Key result
Maternal HRV inflection tracks time until birth better than gestational age, offering a potential preterm biomarker.
Why the study?
Preterm birth incidence remains unchanged partly due to limited screening methods, and it was unknown whether wearable-derived maternal heart rate variability inflection reflects gestational age or time to delivery.
Does wearable-derived maternal heart rate variability (mHRV) inflection serve as a digital biomarker for preterm birth in pregnant individuals?
Case-Control (n=241)
Yes
Does wearable-derived maternal heart rate variability (mHRV) inflection serve as a digital biomarker for preterm birth in pregnant individuals?
Effect estimate: relative log-likelihood ratio 859.4
Wearable-derived maternal heart rate variability inflection is more strongly associated with time until birth than gestational age, suggesting its potential as a novel digital biomarker to screen for preterm delivery.
May enable earlier preterm birth risk detection with wearables; hypothesis-generating and should not yet change practice.
Despite considerable health consequences from preterm births, their incidence remains unchanged over recent decades, due partially to limited screening methods and limited use of extant methods. Wearable technology offers a novel, noninvasive, and acceptable way to track vital signs, such as maternal heart rate variability (mHRV). Previous research observed that mHRV declines throughout the first 33 weeks of gestation in term, singleton pregnancies, after which it improves. The aim of this study was to explore whether mHRV inflection is a feature of gestational age or an indication of time to delivery. This retrospective case-control study considered term and preterm deliveries. Remote data collection via non-invasive wearable technology enabled diverse participation with subjects representing 42 US states and 16 countries. Participants (N=241) were recruited from the WHOOP (Whoop, Inc.) userbase and wore WHOOP straps during singleton pregnancies between March 2021 and October 2022. Mixed effect spline models by gestational age and time until birth were fit for within-person mHRV, grouped into preterm and term births. For term pregnancies, gestational age (AIC = 26627.6, R 2 m = 0.0109, R 2 c= 0.8571) and weeks until birth (AIC =26616.3, R 2 m = 0.0112, R 2 c = 0.8576) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio = 279.5). For preterm pregnancies, gestational age (AIC =1861.9, R 2 m = 0.0016, R 2 c = 0.8582) and time until birth (AIC = 1848.0, R 2 m = 0.0100, R 2 c = 0.8676) were representative of mHRV trends, with significantly stronger fit for weeks until birth (relative log-likelihood ratio= 859.4). This study suggests that wearable technology, such as the WHOOP strap, may provide a digital biomarker for preterm delivery by screening for changes in nighttime mHRV throughout pregnancy that could in turn alert to the need for further evaluation and intervention.
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Jasinski et al. (2022) conducted a case-control in Pregnancy (Preterm and Term Births) (n=241). Maternal heart rate variability (mHRV) monitoring vs. Term vs preterm pregnancies was evaluated on Model fit for mHRV trends (time until birth vs gestational age in preterm pregnancies) (relative log-likelihood ratio 859.4). Maternal heart rate variability trends were significantly better explained by time until birth than gestational age, suggesting mHRV inflection is a potential digital biomarker for preterm delivery.
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