The connected health of cardiovascular medicine: current status and future directions

Ansary, Ali M; Azuma, Alex; Komatireddy, Ravi; Barrett, Paddy

doi:10.1093/qjmed/hct159

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…mHealth can improve blood pressure control by enhancing patient awareness in self‐management and strengthening communication between healthcare providers and patients 31,32 . A previous meta‐analysis has reported the benefit of mHealth on blood pressure management in the general hypertensive population.…”

Section: Discussionmentioning

confidence: 99%

“…30 mHealth can improve blood pressure control by enhancing patient awareness in self-management and strengthening communication between healthcare providers and patients. 31,32 A previous metaanalysis has reported the benefit of mHealth on blood pressure management in the general hypertensive population. Its subgroup analysis demonstrated that the effect size tended to be more prominent in those with baseline uncontrolled hypertension, 33 Morawski and coworkers has reported that mHealth management had no significant benefit in systolic blood pressure control and only had improvement in self-reported adherence.…”

Section: Number Of Comparisons Wmd (95% Ci) P P For Interactionmentioning

confidence: 99%

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Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials

Zhou

Kong

et al. 2023

J of Clinical Hypertension

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The benefits of mHealth interventions in uncontrolled hypertension are unclear. To determine whether mHealth effectively improves the control rate of uncontrolled hypertension. PubMed, Web of Science, EMBASE, Scopus, and Cochrane Library were searched for randomized controlled trials (RCTs) from January 2007 to September 2022. The intervention group consisted of mHealth intervention, and the control group was usual care. Random‐effects meta‐analysis models were used to assess pooled mHealth intervention effects and CIs. The primary outcome was the blood pressure (BP) control rate of uncontrolled hypertension. The secondary outcome was the change of BP. Thirteen RCTs were included in this meta‐analysis, of which eight reported the successful BP control rate, 13 reported the change of systolic blood pressure (SBP), and 11 reported the change in diastolic blood pressure (DBP). The mean age of trial participants ranged from 47.7 to 66.9 years old, with a female composition ratio of 40.0%–66.1%. The duration of follow‐up ranged from 3 to 18 months. This study showed a more robust effect size for improving BP control rate by mHealth interventions than usual care (57.5% vs. 40.8% of successful control rate; odds ratio [OR], 2.19 [95% CI, 1.32—3.62]). Furthermore, mHealth significantly reduced SBP by 4.45 mm Hg and DBP by 2.47 mm Hg, and subgroup analysis did not observe the major source of heterogeneity. This meta‐analysis found that mHealth could significantly improve the uncontrolled hypertension control rate and might be a feasible, acceptable, and effective tool for uncontrolled hypertension management.

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Section: Discussionmentioning

confidence: 99%

Section: Number Of Comparisons Wmd (95% Ci) P P For Interactionmentioning

confidence: 99%

Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials

Zhou

Kong

et al. 2023

J of Clinical Hypertension

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“…One of the areas of concern that Connected Health will have impact, besides caring for the aged (such as in [42]), is in the management of chronic diseases [6]. As a result, many researchers working on Connected Health are already testing the relevance and applicability of connected health in the management of chronic diseases such as cardiovascular disease [7] and dementia [18]. In confirming the practical applicability of Connected Health [41] reported a project which produced WIISEL (Wireless Insole for Independent and Safe Elderly Living) system, designed to monitor fall risk and to detect falls in older people [42].…”

Section: A Connected Healthmentioning

confidence: 99%

Integration of Recommendation Systems Into Connected Health for Effective Management of Chronic Diseases

Afolabi

Toivanen

2019

IEEE Access

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An important trend in meeting the needs of modern caregiving is providing a well-rounded care delivery. In doing this, access to data of care receiver is important. This, however, has been shown to be possible with connected health with the aid of modern technology. In this paper, we are presenting a design that will expand on the opportunities for better data accessibility and use, by integrating the recommendation system into connected health. In order to ensure a design that meets the needs of care receivers, we conducted two independent surveys with a view to gathering requirements for the design. The result has shown the relevance of timeliness in caregiving along with what the care receivers are interested in such as what their data say about their conditions, the immediate and future expectation of their conditions, and collaborative efforts in managing their conditions. The requirements gathered were used in the design and implementation of the mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). The benefits of this solution have been real-time recommendations' availability, cost saving, adequate care, and access to health data and information for better care decision-making.INDEX TERMS Recommender systems, connected health real-time recommendations, ReTReSCAP, ReSCAP, healthcare.

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“…With further time for patient recall, the intervention lag could range from 2–5 days. The delay could be reduced with telephone follow‐up and use of recent advances in telemonitoring of clinical symptoms and signs . Taking this intervention lag into account is essential in planning a monitoring schedule.…”

Section: Limitations Of Monitoring Renal Functionmentioning

confidence: 99%

Renal function monitoring in heart failure – what is the optimal frequency? A narrative review

Al-Naher

Wright

Devonald

et al. 2017

Brit J Clinical Pharma

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The second most common cause of hospitalization due to adverse drug reactions in the UK is renal dysfunction due to diuretics, particularly in patients with heart failure, where diuretic therapy is a mainstay of treatment regimens. Therefore, the optimal frequency for monitoring renal function in these patients is an important consideration for preventing renal failure and hospitalization. This review looks at the current evidence for optimal monitoring practices of renal function in patients with heart failure according to national and international guidelines on the management of heart failure (AHA/NICE/ESC/SIGN). Current guidance of renal function monitoring is in large part based on expert opinion, with a lack of clinical studies that have specifically evaluated the optimal frequency of renal function monitoring in patients with heart failure. Furthermore, there is variability between guidelines, and recommendations are typically nonspecific. Safer prescribing of diuretics in combination with other antiheart failure treatments requires better evidence for frequency of renal function monitoring. We suggest developing more personalized monitoring rather than from the current medication‐based guidance. Such flexible clinical guidelines could be implemented using intelligent clinical decision support systems. Personalized renal function monitoring would be more effective in preventing renal decline, rather than reacting to it.

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The connected health of cardiovascular medicine: current status and future directions

Cited by 5 publications

References 15 publications

Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials

Effectiveness of mHealth interventions for improving hypertension control in uncontrolled hypertensive patients: A meta‐analysis of randomized controlled trials

Integration of Recommendation Systems Into Connected Health for Effective Management of Chronic Diseases

Renal function monitoring in heart failure – what is the optimal frequency? A narrative review

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