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A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients
PURPOSE: This study aimed to investigate the rate and profile of bacterial infections, mortality-associated predictors, and report the most common microorganisms and antibiotic use in coronavirus disease-19 (COVID-19) patients. PATIENTS AND METHODS: This study used a retrospective approach to evalua...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983054/ https://www.ncbi.nlm.nih.gov/pubmed/35392031 http://dx.doi.org/10.2147/IJGM.S351180 |
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author | Suranadi, I Wayan Sucandra, I Made Agus Kresna Fatmawati, Ni Nengah Dwi Wisnawa, Ayu Dilia Febriani |
author_facet | Suranadi, I Wayan Sucandra, I Made Agus Kresna Fatmawati, Ni Nengah Dwi Wisnawa, Ayu Dilia Febriani |
author_sort | Suranadi, I Wayan |
collection | PubMed |
description | PURPOSE: This study aimed to investigate the rate and profile of bacterial infections, mortality-associated predictors, and report the most common microorganisms and antibiotic use in coronavirus disease-19 (COVID-19) patients. PATIENTS AND METHODS: This study used a retrospective approach to evaluate the bacterial culture, antibiotic use, comorbidities, imaging, and laboratory discoveries of patients with COVID-19 (hospitalized) confirmed by reverse transcription polymerase chain reaction (RT-PCR) between May and December 2020. We have selected 906 COVID-19 positive patients using a consecutive sampling technique and analyzed data using IBM SPSS-22 statistical software. Statistical analysis included univariate, bivariate, and multivariate analysis. It was carried out using multivariable logistic regression analysis to predict the mortality of COVID-19 patients. RESULTS: A total of 410 patients, which involved 247 males with a mean age of 53.9 years were evaluated. Based on the results, the positive bacterial culture was detected in 18.3% of all patients who sent the culture sample test, representing bacterial infections. The Acinetobacter baumannii was the most commonly identified organism, while the proportion of patients treated with antibiotics was 83.4%. Furthermore, azithromycin was prescribed in the highest number of patients with approximately 44.3% of all antibiotics. The total mortality rate was 39.8% and its ratio was higher in COVID-19 patients with bacterial infections (65.3%, X(2) = 25.1, P<0.001). Patients mortality who used antibiotics were also higher compared to those who did not (89% vs 11%, P<0.014). Age, length of hospitalization, bacterial infection, shortness of breath, neutrophil-to-lymphocyte ratio (NLR), and diabetes mellitus were also associated predictors to increased hospital mortality (adjusted OR (aOR) 0.382, P<0.013; aOR 4.265, P<0.001; aOR 3.720, P<0.001; aOR 3.889, P<0.001; aOR 6.839, P<0.003; aOR 1.844, P<0.030), respectively. CONCLUSION: This study discovered that there is high use of antibiotics amongst COVID-19 patients; however, the bacterial infection rates did not exceed one-fifth of the total patients. Furthermore, older age, bacterial infections, a longer length of hospitalization, diabetes mellitus, shortness of breath, and higher NLR have a significant impact on the mortality of COVID-19 patients. |
format | Online Article Text |
id | pubmed-8983054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-89830542022-04-06 A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients Suranadi, I Wayan Sucandra, I Made Agus Kresna Fatmawati, Ni Nengah Dwi Wisnawa, Ayu Dilia Febriani Int J Gen Med Original Research PURPOSE: This study aimed to investigate the rate and profile of bacterial infections, mortality-associated predictors, and report the most common microorganisms and antibiotic use in coronavirus disease-19 (COVID-19) patients. PATIENTS AND METHODS: This study used a retrospective approach to evaluate the bacterial culture, antibiotic use, comorbidities, imaging, and laboratory discoveries of patients with COVID-19 (hospitalized) confirmed by reverse transcription polymerase chain reaction (RT-PCR) between May and December 2020. We have selected 906 COVID-19 positive patients using a consecutive sampling technique and analyzed data using IBM SPSS-22 statistical software. Statistical analysis included univariate, bivariate, and multivariate analysis. It was carried out using multivariable logistic regression analysis to predict the mortality of COVID-19 patients. RESULTS: A total of 410 patients, which involved 247 males with a mean age of 53.9 years were evaluated. Based on the results, the positive bacterial culture was detected in 18.3% of all patients who sent the culture sample test, representing bacterial infections. The Acinetobacter baumannii was the most commonly identified organism, while the proportion of patients treated with antibiotics was 83.4%. Furthermore, azithromycin was prescribed in the highest number of patients with approximately 44.3% of all antibiotics. The total mortality rate was 39.8% and its ratio was higher in COVID-19 patients with bacterial infections (65.3%, X(2) = 25.1, P<0.001). Patients mortality who used antibiotics were also higher compared to those who did not (89% vs 11%, P<0.014). Age, length of hospitalization, bacterial infection, shortness of breath, neutrophil-to-lymphocyte ratio (NLR), and diabetes mellitus were also associated predictors to increased hospital mortality (adjusted OR (aOR) 0.382, P<0.013; aOR 4.265, P<0.001; aOR 3.720, P<0.001; aOR 3.889, P<0.001; aOR 6.839, P<0.003; aOR 1.844, P<0.030), respectively. CONCLUSION: This study discovered that there is high use of antibiotics amongst COVID-19 patients; however, the bacterial infection rates did not exceed one-fifth of the total patients. Furthermore, older age, bacterial infections, a longer length of hospitalization, diabetes mellitus, shortness of breath, and higher NLR have a significant impact on the mortality of COVID-19 patients. Dove 2022-04-01 /pmc/articles/PMC8983054/ /pubmed/35392031 http://dx.doi.org/10.2147/IJGM.S351180 Text en © 2022 Suranadi et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Suranadi, I Wayan Sucandra, I Made Agus Kresna Fatmawati, Ni Nengah Dwi Wisnawa, Ayu Dilia Febriani A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title | A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title_full | A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title_fullStr | A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title_full_unstemmed | A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title_short | A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients |
title_sort | retrospective analysis of the bacterial infections, antibiotic use, and mortality predictors of covid-19 patients |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983054/ https://www.ncbi.nlm.nih.gov/pubmed/35392031 http://dx.doi.org/10.2147/IJGM.S351180 |
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