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Natural Cycles is a stand-alone software application, intended for women 18 years and older, to monitor their fertility.
Natural Cycles can be used for preventing a pregnancy (contraception) or planning a pregnancy (conception).

Natural Cycles is an over-the-counter and prescription web and mobile-based standalone software application that monitors a woman's menstrual cycle using information entered by the user and informs the user about her past, current and future fertility status. The following information is used by the Natural Cycles software: daily temperature measurements, information about the user's menstruation cycle (i.e., start date, number of days), and optional ovulation or pregnancy test results. A proprietary algorithm evaluates the data and returns the user's fertility status. Users can choose to use Natural Cycles in various modes based on their goals.

Natural Cycles is available in three modes: Contraception (NC° Birth Control), Conception (NC° Plan Pregnancy), and Pregnancy (NC° Follow Pregnancy). For NC° Birth Control mode, the device provides predictions of "not fertile," shown as green days, and "use protection," shown as red days, that allow the user to determine the days on which her risk of conception is highest, and then make contraception to prevent pregnancy.

Inputs to the device include user-inputted daily basal body temperature measured with an oral thermometer with two decimal points or a compatible wearable device (e.g., Oura Ring and Apple Watch).

Natural Cycles can be used by women 18 years and older. Women who have been on hormonal birth control within 60 days prior to using Natural Cycles have a higher risk of becoming pregnant when compared to women who have not been on hormonal birth control within the 12 months prior to using the device. This device may not be right for women who have a medical condition where pregnancy would be associated with a significant risk to the mother or the fetus

The provided document is a 510(k) summary for the Natural Cycles device (K250561), which is a software application for contraception.

Based on the provided document, no study was conducted to prove the device meets acceptance criteria. The document explicitly states:

"There have been no changes to the technology of the device, and no new risks or increased likelihood or magnitude of identified risks have been introduced due to the change from over-the-counter to prescription and over-thecounter use. Therefore, no performance data is needed to validate this change."

This indicates that the submission relies on the substantial equivalence to a predicate device (K231274 Natural Cycles) which presumably demonstrated performance in its original submission. The current submission, K250551, is simply adding "Prescription Use" in addition to the existing "Over-The-Counter Use" without any technological changes to the device itself.

Therefore, most of the requested information regarding acceptance criteria and a study to prove the device meets them cannot be extracted from this document, as no such study was performed or needed for this specific 510(k) submission.

However, I can provide what is stated or implied regarding the device's characteristics and the rationale for the lack of new performance data.

Detailed Breakdown based on the provided document:

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

• Acceptance Criteria: Not explicitly stated as this submission is based on substantial equivalence and no new performance data was generated. The "acceptance criteria" for this submission are that the device remains "as safe and effective" as the predicate device despite the change in use classification.
• Reported Device Performance: No new performance data is reported for K250561. The document asserts that "The technology of the Natural Cycles Application is identical to the predicate device." Therefore, the performance is assumed to be equivalent to the predicate device (K231274).

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

• Not Applicable. No new test set data or studies were performed for this 510(k) submission (K250561).

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. No new test set and thus no experts were used for ground truth establishment for this specific submission.

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

• Not Applicable. No new test set and thus no adjudication method for ground truth establishment for this specific submission.

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. Natural Cycles is described as a "stand-alone software application" with a "proprietary algorithm" for fertility status. It is not an AI-assisted diagnostic tool that human "readers" would use to improve their performance. No MRMC study was conducted or is relevant to this device's function.

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

• Not Applicable. While Natural Cycles is described as a "stand-alone software application," this submission (K250561) does not report a new standalone performance study. It relies on the prior performance of the identical predicate device (K231274). The device's function inherently involves "human-in-the-loop" as users input data (temperature, menstruation info) and then interpret the device's output (red/green days) for contraception or conception planning. The algorithm's "standalone" performance would pertain to its accuracy in interpreting the input data to determine fertility status, which would have been established in the predicate device's submission.

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

• Not Applicable to this submission. The basis for fertility status determination (ground truth) for the predicate device's performance (upon which this submission relies) is not detailed here. For fertility tracking apps, this typically involves comparing the algorithm's predictions against biological indicators of ovulation (e.g., ultrasound, hormone levels) over multiple cycles, or analyzing real-world pregnancy rates for contraception claims.

8. The sample size for the training set

• Not Applicable to this submission. The document explicitly states "No changes have been made to the device technology," meaning no new training or re-training of the algorithm occurred for this submission (K250561). The training set data for the predicate device's algorithm is not disclosed in this document.

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

• Not Applicable to this submission. As noted above, no new training occurred. The method for establishing ground truth for the training set used for the predicate device's algorithm is not detailed in this document.

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