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      Bacterial profile and drug susceptibility among adult patients with community acquired lower respiratory tract infection at tertiary hospital, Southern Ethiopia

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          Abstract

          Background

          Lower respiratory tract infection is a global problem accounting over 50 million deaths annually. Here, we determined the bacterial profile and antimicrobial susceptibility pattern of lower respiratory tract infections among adult patients attending at Tertiary Hospital, Southern Ethiopia.

          Methods

          A cross sectional study was conducted among adult patients with lower respiratory infection at the medical outpatient department of the Hospital. A sputum sample was collected and processed for bacterial culture and antimicrobial susceptibility test. Semi structured questionnaires were used to collect data. SPSS version 22 software was used for statistical analysis and a p value of < 0.05 was considered as statistically significant.

          Results

          Out of 406 sputum samples of participants 136(33.5%) were culture positive for 142 bacterial isolates. Klebsiella pneumoniae 36(25.4%) was the predominant isolate followed by Pseudomonas species 25(17.6%). Gram-negative bacteria were sensitive to cefepime (86.0%) and ciprofloxacin (77.8%) antibiotics while gram-positive (76.5%) to clindamycin.

          Conclusion

          Community acquired lower respiratory tract Infection was highly prevalent in the study area and the isolates showed resistant to common antibiotics such as ampicillin, augmentin, ceftazidime and tetracycline. Therefore, culture and susceptibility test is vital for appropriate management of lower respiratory tract infection in the study area.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12879-021-06151-2.

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          Most cited references30

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          Purposeful selection of variables in logistic regression

          Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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            District Laboratory Practice in Tropical Countries

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              Pneumonia in the developing world: Characteristic features and approach to management

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                Author and article information

                Contributors
                moges22@yahoo.com
                Journal
                BMC Infect Dis
                BMC Infect Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                13 May 2021
                13 May 2021
                2021
                : 21
                : 440
                Affiliations
                GRID grid.192268.6, ISNI 0000 0000 8953 2273, Hawassa University College of Medicine and Health Science, ; Hawassa, Ethiopia
                Article
                6151
                10.1186/s12879-021-06151-2
                8120775
                33985445
                0e8ebdbd-87db-42a6-9a1a-e996b62f343a
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 31 October 2020
                : 6 May 2021
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Infectious disease & Microbiology
                lower respiratory tract infection,culture-positive,antimicrobial susceptibility test

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