Evidence map›Paper›PMID 27924346›Full record

ArticleApplied clinical informatics2016

BPcontrol. A Mobile App to Monitor Hypertensive Patients.

Adrian Carrera, Marc Pifarré, Jordi Vilaplana, Josep Cuadrado, Sara Solsona, Jordi Mateo, Francesc Solsona

Abstract read
In one paragraph

Article in Applied clinical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Adrian Carrera
Marc Pifarré
Jordi Vilaplana
Josep Cuadrado
Sara Solsona
Jordi Mateo
Francesc SolsonaFrancesc Solsona, Department of Computer Science and INSPIRES, University of Lleida, C/ Jaume II 69,, E-25001 Lleida, Spain, Email: francesc@diei.udl.cat.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypertension or high blood pressure is on the rise. Not only does it affect the elderly but is also increasingly spreading to younger sectors of the population. Treating this condition involves exhaustive monitoring of patients. The current mobile health services can be improved to perform this task more effectively.

objectiveTo develop a useful, user-friendly, robust and efficient app, to monitor hypertensive patients and adapted to the particular requirements of hypertension.

methodsThis work presents BPcontrol, an Android and iOS app that allows hypertensive patients to communicate with their health-care centers, thus facilitating monitoring and diagnosis. Usability, robustness and efficiency factors for BPcontrol were evaluated for different devices and operating systems (Android, iOS and system-aware). Furthermore, its features were compared with other similar apps in the literature.

resultsBPcontrol is robust and user-friendly. The respective start-up efficiency of the Android and iOS versions of BPcontrol were 2.4 and 8.8 times faster than a system-aware app. Similar values were obtained for the communication efficiency (7.25 and 11.75 times faster for the Android and iOS respectively). When comparing plotting performance, BPcontrol was on average 2.25 times faster in the Android case. Most of the apps in the literature have no communication with a server, thus making it impossible to compare their performance with BPcontrol.

conclusionsIts optimal design and the good behavior of its facilities make BPcontrol a very promising mobile app for monitoring hypertensive patients.

Indexed as

Mobile ApplicationsAlgorithmsBlood PressureHumansHypertensionMonitoring, PhysiologicTelemedicineUser-Computer InterfaceHypertensionremote monitoringtelemedicine and telehealth

Identifiers

PMID27924346
PMCPMC5228147

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.