Evidence map›Paper›PMID 35392031›Full record

ArticleInternational journal of general medicine2022

A Retrospective Analysis of the Bacterial Infections, Antibiotic Use, and Mortality Predictors of COVID-19 Patients.

I Wayan Suranadi, I Made Agus Kresna Sucandra, Ni Nengah Dwi Fatmawati, Ayu Dilia Febriani Wisnawa

Abstract read
In one paragraph

Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Review
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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

4 authors.

I Wayan SuranadiDepartment of Anesthesiology and Intensive Care, Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia.ORCID 0000-0002-8444-1633
I Made Agus Kresna SucandraDepartment of Anesthesiology and Intensive Care, Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia.
Ni Nengah Dwi FatmawatiDepartment of Clinical Microbiology, Faculty of Medicine, Udayana University, Denpasar, Bali, Indonesia.
Ayu Dilia Febriani WisnawaFaculty of Medicine, Udayana University, Denpasar, Bali, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 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.

Indexed as

antibioticsbacterial infectionsCOVID-19mortality

Identifiers

PMID35392031
PMCPMC8983054

What OpenQuestion holds

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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.