which is described as an "allergen delivery system" for skin prick tests. These documents are dated from 1998 and an administrative update from 2024. They primarily concern the regulatory classification and substantial equivalence determination for the device, not a study describing acceptance criteria and device performance in the context of recent AI-powered medical devices.

Therefore, I cannot provide the requested information regarding acceptance criteria, device performance, study details, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth establishment based on the provided text.

The documents confirm the following about the device:

• Device Name: Quanti-Test System
• Intended Use: An allergen delivery system which, through a skin prick test, places antigen into the epidermis to indicate a sensitivity to allergens.
• Original Product Code (1998): LDH (Unclassified)
• Updated Product Code (2024): SCL (Hypodermic single lumen needle, Class II)

The provided text does not contain any information about:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes or data provenance for a test set.
3. Number or qualifications of experts for ground truth.
4. Adjudication method.
5. MRMC comparative effectiveness study or human reader improvement with AI.
6. Standalone performance of an algorithm.
7. Type of ground truth used (e.g., pathology, outcomes data).
8. Sample size for a training set.
9. How ground truth for a training set was established.

These kinds of details are typically found in the 510(k) summary or detailed submission documents, which are not included in the provided snippets.

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