Evidence mapPaperPMID 33714416Full record

SynthesisIndian heart journal

Impact of congestive heart failure and role of cardiac biomarkers in COVID-19 patients: A systematic review and meta-analysis.

Tarun Dalia, Shubham Lahan, Sagar Ranka, Prakash Acharya, Archana Gautam, Amandeep Goyal, Ioannis Mastoris, Andrew Sauer, Zubair Shah

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Indian heart journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
0.8field-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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Predicting mortality in hospitalized COVID-19 patients.Internal and emergency medicine · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. COVID19 biomarkers: What did we learn from systematic reviews?Frontiers in cellular and infection microbiology · 2022
    Review
  15. Prognostic significance of CHADSJournal of cardiovascular and thoracic research · 2022
    Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

9 authors at 3 institutions in 2 countries.

Tarun DaliaDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA.
Shubham LahanUniversity College of Medical Sciences, New Delhi, India.
Sagar RankaDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA.
Prakash AcharyaDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA.
Archana GautamDepartment of Nephrology, The University of Kansas Health System, KS, USA.
Amandeep GoyalResearch and Clinical Fellow, Advanced heart failure and transplant division, University of Kansas Medical Center, Kansas City, Kansas, USA. Electronic address: agoyal3@kumc.edu.
Ioannis MastorisDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA.
Andrew SauerDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA.
Zubair ShahDepartment of Cardiovascular Medicine, The University of Kansas Health System, KS, USA. Electronic address: zshah2@kumc.edu.
University of Kansas · USUniversity College of Medical Sciences · INUniversity of Kansas Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) has been reported to cause worse outcomes in patients with underlying cardiovascular disease, especially in patients with acute cardiac injury, which is determined by elevated levels of high-sensitivity troponin. There is a paucity of data on the impact of congestive heart failure (CHF) on outcomes in COVID-19 patients.

methodsWe conducted a literature search of PubMed/Medline, EMBASE, and Google Scholar databases from 11/1/2019 till 06/07/2020, and identified all relevant studies reporting cardiovascular comorbidities, cardiac biomarkers, disease severity, and survival. Pooled data from the selected studies was used for metanalysis to identify the impact of risk factors and cardiac biomarker elevation on disease severity and/or mortality.

resultsWe collected pooled data on 5967 COVID-19 patients from 20 individual studies. We found that both non-survivors and those with severe disease had an increased risk of acute cardiac injury and cardiac arrhythmias, our pooled relative risk (RR) was - 8.52 (95% CI 3.63-19.98) (p < 0.001); and 3.61 (95% CI 2.03-6.43) (p = 0.001), respectively. Mean difference in the levels of Troponin-I, CK-MB, and NT-proBNP was higher in deceased and severely infected patients. The RR of in-hospital mortality was 2.35 (95% CI 1.18-4.70) (p = 0.022) and 1.52 (95% CI 1.12-2.05) (p = 0.008) among patients who had pre-existing CHF and hypertension, respectively.

conclusionCardiac involvement in COVID-19 infection appears to significantly adversely impact patient prognosis and survival. Pre-existence of CHF, and high cardiac biomarkers like NT-pro BNP and CK-MB levels in COVID-19 patients correlates with worse outcomes.

Indexed as

BiomarkersCOVID-19Creatine Kinase, MB FormHeart FailureHumansNatriuretic Peptide, BrainPandemicsPeptide FragmentsPrognosisSARS-CoV-2Severity of Illness IndexSurvival RateTroponinBiomarkersCreatine Kinase, MB FormNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)TroponinAcute cardiac injuryCardiac arrhythmiaCardiac biomarkersCOVID-19Mortality risk

Identifiers

PMID33714416
PMCPMC7719198
OpenAlexW3111911754

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.