ESC Congress 2026 Abstract · Oct 26, 2026
Sleep parameters derived from smartwatch sphygmomanometer are associated with systolic blood pressure and time in therapeutic range: a large-scale real-world longitudinal study
By Liu Y, lv Z, Wang Y et al.
Background: Sleep disturbance is an established hypertension risk factor. However, prior studies relied on self-reported or single-night polysomnographic data, precluding dynamic long-term evaluation. Conventional ambulatory monitoring cannot concurrently quantify sleep. The smartwatch sphygmomanometer enable simultaneous capture of blood pressure (BP) and multidimensional sleep parameters in real-world. Time in therapeutic range (TTR), a validated index of sustained BP control, remains uncharacterised in relation to sleep. Purpose: To systematically evaluate the associations between five objectively measured sleep parameters and systolic blood pressure (SBP) and TTR (target 110–130 mmHg), using large-scale, real-world, longitudinal data obtained from smartwatch sphygmomanometer. Methods: In total, 2,128 participants (mean age 51.1 ± 11.3 years; 90.0% male) were monitored continuously throughout 2023, contributing 317,782 person-days (median 149 days/person). Five sleep parameters were examined: duration, onset time, deep sleep proportion, dream time, and awakening frequency. Non-linear associations with SBP were modelled via restricted cubic splines (RCS) with random effects, adjusting for age, sex, smoking, alcohol, body mass index (BMI), diabetes mellitus (DM), chronic kidney disease (CKD), et al. TTR was calculated using the percentage and Rosendaal interpolation methods. The associations were assessed via Pearson correlation, multivariable linear regression, and binary logistic regression (TTR ≥70% vs. <70%) across three sequentially adjusted models, with ten-variable subgroup analyses and likelihood ratio interaction testing. A composite sleep quality score was derived using item response theory (IRT) and validated by group-based trajectory modelling (GBTM). Results: RCS revealed a significant U-shaped relationship between sleep duration and SBP (P-overall = 0.001; P-nonlinear = 0.001): SBP was elevated with both short (<5 h) and long (>9.6 h) sleep; the 7–9 h range yielded the lowest SBP. Later sleep onset (11 PM–1 AM) independently increased TTR <70% risk (OR = 1.256, 95% CI 1.011–1.560, P = 0.040). Awakening frequency >3/night was associated with TTR <70% (OR = 1.467, 95% CI 1.064–2.024, P = 0.019). Dream time was shorter in TTR <70% participants (35.6 ± 18.2 vs. 37.6 ± 18.4 min; P = 0.018). IRT-derived sleep scores showed good fit (entropy >0.80), with sleep duration as the strongest discriminator (α=4.455). GBTM identified heterogeneous sleep trajectories supporting BP-targeted stratification. Conclusions: Multidimensional sleep parameters are independently and non-linearly associated with SBP and TTR in a large real-world cohort. IRT-based scoring and GBTM trajectory modelling offer a rigorous, clinically translatable framework for sleep-informed hypertension management, underscoring the transformative potential of wrist-worn devices for precision cardiovascular risk stratification.figure 1figure 2