Evidence map›Paper›PMID 21424278›Full record

ArticleHeart failure reviews2011

Device monitoring strategies in acute heart failure syndromes.

Michael A Samara, W H Wilson Tang

Abstract read
PubMed Publisher
In one paragraph

Article in Heart failure reviews, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Digital Health Applications in Heart Failure: a Critical Appraisal of Literature.Current treatment options in cardiovascular medicine · 2021
    Review
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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

2 authors at 1 institution in 1 country.

Michael A SamaraDepartment of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, 9500 Euclid Avenue, Desk J3-4, Cleveland, OH 44195, USA.
W H Wilson Tang
Cleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute heart failure syndromes (AHFS) represent the most common discharge diagnoses in adults over age 65 and translate into dramatically increased heart failure-associated morbidity and mortality. Conventional approaches to the early detection of pulmonary and systemic congestion have been shown to be of limited sensitivity. Despite their proven efficacy, disease management and structured telephone support programs have failed to achieve widespread use in part due to their resource intensiveness and reliance upon motivated patients. While once thought to hold great promise, results from recent prospective studies on telemonitoring strategies have proven disappointing. Implantable devices with their capacity to monitor electrophysiologic and hemodynamic parameters over long periods of time and with minimal reliance on patient participation may provide solutions to some of these problems. Conventional electrophysiologic parameters and intrathoracic impedance data are currently available in the growing population of heart failure patients with equipped devices. A variety of implantable hemodynamic monitors are currently under investigation. How best to integrate these devices into a systematic approach to the management of patients before, during, and after AHFS is yet to be established.

Indexed as

Cardiac CatheterizationCardiography, ImpedanceElectrophysiologic Techniques, CardiacRemote Sensing TechnologyAcute DiseaseAgedBlood VolumeDisease ManagementEarly DiagnosisEfficiency, OrganizationalEquipment DesignEvaluation Studies as TopicHeart FailureHemodynamicsHumansPatient Participation

Identifiers

PMID21424278
OpenAlexW2131385824

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.