Evidence map›Paper›PMID 35928232›Full record

ArticleCanadian journal of respiratory therapy : CJRT = Revue canadienne de la therapie respiratoire : RCTR2022

Predictors of mortality among hospitalized patients with COVID-19: A single-centre retrospective analysis.

Kumar Pranshu, Aneesa Shahul, Surjit Singh, Ashok Kuwal, Maldev Sonigra, Naveen Dutt

Abstract read
In one paragraph

Article in Canadian journal of respiratory therapy : CJRT = Revue canadienne de la therapie respiratoire : RCTR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

6 authors.

Kumar PranshuDepartment of Pulmonary Medicine, Pacific Institute of Medical Sciences, Udaipur.
Aneesa ShahulDepartment of Pulmonary Medicine, AIIMS, Jodhpur.
Surjit SinghDepartment of Pharmacology, AIIMS, Jodhpur.
Ashok KuwalDepartment of Pulmonary Medicine, Dr S N Medical College, Jodhpur.
Maldev SonigraDepartment of Pulmonary Medicine, AIIMS, Jodhpur.
Naveen DuttDepartment of Pulmonary Medicine, AIIMS, Jodhpur.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The severity of disease and mortality due to coronavirus disease (COVID-19) was found to be high among patients with concurrent medical illnesses. Serum biomarkers can be used to predict the course of COVID-19 pneumonia. Data from India are very scarce about predictors of mortality among COVID-19 patients. Methodology: In the present retrospective study of 65 RT-PCR confirmed COVID-19 patients, we retrieved data regarding clinical symptoms, laboratory parameters, and radiological grading of severity. Further, we also collected data about their hospital course, duration of stay, treatment, and outcome. Data analysis was done to compare the patient characteristics between survivor and non-survivor groups and to assess the predictors of mortality. Results: The mean age of the study population was 56.23 years (SD, 12.91) and most of them were males (63%); 81.5% of patients survived and were discharged, whereas 18.5% of patients succumbed to the disease. Univariate analysis across both groups showed that older age, diabetes mellitus, higher computed tomogram (CT) severity score, and raised levels of laboratory parameters viz, D-dimer, CPK-MB (creatine kinase), and lactate dehydrogenase (LDH) were associated with increased mortality among hospitalized patients. On multivariate analysis, elevated levels of serum D-dimer (odds ratio, 95% CI: 10.98, 1.13-106.62, Conclusion: Older patients, diabetics, and patients with high CT severity scores at admission are at increased risk of death from COVID-19. Serum biomarkers such as D-dimer and LDH help in predicting mortality in COVID-19 patients.

Indexed as

comorbidityCOVID-19inflammatory markersmortalitypredictors

Identifiers

PMID35928232
PMCPMC9318266

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