Effectiveness of biofeedback on blood pressure in patients with hypertension: systematic review and meta-analysis.
Sian JenkinsAinslea CrossHanad OsmanFarah SalimDan LaneDennis BerniehKamlesh KhuntiPankaj GuptaPublished in: Journal of human hypertension (2024)
Hypertension is the leading modifiable risk factor for cardiovascular disease, but less than 50% have their blood pressure controlled. A possible avenue to support hypertension management is a holistic approach, using non-pharmacological interventions. Since hypertension is mediated in part by dysregulation of the autonomic nervous system (ANS), biofeedback may help improve hypertension management by targeted self-regulation and self-awareness of parameters that regulate the ANS. This systematic review aimed to assess the effectiveness of biofeedback on blood pressure in hypertensive patients. The review was pre-registered on PROSPERO and followed the PICO strategy. A total of 1782 articles were retrieved, 20 met the inclusion criteria. Sample sizes ranged from 15 to 301 participants; with a median age of 49.3 (43.3-55.0) years and 45% were female. There was a significant effect of biofeedback on systolic (-4.52, Z = 2.31, P = 0.02, CI [-8.35, -0.69]) and diastolic blood pressure (-5.19, Z = 3.54, P = 0.0004, CI [-8.07, -2.32]). Six different biofeedback modalities were used, with biofeedback delivered by psychologists, trained therapists and research assistants. There was no publication bias, heterogeneity was rated as substantial and data quality was rated to be poor. This review demonstrated that biofeedback had a significant effect on blood pressure. However, this should be viewed in the context of included studies being limited by heterogeneity and dated literature, meaning the research does not reflect the current biofeedback technology such as wearable devices. Future research should incorporate these technologies with robust methodology to fully understand the effect of biofeedback on hypertension.
Keyphrases
- blood pressure
- hypertensive patients
- heart rate
- systematic review
- cardiovascular disease
- heart rate variability
- randomized controlled trial
- blood glucose
- single cell
- type diabetes
- heart failure
- metabolic syndrome
- meta analyses
- drug delivery
- left ventricular
- electronic health record
- artificial intelligence
- body composition
- quality improvement
- coronary artery disease
- adipose tissue
- cancer therapy
- deep learning
- insulin resistance
- glycemic control
- resistance training