Evidence map›Paper›PMID 38567218›Full record

ArticleCureus2024

Association Between Baseline Echocardiographic Parameters and Acute Coronavirus Disease 2019 Infection in Hospitalized Patients.

Jin Wang, Dongmei Yang, Cheng Cao

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Jin WangDepartment of Echocardiography, The First Affiliated Hospital of University of Science and Technology of China (USTC), Hefei, CHN.
Dongmei YangDepartment of Echocardiography, The First Affiliated Hospital of University of Science and Technology of China (USTC), Hefei, CHN.
Cheng CaoDepartment of Cardiology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Hefei, CHN.
University of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The current study aimed to examine the association between baseline clinical and echocardiographic parameters with new-onset coronavirus disease 2019 (COVID-19) infection. Methodology We retrospectively enrolled consecutive hospitalized patients from our center during the national outbreak of the COVID-19 pandemic in China. Overall, 100 patients were enrolled, including 38 patients with COVID-19 infection. Results Compared with those without infection, patients with COVID-19 infection were more likely male (63.2% vs. 35.5%, p = 0.008), were older (59.08 vs. 52.35 years, p = 0.022), had higher heart failure (31.6% vs. 11.3%, p = 0.018) and hypertension (52.6% vs. 30.6%, p = 0.036) rates, had lower left ventricular ejection fraction (LVEF) (61.16% vs. 65.76%, p = 0.018), had higher A-wave velocity (86.84 vs. 73.63 cm/s, p = 0.003), and had and lower E/A ratio (0.85 vs 1.04, p = 0.015). On univariate and multivariate analysis, baseline echocardiographic parameters (LVEF and A-wave velocity) were independent risk factors for COVID-19 infection. There were no significant changes in echocardiographic parameters during the one-month follow-up period in patients infected and not infected with COVID-19. Conclusions In conclusion, baseline echocardiographic parameters were significantly associated with acute COVID-19 infection.

Indexed as

coronavirus disease 2019 (covid-19)doppler echocardiographyleft ventricular functionsars-cov-2 omicron variantshort-term outcomes

Identifiers

PMID38567218
PMCPMC10986441
OpenAlexW4392362925

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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.