Abstract 4365286: Association of Sleep Temperature Patterns with Resting Heart Rate in Regular and Irregular Menstrual Cycles using Wearables: a real-world cross-sectional study

Background: Temperature, heart rate (HR) and heart rate variability (HRV) are known to be hormonally influenced and fluctuate across the menstrual cycle. However, the association of sleep resting heart rate (RHR) and the nuanced thermal patterns indicative of changing progesterone levels relative to cycle type and age remains less studied. Hypothesis: We hypothesize that RHR segregates in discrete patterns in different cycle types for menstrual cycles that can be mapped by nocturnal thermal patterns. Methods: In this study, we used specific thermally-derived patterns or “Cycle Flags (CF)” and examined how these associate with sleep RHR in regular and irregular menstrual cycles. We examined 1492 de-identified, randomly-selected cycles of Ultrahuman Ring AIR users (N=1263, ages 20-50 years) between September 2024 and March 2025. Data aggregation was carried out in accordance with Ultrahuman’s privacy policy. Nocturnal skin temperatures were processed through the OvuSense algorithm to generate CFs. The mode of night RHR per cycle was categorized into typical (<60 bpm), elevated (60-75 bpm), and high RHR (>75 bpm). Odds ratios (OR) with 95% confidence intervals were computed for associations between cycle flags and RHR. Results: In pooled cycles, Anovulation (non-ovulatory cycle) CF was consistently associated with higher RHR. False Start (early progesterone spike without ovulation) demonstrated an inverse association with elevated RHR (OR=0.13, p<0.05). In regular-cycling younger women (20-30 y), Slow Rise (weak progesterone response) was significantly linked to elevated RHR (OR=4.97, p<0.05), while those with irregular cycles displayed a connection with typical RHR levels (OR=9.00, p<0.05). In the 30-40 y group, Fall After Ovulation (possible luteal phase insufficiency) in regular cycles (OR=2.89, p<0.05) and Anovulation in irregular cycles (OR=6.31, p<0.05) were both associated with higher RHR. In older women (40-50 y), Fall After Ovulation in regular cycles displayed a near-significant association with elevated RHR (OR=3.53, p=0.051). Conclusions: Combinatorial signatures of elevated RHR and temperature patterns have the potential to identify cycle types with fluctuating hormone levels. Age-wise analyses indicated that CFs are the most pronounced in women aged 20-40 years. Hence, longitudinal tracking via continuous-use wearables provides valuable support for cardiovascular and reproductive health awareness in real-world settings.