ArticleBMC infectious diseases2024
The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19.
Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
Corrections and comments
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Authors and funding
16 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.
resultsThe prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.
conclusionIdentified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.
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