Evidence map›Paper›PMID 31508495›Full record

ArticleNPJ digital medicine2019

A protocol integrating remote patient monitoring patient reported outcomes and cardiovascular biomarkers.

Chrisandra Shufelt, Eldin Dzubur, Sandy Joung, Garth Fuller, Kelly N Mouapi, Irene Van Den Broek, Mayra Lopez, Shivani Dhawan, Corey W Arnold, William Speier and 5 more

Open access · goldAbstract read
In one paragraph

Article in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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  8. Feasibility of Patient-Centric Remote DriedBiodemography and social biology
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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

15 authors at 2 institutions in 1 country.

Chrisandra Shufelt1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Eldin DzuburCedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, CA USA.
Sandy Joung1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Garth FullerCedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, CA USA.
Kelly N Mouapi1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Irene Van Den Broek1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Mayra LopezCedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, CA USA.
Shivani Dhawan1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Corey W Arnold4Medical Imaging and Informatics Group, University of California, Los Angeles, CA USA.
William Speier4Medical Imaging and Informatics Group, University of California, Los Angeles, CA USA.
Mitra Mastali1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Qin Fu1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Jennifer E Van Eyk1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Brennan SpiegelCedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, CA USA.
C Noel Bairey Merz1Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.ORCID 0000-0002-9933-5155
Cedars-Sinai Medical Center · USUniversity of California, Los Angeles · US

Funding

UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
Genomic and Proteomic Architecture of AtherosclerosisR01HL111362 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HERRINGTON, DAVID MCLEOD · 2012 to 2021
$17.2M
UF Clinical and Translational Science AwardUL1TR000064 · NCATS · UNIVERSITY OF FLORIDA · PI NELSON, DAVID R · 2012 to 2014
$12.2M
Training in Advanced Heart Disease ResearchT32HL116273 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Joshua I Goldhaber, EDUARDO MARBAN · 2013 to 2026
$5.6M
Atherosclerosis, Immune Mediated Inflammation and Hypoestrogenemia in Young WomenK23HL127262 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI SHUFELT, CHRISANDRA LEE · 2016 to 2020
$988k
mHealth for Heart Failure: Predictive Models of Readmission Risk and Self-care Using Consumer Activity TrackersR56HL135425 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARNOLD, COREY WELLS · 2017 to 2017
$599k
NCATS NIH HHS UL1 TR000064NCATS NIH HHS UL1 TR000124NHLBI NIH HHS K23 HL127262NHLBI NIH HHS R01 HL111362NHLBI NIH HHS R56 HL135425NHLBI NIH HHS T32 HL116273
6 · The paper itself

Abstract

We describe the protocol, design, and methodology of the Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE-MACE) study as a multicomponent remote patient monitoring in cardiology. Using biosensor, biomarkers, and patient-reported outcomes in participants with stable ischemic heart disease, the PRE-MACE study is designed to measure cross-sectional correlations and establish the ability of remote monitoring to predict major adverse cardiovascular event (MACE) biomarkers and incident MACE at baseline and 12-month follow-up. It will further assess the adherence and cost-effectiveness of remote monitoring and blood sampling over the initial months. Despite medication and lifestyle changes, patients with cardiovascular disease can experience MACE due to undertreatment, poor adherence, or failure to recognize clinical or biochemical changes that presage MACE. Identifying patients using remote monitoring to detect MACE forerunners has potential to improve outcomes, avoid MACE, and reduce resource utilization. Data collection will include: (1) continuous remote monitoring using wearable biosensors; (2) biomarker measurements using plasma and at-home micro-sampling blood collection; and (3) patient-reported outcomes to monitor perceived stress, anxiety, depression, and health-related quality of life. Two hundred participants will be followed for 90 days with a subset (

Indexed as

Cardiovascular diseasesPredictive markers

Identifiers

PMID31508495
PMCPMC6722086
OpenAlexW2971432374

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.