Evidence map›Paper›PMID 28970189›Full record

ArticleJMIR mHealth and uHealth2017

Impact of a Telehealth Program With Voice Recognition Technology in Patients With Chronic Heart Failure: Feasibility Study.

Heesun Lee, Jun-Bean Park, Sae Won Choi, Yeonyee E Yoon, Hyo Eun Park, Sang Eun Lee, Seung-Pyo Lee, Hyung-Kwan Kim, Hyun-Jai Cho, Su-Yeon Choi and 7 more

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Machine Learning and Artificial Intelligence in Surgical Fields.Indian journal of surgical oncology · 2020
    Review
  9. 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

17 authors at 2 institutions in 1 country.

Heesun LeeDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0003-4037-3955
Jun-Bean ParkDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0003-4053-8713
Sae Won ChoiOffice of Hospital Information, Seoul National University Hospital, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-0123-8227
Yeonyee E YoonDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-8479-9889
Hyo Eun ParkDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0001-7233-1771
Sang Eun LeeDepartment of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-7290-2463
Seung-Pyo LeeDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-5502-3977
Hyung-Kwan KimDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0001-7950-2131
Hyun-Jai ChoDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-2779-4037
Su-Yeon ChoiDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0001-9977-4740
Hae-Young LeeDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-9521-4102
Jonghyuk ChoiAIMMED Co., Ltd., Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-6015-9166
Young-Joon LeeAIMMED Co., Ltd., Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-5756-7644
Yong-Jin KimDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-1366-432X
Goo-Yeong ChoDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-7067-5535
Jinwook ChoiDepartment of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-9424-9944
Dae-Won SohnDepartment of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic Of Korea.ORCID http://orcid.org/0000-0002-1092-3285
Seoul National University · KRUlsan College · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the advances in the diagnosis and treatment of heart failure (HF), the current hospital-oriented framework for HF management does not appear to be sufficient to maintain the stability of HF patients in the long term. The importance of self-care management is increasingly being emphasized as a promising long-term treatment strategy for patients with chronic HF.

objectiveThe objective of this study was to evaluate whether a new information communication technology (ICT)-based telehealth program with voice recognition technology could improve clinical or laboratory outcomes in HF patients.

methodsIn this prospective single-arm pilot study, we recruited 31 consecutive patients with chronic HF who were referred to our institute. An ICT-based telehealth program with voice recognition technology was developed and used by patients with HF for 12 weeks. Patients were educated on the use of this program via mobile phone, landline, or the Internet for the purpose of improving communication and data collection. Using these systems, we collected comprehensive data elements related to the risk of HF self-care management such as weight, diet, exercise, medication adherence, overall symptom change, and home blood pressure. The study endpoints were the changes observed in urine sodium concentration (uNa), Minnesota Living with Heart Failure (MLHFQ) scores, 6-min walk test, and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) as surrogate markers for appropriate HF management.

resultsAmong the 31 enrolled patients, 27 (87%) patients completed the study, and 10 (10/27, 37%) showed good adherence to ICT-based telehealth program with voice recognition technology, which was defined as the use of the program for 100 times or more during the study period. Nearly three-fourths of the patients had been hospitalized at least once because of HF before the enrollment (20/27, 74%); 14 patients had 1, 2 patients had 2, and 4 patients had 3 or more previous HF hospitalizations. In the total study population, there was no significant interval change in laboratory and functional outcome variables after 12 weeks of ICT-based telehealth program. In patients with good adherence to ICT-based telehealth program, there was a significant improvement in the mean uNa (103.1 to 78.1; P=.01) but not in those without (85.4 to 96.9; P=.49). Similarly, a marginal improvement in MLHFQ scores was only observed in patients with good adherence (27.5 to 21.4; P=.08) but not in their counterparts (19.0 to 19.7; P=.73). The mean 6-min walk distance and NT-proBNP were not significantly increased in patients regardless of their adherence.

conclusionsShort-term application of ICT-based telehealth program with voice recognition technology showed the potential to improve uNa values and MLHFQ scores in HF patients, suggesting that better control of sodium intake and greater quality of life can be achieved by this program.

Indexed as

complianceheart failureselfcaretelemedicine

Identifiers

PMID28970189
PMCPMC5643844
OpenAlexW2761766543

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.