Relationships Between Blood Pressure Reduction, Weight Loss, and Engagement in a Digital App-Based Hypertension Care Program: Observational Study.

Autor:	Branch OH; Lark Technologies, Inc, Mountain View, CA, United States., Rikhy M; Lark Technologies, Inc, Mountain View, CA, United States., Auster-Gussman LA; Lark Technologies, Inc, Mountain View, CA, United States., Lockwood KG; Lark Technologies, Inc, Mountain View, CA, United States., Graham SA; Lark Technologies, Inc, Mountain View, CA, United States.
Jazyk:	angličtina
Zdroj:	JMIR formative research [JMIR Form Res] 2022 Oct 27; Vol. 6 (10), pp. e38215. Date of Electronic Publication: 2022 Oct 27.
DOI:	10.2196/38215
Abstrakt:	Background: Home blood pressure (BP) monitoring is recommended for people with hypertension; however, meta-analyses have demonstrated that BP improvements are related to additional coaching support in combination with self-monitoring, with little or no effect of self-monitoring alone. High-contact coaching requires substantial resources and may be difficult to deliver via human coaching models. Objective: This observational study assessed changes in BP and body weight following participation in a fully digital program called Lark Hypertension Care with coaching powered by artificial intelligence (AI). Methods: Participants (N=864) had a baseline systolic BP (SBP) ≥120 mm Hg, provided their baseline body weight, and had reached at least their third month in the program. The primary outcome was the change in SBP at 3 and 6 months, with secondary outcomes of change in body weight and associations of changes in SBP and body weight with participant demographics, characteristics, and program engagement. Results: By month 3, there was a significant drop of -5.4 mm Hg (95% CI -6.5 to -4.3; P<.001) in mean SBP from baseline. BP did not change significantly (ie, the SBP drop maintained) from 3 to 6 months for participants who provided readings at both time points (P=.49). Half of the participants achieved a clinically meaningful drop of ≥5 mm Hg by month 3 (178/349, 51.0%) and month 6 (98/199, 49.2%). The magnitude of the drop depended on starting SBP. Participants classified as hypertension stage 2 had the largest mean drop in SBP of -12.4 mm Hg (SE 1.2 mm Hg) by month 3 and -13.0 mm Hg (SE 1.6 mm Hg) by month 6; participants classified as hypertension stage 1 lowered by -5.2 mm Hg (SE 0.8) mm Hg by month 3 and -7.3 mm Hg (SE 1.3 mm Hg) by month 6; participants classified as elevated lowered by -1.1 mm Hg (SE 0.7 mm Hg) by month 3 but did not drop by month 6. Starting SBP (β=.11; P<.001), percent weight change (β=-.36; P=.02), and initial BMI (β=-.56; P<.001) were significantly associated with the likelihood of lowering SBP ≥5 mm Hg by month 3. Percent weight change acted as a mediator of the relationship between program engagement and drop in SBP. The bootstrapped unstandardized indirect effect was -0.0024 (95% CI -0.0052 to 0; P=.002). Conclusions: A hypertension care program with coaching powered by AI was associated with a clinically meaningful reduction in SBP following 3 and 6 months of program participation. Percent weight change was significantly associated with the likelihood of achieving a ≥5 mm Hg drop in SBP. An AI-powered solution may offer a scalable approach to helping individuals with hypertension achieve clinically meaningful reductions in their BP and associated risk of cardiovascular disease and other serious adverse outcomes via healthy lifestyle changes such as weight loss. (©OraLee H Branch, Mohit Rikhy, Lisa A Auster-Gussman, Kimberly G Lockwood, Sarah A Graham. Originally published in JMIR Formative Research (https://formative.jmir.org), 27.10.2022.)
Databáze:	MEDLINE
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