scholarly journals Determining which automatic digital blood pressure device performs adequately: a systematic review

2010 ◽  
Vol 24 (7) ◽  
pp. 431-438 ◽  
Author(s):  
Y Wan ◽  
C Heneghan ◽  
R Stevens ◽  
R J McManus ◽  
A Ward ◽  
...  
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Blood Pressure Device

High Blood Pressure Combined with Sedentary Behavior in Young People: A Systematic Review

2017 ◽  
Vol 12 (3) ◽  
pp. 215-221 ◽  
Author(s):  
Loreana Sanches Silveira ◽  
Daniela Sayuri Inoue ◽  
Jose Messias Rodrigues da Silva ◽  
Suziane Ungari Cayres ◽  
Diego Giulliano Destro Christofaro
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Young People ◽  
Sedentary Behavior ◽  
High Blood Pressure

Effects of wearable technology on patients with diabetes: A systematic review and meta-analysis (Preprint)

2020 ◽  
Author(s):  
Dongjun Wu ◽  
Nicholas Buys ◽  
Guandong Xu ◽  
Jing Sun
Keyword(s):  
Systematic Review ◽  
Blood Pressure ◽  
Relapse Prevention ◽  
Diabetes Management ◽  
Meta Analysis ◽  
Intervention Group ◽  
Wearable Technologies ◽  
Patients With Diabetes ◽  
Hba1c Levels

UNSTRUCTURED Aims: This systematic review and meta-analysis aimed to evaluate the effects of wearable technologies on HbA1c, blood pressure, body mass index (BMI), and fastening blood glucose (FBG) in patients with diabetes. Methods: We searched PubMed, Scopus, Embase, the Cochrane database, and the Chinese CNKI database from last 15 years until August 2021. The quality of the 16 included studies was assessed using the PEDro scale, and random effect models were used to estimate outcomes, with I2 used for heterogeneity testing. Results: A significant reduction in HbA1c (-0.475% [95% CI -0.692 to -0.257, P<0.001]) was found following telemonitoring. However, the results of the meta-analysis did not show significant changes in blood pressure, BMI, and glucose, in the intervention group (P>0.05), although the effect size for systolic blood pressure (0.389) and diastolic blood pressure may indicate a significant effect. Subgroup analysis revealed statistically significant effects of wearable technologies on HbA1c when supported by dietetic interventions (P<0.001), medication monitoring (P<0.001), and relapse prevention (P<0.001). Online messages and telephone interventions significantly affected HbA1c levels (P<0.001). Trials with additional online face-to-face interventions showed greater reductions in HbA1c levels. Remote interventions including dietetic advice (P<0.001), medication (P<0.001), and relapse prevention (P<0.001) during telemonitoring showed a significant effect on HbA1c, particularly in patients attending ten or more intervention sessions (P<0.001). Conclusion: Wearable technologies can improve diabetes management by simplifying self-monitoring, allowing patients to upload their live measurement results frequently and thereby improving the quality of telemedicine. Wearable technologies also facilitate remote medication management, dietetic interventions, and relapse prevention.

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