What is the clinical evidence from this study?

Study design: RCT. Population: Hypertension (n=48). Intervention: Cuffless wrist blood pressure devices (PPG and AT) vs. 24-hour ambulatory BP monitoring (ABPM). Primary outcome: mean differences in average daytime (7am-11pm) systolic BP (SBP) between each wrist BP device and ABPM (PPG mean bias -3.51 mmHg; AT mean bias -10.98 mmHg).

What question did this study set out to answer?

This study aims to create equations that convert estimates from cuffless wrist blood pressure devices to corresponding cuffed ambulatory blood pressure values.

June 3, 2026

Translating Ambulatory Cuffless Wrist Blood Pressure Estimates to Cuffed Blood Pressure Equivalents for Clinical Decision-Making: The Continuum Bp Study

Key Result

Cuffless wrist blood pressure devices (PPG and AT) exhibited mean biases of -3.51 mmHg and -10.98 mmHg respectively compared to 24-hour ABPM for daytime systolic blood pressure.

Key Points

This study aims to create equations that convert estimates from cuffless wrist blood pressure devices to corresponding cuffed ambulatory blood pressure values.
Randomized crossover trial with 48 participants using two cuffless wrist BP devices and concurrent 24-hour ABPM.
Mean differences in average daytime systolic BP were analyzed using device-specific linear regression models.
Selected covariates included demographic, clinical, and lifestyle variables.
The PPG device had a mean bias of -3.51 mmHg with 41.8% variance explained in cuffed SBP; RMSE was 11 mmHg.
The AT device showed a mean bias of -10.98 mmHg with 37.6% variance explained; a combined model improved variance to 71.7% with RMSE 8 mmHg.
Formulae can enable accurate translations of cuffless BP readings for clinical use.

Study Design

Type

RCT (n=48)

Randomization

random order

Structured PICO

Do device-specific prediction equations accurately translate cuffless wrist BP estimates into cuffed ABPM equivalents in adult participants?

Population

48 participants (34 with sufficient data, mean age 52 years, 50% female, 29% hypertensive) who wore two cuffless wrist BP devices and concurrent 24-hour ABPM.

Intervention

Cuffless wrist blood pressure devices (photoplethysmography [Aktiia/Hilo] and applanation tonometry [Healthstats BPro Evo]) worn in random order.

Comparator

Concurrent 24-hour ambulatory blood pressure monitoring (ABPM).

Outcome

Mean differences in average daytime (7am-11pm) systolic BP between each wrist BP device and ABPM, and variance explained by prediction models.surrogate

Device-specific prediction equations incorporating individual characteristics can translate cuffless wrist BP estimates into cuffed ABPM equivalents, potentially supporting their clinical use pending external validation.

Main Result

Effect estimate: PPG mean bias -3.51 mmHg; AT mean bias -10.98 mmHg

Limitations

External validation is required to establish generalisability and clinical utility.

Abstract

Objective: Current hypertension guidelines do not recommend cuffless wrist blood pressure (BP) devices for clinical use. Yet their prevalent use continues to rise. Clinicians are therefore confronted with cuffless BP data without a valid evidence-based framework for interpretation and decision making. In the Continuum BP study, we aimed to develop equations to translate BP estimates from two wrist BP devices employing distinct cuffless technologies—photoplethysmography (PPG; Aktiia/Hilo) and applanation tonometry (AT; Healthstats BPro Evo)—into corresponding 24-hour ambulatory BP monitoring (ABPM) values to support clinical use.Design and method: In a randomized crossover trial, 48 participants wore each wrist BP device in random order with concurrent 24-hour ABPM within a two-week interval, to complete two non-overlapping periods of BP recordings per participant. We quantified mean differences in average daytime (7am-11pm) systolic BP (SBP) between each wrist BP device and ABPM. Device-specific linear regression models predicted average daytime cuffed ambulatory SBP using cuffless SBP and covariates, selected via backward elimination from demographic, clinical, and lifestyle variables. Results: Sufficient data (14 or more daytime readings from all devices) was available from 34 participants (mean age 52 years; 50% female; 35% non-White; 29% hypertensive). The PPG device exhibited mean bias of -3.51 mmHg (SD 12.57). Device estimated average daytime cuffless SBP alone explained 41.8% of the variance in average daytime cuffed SBP (Table 1). A prediction model additionally incorporating Black ethnicity, body mass index, oscillometric SBP, and stress score improved explained variance to 52.6% with root mean square error (RMSE) 11 mmHg. The AT device showed mean bias of -10.98 mmHg (SD 12.45). Device estimated average daytime cuffless SBP alone explained 37.6% of the variance in average daytime cuffed SBP (Table 1). A model, additionally including age, body mass index, oscillometric SBP, stress score, and alcohol intake, improved explained variance to 71.7% with RMSE 8 mmHg. Conclusions: Device-specific prediction equations incorporating relevant individual characteristics enable translation of cuffless BP estimates to cuffed ABPM equivalents. Incorporating physical activity data may improve prediction accuracy. External validation is required to establish generalisability and clinical utility.

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