ArticleSensors (Basel, Switzerland)2018
Sensing and Storing the Blood Pressure Measure by Patients through A Platform and Mobile Devices
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Accuracy of Mobile Applications versus Wearable Devices in Long-Term Step Measurements.Sensors (Basel, Switzerland) · 2020Article
- Mobile health technologies in the prevention and management of hypertension: A scoping review.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this article, we present a platform that allows for the integration of different applications for the follow-up of patients with chronic diseases. We developed two elements: a mobile and a web application. The mobile application allows the capture and processing of vital signs for patients with high blood pressure (hypertension). This application allows for the patient to store the data obtained, provides historical information and trends of the stored measures, and provides alerts and recommendations according to ranges of measures that were obtained. The web application allows the doctor and patients to obtain updated information of the disease behavior through the measures obtained. We used different biometric devices including an efimomanometer, glucometer, scale, and a thermometer with a wi-fi connection. Through this web application, we also generated information about average measures at a given time, by age, by region, and by a specific date. The developed system was evaluated in a medical center with different types of patients.
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Registered trials
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