Evidence map›Paper›PMID 34648044›Full record

ReviewDer Internist2021

[Heart failure care in a digitalized future : A discourse on resource-sparing structures and self-determined patients].

Thomas M Helms, Anne Köpnick, Alexander Leber, Christian Zugck, Henning Steen, Christoph Karle, Andrew Remppis, Bettina Zippel-Schultz

Abstract readCase ReportsReview
PubMed Publisher
In one paragraph

Review in Der Internist, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 4 institutions in 1 country.

Thomas M HelmsDeutsche Stiftung für chronisch Kranke, Fürth, Deutschland. thomas_helms@t-online.de.
Anne KöpnickDeutsche Stiftung für chronisch Kranke, Fürth, Deutschland.
Alexander LeberKardiologie, Isarklinikum München, München, Deutschland.
Christian ZugckKardiologie, Kardiologische Praxis im Steiner Thor, Straubing, Deutschland.
Henning Steenmedneo, Hamburg, Deutschland.
Christoph KarlePraxis für Diagnostik Hohenlohe, Künzelsau, Deutschland.
Andrew RemppisHerz- und Gefäßzentrum Bad Bevensen, Bad Bevensen, Deutschland.
Bettina Zippel-SchultzDeutsche Stiftung für chronisch Kranke, Fürth, Deutschland.
Deutsche Stiftung für Chronisch Kranke · DEKlinik Lüneburger Heide · DEMünchen Klinik · DEOrthopädische Praxis · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital health solutions, applications of artificial intelligence (AI) and new technologies, such as cardiac magnetic resonance imaging and cardiac human genetics are currently being validated in cardiac healthcare pathways. They show promising approaches for improving existing healthcare structures in the future by strengthening the focus on predictive, preventive and personalized medicine. In addition, the accompanying use of digital health applications will become increasingly more important in the future healthcare, especially in patients with chronic diseases. In this article, the authors describe a case of chronic heart failure (HF) as an example to provide an overview of how digitalized healthcare can be efficiently designed across sectors and disciplines in the future. Moreover, the importance of a self-determined patient management for the treatment process itself is underlined. Since HF is frequently accompanied by various comorbidities during the course of the disease that are often recognized only after a delay, the necessity for a timely simultaneous and preventive treatment of multiple comorbidities in cardiovascular diseases is emphasized. Against this background the currently separately applied disease management programs (DMP) are critically questioned. The development of a holistic DMP encompassing all indications for the treatment of chronic diseases may pave the way to a more efficient medical care system.

Indexed as

Artificial IntelligenceHeart FailureDelivery of Health CareForecastingHeartHumansArtificial intelligenceChronic diseaseDigital health applicationsDisease management programSelf-efficacy

Identifiers

PMID34648044
OpenAlexW3207774525

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.