Evidence map›Paper›PMID 32998237›Full record

ArticleGeriatrics (Basel, Switzerland)2020

Factors Predicting the Utilization of Center-Based Cardiac Rehabilitation Program.

Lufei Young, Qi Zhang, Eric Lian, Kimberly Roberts, Neal Weintraub, Yanbin Dong, Haidong Zhu, Hongyan Xu, Pascha Schafer, Stephanie Dunlap

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Geriatrics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
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

10 authors at 3 institutions in 2 countries.

Lufei YoungCollege of Nursing, Augusta University, Augusta, GA 30912, USA.ORCID 0000-0001-5056-4777
Qi ZhangThe Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China.
Eric LianDepartments of Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Kimberly RobertsDepartment of Nursing, School of Health Sentences, Georgia Highlands College, Rome, GA 30161, USA.
Neal WeintraubDepartments of Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.ORCID 0000-0002-5138-3705
Yanbin DongGeorgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Haidong ZhuGeorgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Hongyan XuDepartment of Biostats & Data, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Pascha SchaferDepartments of Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Stephanie DunlapDepartments of Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Augusta University · USChinese University of Hong Kong · HKGeorgia Highlands College · US

Funding

Innovative Approaches to Treat Duchenne Muscular Dystrophy Using iPSC-Derived Muscle ProgenitorsR01AR070029 · NIAMS · AUGUSTA UNIVERSITY · PI ASHRAF, MUHAMMAD, TANG, YAO LIANG · 2016 to 2021
$2.6M
Notch1/miR-322 Axis in Stem Cell Mediated Vascular RepairR01HL134354 · NHLBI · AUGUSTA UNIVERSITY · PI ASHRAF, MUHAMMAD, TANG, YAO LIANG · 2016 to 2020
$2.5M
Mechanisms of myeloperoxidase and Nox4 interactions in abdominal aortic aneurysmR01HL142097 · NHLBI · AUGUSTA UNIVERSITY · PI WEINTRAUB, NEAL L · 2018 to 2021
$2.1M
Epigenetic regulation of HDAC9 in obesity and atherosclerosisR01HL126949 · NHLBI · AUGUSTA UNIVERSITY · PI WEINTRAUB, NEAL L · 2016 to 2019
$1.8M
HDAC9, Aging and Alzheimer's DiseaseR56AG064895 · NIA · AUGUSTA UNIVERSITY · PI LU, XIN-YUN, WEINTRAUB, NEAL L · 2019 to 2020
$1.5M
NHLBI NIH HHS R01 HL126949NHLBI NIH HHS R01 HL134354NHLBI NIH HHS R01 HL142097NIAMS NIH HHS R01 AR070029NIA NIH HHS R56 AG064895
6 · The paper itself

Abstract

Although cardiac rehabilitation (CR) is clearly beneficial to improving patients' physical functioning and reducing heart disease progression, significant proportions of patients do not complete CR programs. To evaluate the prevalence and predictors of completion of a center-based CR program in eligible cardiac patients, existing data collected from electronic medical records were used. To identify the predictors of CR completion, we used principal components analysis (PCA) and an artificial neural network (ANN) module. Among 685 patients, 61.4% (

Indexed as

attendancecardiac rehabilitationincompletionneural networkprincipal components analysis

Identifiers

PMID32998237
PMCPMC7709641
OpenAlexW3088348521

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.