Evidence map›Paper›PMID 29075920›Full record

ArticleJournal of medical systems2017

Primary Prevention of Asymptomatic Cardiovascular Disease Using Physiological Sensors Connected to an iOS App.

Leire Moreno-Alsasua, Begonya Garcia-Zapirain, J David Rodrigo-Carbonero, Ibon Oleagordia Ruiz, Sofiane Hamrioui, Isabel de la Torre Díez

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. A mobile app for Glaucoma diagnosis and its possible clinical applications.BMC medical informatics and decision making · 2020
    Article
  3. Review
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

6 authors at 4 institutions in 2 countries.

Leire Moreno-AlsasuaeVIDA - DeustoTechLIFE Research Group, Universidad de Deusto, Avda/Universidades 24, 48007, Bilbao, Spain.
Begonya Garcia-ZapiraineVIDA - DeustoTechLIFE Research Group, Universidad de Deusto, Avda/Universidades 24, 48007, Bilbao, Spain.
J David Rodrigo-CarboneroCardiology Department, Cruces University Hospital, University of the Basque Country, Vizcaya, Spain.
Ibon Oleagordia RuizeVIDA - DeustoTechLIFE Research Group, Universidad de Deusto, Avda/Universidades 24, 48007, Bilbao, Spain.
Sofiane HamriouiBretagne Loire and Nantes Universities, UMR 6164, IETR Polytech Nantes, Nantes, France.
Isabel de la Torre DíezDepartment of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain. isator@tel.uva.es.ORCID http://orcid.org/0000-0003-3134-7720
Universidad de Deusto · ESInstitut d'Électronique et des Technologies du numéRique · FRUniversidad de Valladolid · ESUniversity of the Basque Country · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease is the first cause of death and disease and one of the leading causes of disability in developed countries. The prevalence of this disease is expected to increase in coming years although the death rate may be lower due to better treatment. To present the design and development of a technology solution for primary prevention of cardiovascular disease in asymptomatic patients. The system aims to raise the population's awareness of the importance of adopting healthy heart habits by using self-feedback techniques. A series of sensors which makes it possible to detect cardiovascular risk factors in asymptomatic patients were used. These sensors enable evaluation of heart rate, blood pressure, SpO

Indexed as

SmartphoneAdolescentAdultBlood PressureBody TemperatureCardiovascular DiseasesDietEarly DiagnosisExerciseFemaleHeart RateHumansMaleMiddle AgedOximetryPrimary PreventioniHealth pulse oximeteriOSMonitoringPrimary detectionWithings blood pressure monitor

Identifiers

PMID29075920
OpenAlexW2765781337

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.