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Showing 3 results for Nosocomial Infection
Contamination Of Computer Keyboards In Various Wards Of Vali-e Asr Teaching Hospital In Birjand, Iran
Mohammad Hasan Namaei, Sima Surgi, Hoda Khoshbakht, Nahid Askari, Seyed Alireza Javadinia,
Volume 5, Issue 5 (3-2012)
Abstract

Background and Aim: The aim of this study was to evaluate bacterial contamination of keyboards of computers located in various wards of Vali-e Asr Teaching Hospital, Birjand, Iran.

Materials and Methods: In this study, all computer keyboards in various wards of Vali-e Asr Hospital were sampled (n=24). Then, the samples were sent to Microbiology Research Laboratory at Birjand University of Medical Sciences and were cultured on Blood ager, Manitol Salt ager and Eosin Methylene Blue media. The isolated bacteria were identified based on their colonial morphology and biochemical characteristics.

Results: A total of 26 samples from 24 different computer keyboards of 16 different wards were obtained. Two keyboards of Infectious Diseases and Neurology wards were routinely disinfected at the end of every shift. All samples(100%) showed contamination to different bacteria. The keyboard of the computer located in Internal Medicine ward(women's division) was the most contaminated one. In total, 13 different bacterial spp. were isolated from keyboards of different computers. The species belonging to Enterobacteriaceae family(61.5%) were the most common contaminating bacteria followed by Bacillus spp(30.7%).

Conclusion: Based on the results, all the sampled keyboards were contaminated by at least one bacterial spp. Therefore, it is necessary to pay more attention to the fact that computer keyboards in hospitals should regularly be disinfected.


Comparing E-learning and Lecture-Based Education in Control of Nosocomial Infections
Mina Sadat Hashemiparast, Roya Sadeghi, Mohammadreza Ghaneapur , Kamal Azam , Azar Tol ,
Volume 10, Issue 3 (7-2016)
Abstract

Background and Aim: Effective educational programs, is one of the most basic methods in prevention of Nosocomial infection. This study aimed to compare the effects of E-learning versus lecture-based education in prevention of Nosocomial infections among hospital staffs.

Materials and Methods: A randomized pre and posttest control group design was conducted on 98 hospital staffs in 2013 after allocating into two groups of "lecture-based education" and "E-learning”. Data were collected by a researcher-made questionnaire which its validity and reliability was confirmed by a pilot study. Wilcoxon, Paired and Independent sample T-test was conducted using SPSS, version18.

Results: There was a significant difference for outcomes before and after education based on two approach of lecture-based (p=0.01) and E-learning (p=0.01).The mean and standard deviation of knowledge in lecture-based education and E-learning group were 12.73± 2.76, 11.50 ± 2.64 respectively. The level of knowledge in the lecture group was significantly higher than that of participants in the E-learning group (p=0.02).

Conclusion: Despite the effectiveness of E-learning in learning and raising awareness of the learners, using of this method among health-related organizations need to empower employees, remove the barriers and suitable infrastructure.


Prediction of Sepsis Due to Acinetobacter Infection in Neonates Admitted to NICU
Niloofar Mohammadzadeh, Ziba Mosayebi, Hamid Beigy, Mohammad Shojaeinia,
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Sepsis is the most important disease in the first 28 days of life and one of the main causes of infant mortality in the intensive care unit. Its definitive diagnosis is possible by performing blood culture. Neonatal sepsis can be a clinical sign of nosocomial infections that are often resistant to antibiotics. Therefore, the purpose of this study was to create and evaluate a hospital sepsis prediction model and present its results to health care providers.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.

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