Evidence map›Paper›PMID 34804519›Full record

ArticleClinical kidney journal2021

Global longitudinal strain by feature-tracking cardiovascular magnetic resonance imaging predicts mortality in patients with end-stage kidney disease.

Alastair J Rankin, Luke Zhu, Kenneth Mangion, Elaine Rutherford, Keith A Gillis, Jennifer S Lees, Rosie Woodward, Rajan K Patel, Colin Berry, Giles Roditi and 1 more

Abstract read
In one paragraph

Article in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Myocardial changes on 3T cardiovascular magnetic resonance imaging in response to haemodialysis with fluid removal.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2021
    Observational
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

11 authors.

Alastair J RankinInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-9031-481X
Luke ZhuInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Kenneth MangionInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0002-3505-7440
Elaine RutherfordInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-9818-8758
Keith A GillisRenal and Transplant Unit, NHS Greater Glasgow and Clyde, Glasgow, UK.
Jennifer S LeesInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-6331-0178
Rosie WoodwardClinical Research Imaging, NHS Greater Glasgow and Clyde, Glasgow, UK.
Rajan K PatelInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Colin BerryInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0002-4547-8636
Giles RoditiInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-9393-7764
Patrick B MarkInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0003-3387-2123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with end-stage kidney disease (ESKD) are at increased risk of premature death, with cardiovascular disease being the predominant cause of death. We hypothesized that left ventricular global longitudinal strain (LV-GLS) measured by feature-tracking cardiovascular magnetic resonance imaging (CMRI) would be associated with all-cause mortality in patients with ESKD.

methodsA pooled analysis of CMRI studies in patients with ESKD acquired within a single centre between 2002 and 2016 was carried out. CMR parameters including LV ejection fraction (LVEF), LV mass index, left atrial emptying fraction (LAEF) and LV-GLS were measured. We tested independent associations of CMR parameters with survival using a multivariable Cox model.

resultsAmong 215 patients (mean age 54 years, 62% male), mortality was 53% over a median follow-up of 5 years. The median LVEF was 64.7% [interquartile range (IQR) 58.5-70.0] and the median LV-GLS was -15.3% (IQR -17.24 to -13.6). While 90% of patients had preserved LVEF (>50%), 58% of this group had abnormal LV-GLS (>-16%). On multivariable Cox regression, age {hazard ratio [HR] 1.04 [95% confidence interval (CI) 1.02-1.05]}, future renal transplant [HR 0.29 (95% CI 0.17-0.47)], LAEF [HR 0.98 (95% CI 0.96-1.00)] and LV-GLS [HR 1.08 (95% CI 1.01-1.16)] were independently associated with mortality.

conclusionsIn this cohort of patients with ESKD, LV-GLS on feature-tracking CMRI and LAEF was associated with all-cause mortality, independent of baseline clinical variables and future renal transplantation. This effect was present even when >90% of the cohort had normal LVEF. Using LV-GLS instead of LVEF to diagnose cardiac dysfunction in patients with ESKD could result in a major advance in our understanding of cardiovascular disease in ESKD.

Indexed as

cardiovascularchronic renal failureESKDleft ventricular hypertrophymagnetic resonance imagingsurvival analysis

Identifiers

PMID34804519
PMCPMC8598121

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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.