Evidence map›Paper›PMID 33129663›Full record

ArticleJournal of the American College of Cardiology2020

Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19.

Jesus Alvarez-Garcia, Samuel Lee, Arjun Gupta, Matthew Cagliostro, Aditya A Joshi, Mercedes Rivas-Lasarte, Johanna Contreras, Sumeet S Mitter, Gina LaRocca, Pilar Tlachi and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American College of Cardiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed, 6 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

124 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
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  4. Pooled it
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  6. Meta-Analysis of Atrial Fibrillation in Patients With COVID-19.The American journal of cardiology · 2021
    Pooled it
  7. Article
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  10. Observational
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  12. Review
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  19. Cardiovascular disease and covid-19: A systematic review.International journal of cardiology. Heart & vasculature · 2024
    Review
  20. Review

64 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Jesus Alvarez-GarciaThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, CIBERCV, Universitat Autónoma de Barcelona, Barcelona, Spain. Electronic address: https://twitter.com/j_alvarezgarcia.
Samuel LeeThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Arjun GuptaThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Matthew CagliostroThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Aditya A JoshiThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Mercedes Rivas-LasarteCardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, CIBERCV, Universitat Autónoma de Barcelona, Barcelona, Spain.
Johanna ContrerasThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Sumeet S MitterThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Gina LaRoccaThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Pilar TlachiThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Danielle BrunjesThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Benjamin S GlicksbergThe Hasso Plattner Institute for Digital Health at Mount Sinai, New York, New York; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York; The Mount Sinai Clinical Intelligence Center, New York, New York.
Matthew A LevinDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York; Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, New York.
Girish NadkarniThe Hasso Plattner Institute for Digital Health at Mount Sinai, New York, New York; The Mount Sinai Clinical Intelligence Center, New York, New York; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York.
Zahi FayadThe BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York.
Valentin FusterThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain.
Donna ManciniThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Anuradha LalaThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York. Electronic address: anu.lala@mountsinai.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse.

objectivesThis study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19.

methodsThis study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF).

resultsMean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use.

conclusionsHistory of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.

Indexed as

Heart FailureHospitalizationAgedAged, 80 and overCohort StudiesCOVID-19FemaleHospital MortalityHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorscoronavirusCOVID-19heart failureleft ventricular ejection fractionoutcomerenin-angiotensin-aldosterone system inhibitor

Identifiers

PMID33129663
PMCPMC7598769

What OpenQuestion holds

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Read underepoch 390

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.