Evidence map›Paper›PMID 33038410›Full record

ArticleInternational journal of cardiology2021

Extent of lung involvement over severity of cardiac disease for the prediction of adverse outcome in COVID-19 patients with cardiovascular disease.

Daniele Andreini, Edoardo Conte, Saima Mushtaq, Carlo Gigante, Maria Elisabetta Mancini, Andrea Annoni, Giulio Stefanini, Cecilia Agalbato, Nicola Cosentino, Gianluca Pontone and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in International journal of cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

12 authors at 2 institutions in 1 country.

Daniele AndreiniCentro Cardiologico Monzino, IRCCS, Milan, Italy; Department of Clinical Sciences and Community Health, Cardiovascular Section, University of Milan, Milan, Italy. Electronic address: daniele.andreini@ccfm.it.
Edoardo ConteCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Saima MushtaqCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Carlo GiganteCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Maria Elisabetta ManciniCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Andrea AnnoniCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Giulio StefaniniDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Humanitas Clinical and Research Hospital IRCCS, Rozzano, Milan, Italy.
Cecilia AgalbatoCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Nicola CosentinoCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Gianluca PontoneCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Emilio AssanelliCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Mauro PepiCentro Cardiologico Monzino, IRCCS, Milan, Italy.
Centro Cardiologico Monzino · ITIRCCS Humanitas Research Hospital · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAim of the present study was to assess if the presence of high cardiovascular risk, left ventricle systolic dysfunction or elevated BNP or Troponin are able to independently predict the outcome of patients with known cardiac disease and COVID-19 pneumonia. METHODS AND

resultsFrom March 7th to April 28th, forty consecutive patients with known cardiac disease (chronic coronary artery disease, n=38; atrial fibrillation, n = 7; valvular disease, n = 13) referred to our emergency department for symptoms of suspected COVID-19, laboratory diagnosis of COVID-19 and typical signs of viral pneumonia at chest CT were enrolled in the study. The only predictor of the composite end-point (all cause of death + invasive ventilation + thromboembolic event) was the lung involvement % at chest CT (OR: 1.06; 95%CI: 1.01-1.11, P = 0.02). In the multivariate analysis, the lung involvement % at chest CT was the only independent predictor of the composite end-point (OR: 1.06; 95%CI: 1.01-1.11, P = 0.034).

conclusionsThe extent of lung involvement by COVID-19 is the only independent predictor of adverse outcome of patients and is predominant over the severity of cardiac disease.

Indexed as

Severity of Illness IndexAgedCardiovascular DiseasesCOVID-19Emergency Service, HospitalFemaleHospitalizationHumansItalyLungMaleMultivariate AnalysisRespiration, ArtificialThromboembolismTomography, X-Ray Computedcardiovascular diseaseCovid-19lung diseasenon-contrast CT scan

Identifiers

PMID33038410
PMCPMC7543753
OpenAlexW3092406618

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.