P-675 Analysis of a digitally integrated ovulation date kit to determine ovulation precisely
Authors: Saramandic M , Martinez-Hurtado J L , Hancke K , Seifert-Klauss V 
Published: June 2023

Study question

Do digitally integrated ovulation prediction kits (OPK) predict the fertile window and the ovulation date accurately? And can this prediction be proven by sonography?

Summary answer

Particularly for subfertile women with irregular cycles, OPKs can help predict their fertile window and ovulation day, in accordance with vaginal sonography.

What is known already

The fertile window is defined as the period of five days before ovulation including the day of ovulation itself. Prediction based only on cohort observations or historical datasets may be inaccurate for women with irregular cycles, particularly when unforeseen changes of ovarian function occur during reproductive life. Urinary luteinizing hormone (LH) assays and smartphone applications are already widely used to detect the optimal time for conception, but can only predict a likelihood of ovulation without proof.

Study design, size, duration

100 healthy women between the ages of 21 and 45, cycle length up to 42 days, trying to conceive and without hormone intake were to be recruited in the gynecological outpatient clinics of the Technical University of Munich (TUM) and of the University of Ulm. Each participant entered the study for up to three consecutive cycles. Two vaginal ultrasound scans were performed per cycle – before and after the ovulation date prognosis by the app.

Participants/materials, setting, methods

After informed consent, participants downloaded the smartphone application “Pearl Fertility” and received OPKs consisting of four different sets of lateral flow immunoassay test strips (LFIA): for luteinizing hormone, follicle-stimulating hormone, progesterone and human chorionic gonadotropin. Home measurements with LFIAs were performed with morning urine. The phone camera feed analyzed the color information of the LFIAs. Three differently prioritized algorithms calculated the ovulation date. Two questionnaires evaluated patient baseline characteristics and their perception of the app.

Main results and the role of chance

89 women were recruited. Mean age was 34.6 yrs. (SD ± 4.2). On average, the included women had tried to conceive for 7.5 (±5) months before joining the study. 8% (n = 7) became pregnant before the first cycle started.140 completed cycles in 71 remaining women were analyzed so far. 46% of the recruited women completed the study after 3 cycles, the drop-out-rate was 32.4%.

The app predicted ovulation for cycle day 14.3 (mean, SD ± 3.5). In 25 cycles the date of ovulation was before day 12 and in 33 cycles on day 16 or later.

The first ultrasound was done on cycle day 13.5 (mean, SD ± 3), the second ultrasound on cycle day 17.6 (mean, SD ± 3.6). In several cycles at least one (up to three) corrections of the prognosis occurred by the app, resulting in the day of predicted ovulation being moved either backward (retrospectively) or forward by 2.5 (mean, SD ± 1.9) days. Urinary progesterone measured with the OPK and post-ovulatory ultrasound were in accordance in the majority of cycles.

17% (n = 12) of the women became pregnant in the current analysis (mean duration to pregnancy: 1.3 cycles). In the ITT population (after informed consent) the rate was 23%.

Limitations, reasons for caution

This study was performed without a control group. Therefore, as an intraindividual control, a follow-up is planned to calculate the pregnancy rates and outcomes with and after the use of the app.

Wider implications of the findings

Our study shows that digitally integrated OPK are able to predict the fertile window and the ovulation date in a slightly subfertile cohort unselected for mild cycle irregularities. An early and accurate prediction may help couples to conceive, particularly if the date of ovulation is divergent from standard information.

Trial registration number

Not applicable