Novel Technique for Confirmation of the Day of Ovulation and Prediction of Ovulation in Subsequent Cycles Using a Skin-Worn Sensor in a Population With Ovulatory Dysfunction: A Side-by-Side Comparison With Existing Basal Body Temperature Algorithm and Vaginal Core Body Temperature Algorithm.

Hurst B S,Pirrie A,Milnes R C,Knowles T G,Davies K

doi:10.3389/fbioe.2022.807139

Abstract

Objective: Determine the accuracy of a novel technique for confirmation of the day of ovulation and prediction of ovulation in subsequent cycles for the purpose of conception using a skin-worn sensor in a population with ovulatory dysfunction. Methods: A total of 80 participants recorded consecutive overnight temperatures using a skin-worn sensor at the same time as a commercially available vaginal sensor for a total of 205 reproductive cycles. The vaginal sensor and its associated algorithm were used to determine the day of ovulation, and the ovulation results obtained using the skin-worn sensor and its associated algorithm were assessed for comparative accuracy alongside a number of other statistical techniques, with a further assessment of the same skin-derived data by means of the “three over six” rule. A number of parameters were used to divide the data into separate comparative groups, and further secondary statistical analyses were performed. Results: The skin-worn sensor and its associated algorithm (together labeled “SWS”) were 66% accurate for determining the day of ovulation (±1 day) or the absence of ovulation and 90% accurate for determining the fertile window (ovulation day ±3 days) in the total study population in comparison to the results obtained from the vaginal sensor and its associated algorithm (together labeled “VS”). Conclusion: SWS is a useful tool for confirming the fertile window and absence of ovulation (anovulation) in a population with ovulatory dysfunction, both known and determined by means of the timing of ovulation. The body site where the skin-worn sensor was worn (arm or wrist) did not appear to affect the accuracy. Prior diagnosis of known causes of ovulatory dysfunction appeared to affect the accuracy to a lesser extent than those cycles grouped into late ovulation and “early and normal ovulation” groups. SWS is a potentially useful tool for predicting ovulation in subsequent cycles, with greater accuracy obtained for the “normal ovulation” group.

Highlights

1.1 Clinical and Scientific BackgroundThere are three main goals in the determination of ovulation for the purposes of improving the chances of conception: 1) to confirm the presence or absence of ovulation in a reproductive cycle, 2) to confirm the day on which ovulation occurred, and 3) to use this ovulation day in one reproductive cycle to predict the date of ovulation and the “fertile window” for the subsequent cycle in order to improve the chances of natural conception or timing of intervention
Results other than true positives (TPs) were classified as follows: false positives (FPs) = a positive (+ve) result outside of these windows; or SWS and/or the same overnight representative data (TOS) +ve, VS negative (−ve) true negatives (TNs) = concordance between TOS and/or SWS and VS that no ovulation took place false negatives (FNs) = SWS and/or TOS −ve, VS +ve The following formulae were used for calculations: Sensitivity = TP/(TP + TN) Specificity = TN/(FP + TN) positive predictive value (PPV) = TP/(TP + FN) negative predictive value (NPV) = TN/(TN + FN) These calculations can be interpreted as follows
The PPV results show the percentage of detected ovulations TOS or SWS get right compared with VS within the ±1 day and ±3 days thresholds

Summary

Introduction

1.1 Clinical and Scientific BackgroundThere are three main goals in the determination of ovulation for the purposes of improving the chances of conception: 1) to confirm the presence or absence of ovulation (anovulation) in a reproductive cycle, 2) to confirm the day on which ovulation occurred, and 3) to use this ovulation day in one reproductive cycle to predict the date of ovulation and the “fertile window” for the subsequent cycle in order to improve the chances of natural conception or timing of intervention. Clinical publications have generally dismissed the use of other temperature curve characteristics such as the “nadir” (the lowest point of the curve) or “dip” prior to the rise for confirmation or prediction of ovulation (McCarthy and Rockette, 1983; Barron and Fehring, 2005). These are important considerations when assessing algorithmic techniques, which might assist us in better understanding both when a temperature rise has occurred and more importantly when the temperature rise is occurring as a cycle progresses. The difficulty in the use of the ovulation day for predicting ovulation and the fertile window for a subsequent cycle—goal 3)—is compounded by the irregularity of their ovulation timing and or cycles, which makes it considerably less likely that ovulation will re-occur on the same day in a subsequent cycle even if it could be established accurately in the first place (Ayres-de-Campos et al, 1995)

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