Evidence map›Paper›PMID 30755074›Full record

ArticleJournal of the American Heart Association2019

Axial Muscle Size as a Strong Predictor of Death in Subjects With and Without Heart Failure.

Anupam Kumar, Bilal A Ansari, Jessica Kim, Arpita Suri, Sowmya Gaddam, Sowjanya Yenigalla, Jagan M Vanjarapu, Senthil Selvaraj, Dheera Tamvada, Jonathan Lee and 2 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  5. Arsenic disrupts extracellular vesicle-mediated signaling in regenerating myofibers.Toxicological sciences : an official journal of the Society of Toxicology · 2023
    Article
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  9. Article
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  13. The mNature communications · 2022
    Article
  14. Article
  15. Article
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  17. Observational
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  19. 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

12 authors.

Anupam Kumar1 Hospital of the University of Pennsylvania Philadelphia PA.
Bilal A Ansari1 Hospital of the University of Pennsylvania Philadelphia PA.
Jessica Kim1 Hospital of the University of Pennsylvania Philadelphia PA.
Arpita Suri1 Hospital of the University of Pennsylvania Philadelphia PA.
Sowmya Gaddam1 Hospital of the University of Pennsylvania Philadelphia PA.
Sowjanya Yenigalla1 Hospital of the University of Pennsylvania Philadelphia PA.
Jagan M Vanjarapu1 Hospital of the University of Pennsylvania Philadelphia PA.
Senthil Selvaraj1 Hospital of the University of Pennsylvania Philadelphia PA.
Dheera Tamvada1 Hospital of the University of Pennsylvania Philadelphia PA.
Jonathan Lee1 Hospital of the University of Pennsylvania Philadelphia PA.
Scott R Akers3 Corporal Michael J. Crescenz VAMC Philadelphia PA.
Julio A Chirinos1 Hospital of the University of Pennsylvania Philadelphia PA.

Funding

NRSA Training CoreTL1TR001880 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI MEAGHER, EMMA ANNE · 2016 to 2025
$10.0M
Efficacy of Potassium Nitrate in Heart Failure with Preserved Ejection FractionR01HL121510 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI CHIRINOS MEDINA, JULIO ALONSO · 2015 to 2019
$3.1M
Targeting Wave Reflections in Heart Failure with Preserved Ejection FractionR21AG043802 · NIA · UNIVERSITY OF PENNSYLVANIA · PI CHIRINOS MEDINA, JULIO ALONSO · 2013 to 2014
$440k
NCATS NIH HHS TL1 TR001880NHLBI NIH HHS R01 HL121510NIA NIH HHS R21 AG043802
6 · The paper itself

Abstract

Background The impact of skeletal muscle size, quantified using simple noninvasive images routinely obtained during cardiac magnetic resonance imaging studies on mortality in the heart failure ( HF ) population is currently unknown. Methods and Results We prospectively enrolled 567 subjects without HF (n=364), with HF with reduced ejection fraction (n=111), or with HF with preserved ejection fraction (n=92), who underwent a cardiac magnetic resonance imaging. Skeletal muscle cross-sectional area was assessed with manual tracing of major thoracic muscle groups on axial chest magnetic resonance images. Factor analysis was used to identify a latent factor underlying the shared variability in thoracic muscle cross-sectional area. Cox regression was used to assess the relationship between these measurements and all-cause mortality (median follow up, 36.4 months). A higher overall thoracic muscle area factor assessed with principal component analysis was independently associated with lower mortality (standardized hazard ratio, 0.51; P<0.0001). The thoracic muscle area factor was predictive of death in subjects with HF with preserved ejection fraction, HF with reduced ejection fraction, and those without HF . Among all muscle groups, the pectoralis major cross-sectional area was the most representative of overall muscle area and was also the most robust predictor of death. A higher pectoralis major cross-sectional area predicted a lower mortality (standardized hazard ratio, 0.49; P<0.0001), which persisted after adjustment for various confounders (standardized hazard ratio, 0.55; P=0.0017). Conclusions Axial muscle size, and in particular smaller size of the pectoralis major, is independently associated with higher risk of mortality in patients with and without HF . Further work should clarify the role of muscle wasting as a therapeutic target in patients with HF .

Indexed as

AgedCause of DeathFemaleFollow-Up StudiesHeart FailureHumansMagnetic Resonance Imaging, CineMaleMiddle AgedOrgan SizePectoralis MusclesPredictive Value of TestsProspective StudiesStroke VolumeSurvival RateTime Factorsheart failure with preserved ejection fractionheart failure with reduced ejection fractionmortalitymuscle mass

Identifiers

PMID30755074
PMCPMC6405649

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LicenceCC BY-NC
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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.