Evidence map›Paper›PMID 31083545›Full record

ArticleJournal of clinical medicine2019

Suffering and Healing in the Context of LVAD Treatment.

Kristin Kostick, Meredith Trejo, J S Blumenthal-Barby

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2019. 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
–field-weighted citation impact
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.

  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

3 authors.

Kristin KostickBaylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, TX 77030, USA. Kristin.Kostick@bcm.edu.
Meredith TrejoBaylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, TX 77030, USA. Meredith.Trejo@bcm.edu.
J S Blumenthal-BarbyBaylor College of Medicine, Center for Medical Ethics and Health Policy, Houston, TX 77030, USA. jennifer.blumenthal-barby@bcm.edu.

Funding

Patient-Centered Outcomes Research Institute CDR-1306-01769
6 · The paper itself

Abstract

backgroundIllness narratives with meaningful, competent and targeted content have been shown to provide useful guides for patient decision-making and have positive influences on health behaviors. The use of narratives in decision aids can confer a sense of structure, plot and context to illness experiences and help patients make treatment decisions that feel sensible, informed, and transparent.

aimThis paper presents narratives of suffering and healing from patients and their caregivers with advanced heart failure who engaged in decision-making regarding Left Ventricular Device Assist (LVAD) treatment.

methodsNarratives were collected from in-depth interviews with patients who accepted (

resultsParticipants shared "restitution" narratives that most commonly conveyed a shift from pre-implant physical suffering and "daily hell," fatigue so intense it "hurts," along with emotional suffering from inability to engage with the world, to post-implant improvements in mobility and quality of life, including positivity and family support, adaptation on a "journey," "getting one's life back" and becoming "normal" again.

conclusionFor LVAD patients, other patients' illness narratives can help to give meaning to their own illness and treatment experiences and to more accurately forecast treatment impacts on lifestyle and identity. For clinicians, patient narratives can enhance patient-practitioner communication and understanding by highlighting perspectives and values that structure patients' clinical experiences.

Indexed as

illness narrativesLVADpatient experiencesuffering and healing

Identifiers

PMID31083545
PMCPMC6571968

What OpenQuestion holds

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Registered trials

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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.