scholarly journals Colonization by Antibiotic-Resistant Gram-Negative Bacteria and Appropriate Empirical Antibiotic Therapy in Intensive Care Unit Patients

2006 ◽  
Vol 27 (1) ◽  
pp. 104-104 ◽  
Author(s):  
Fernando Bellíssimo-Rodrigues ◽  
José Fernando de Castro Figueiredo ◽  
Roberto Martinez
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Antibiotic Therapy ◽  
Gram Negative Bacteria ◽  
Empirical Antibiotic Therapy ◽  
Antibiotic Resistant ◽  
Gram Negative

Colonization Status and Appropriate Antibiotic Therapy for Nosocomial Bacteremia Caused by Antibiotic-Resistant Gram-Negative Bacteria in an Intensive Care Unit

2005 ◽  
Vol 26 (6) ◽  
pp. 575-579 ◽  
Author(s):  
Stijn Blot ◽  
Pieter Depuydt ◽  
Dirk Vogelaers ◽  
Johan Decruyenaere ◽  
Jan De Waele ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Antibiotic Therapy ◽  
Empiric Antibiotic Therapy ◽  
Gram Negative Bacteria ◽  
Antibiotic Resistant ◽  
Gram Negative ◽  
Nosocomial Bacteremia ◽  
Appropriate Therapy ◽  
Colonization Status

AbstractObjective:Timely initiation of antibiotic therapy is crucial for severe infection. Appropriate antibiotic therapy is often delayed for nosocomial infections caused by antibiotic-resistant bacteria. The relationship between knowledge of colonization caused by antibiotic-resistant gram-negative bacteria (ABR-GNB) and rate of appropriate initial antibiotic therapy for subsequent bacteremia was evaluated.Design:Retrospective cohort study.Setting:Fifty-four-bed intensive care unit (ICU) of a university hospital. In this unit, colonization surveillance is performed through routine site-specific surveillance cultures (urine, mouth, trachea, and anus). Additional cultures are performed when presumed clinically relevant.Patients:ICU patients with nosocomial bacteremia caused by ABR-GNB.Results:Infectious and microbiological characteristics and rates of appropriate antibiotic therapy were compared between patients with and without colonization prior to bacteremia. Prior colonization was defined as the presence (detected ≥ 2 days before the onset of bacteremia) of the same ABR-GNB in colonization and subsequent blood cultures. During the study period, 157 episodes of bacteremia caused by ABR-GNB were suitable for evaluation. One hundred seventeen episodes of bacteremia (74.5%) were preceded by colonization. Appropriate empiric antibiotic therapy (started within 24 hours) was administered for 74.4% of these episodes versus 55.0% of the episodes that occurred without prior colonization. Appropriate therapy was administered within 48 hours for all episodes preceded by colonization versus 90.0% of episodes without prior colonization.Conclusion:Knowledge of colonization status prior to infection is associated with higher rates of appropriate therapy for patients with bacteremia caused by ABR-GNB (Infect Control Hosp Epidemiol 2005;26:575-579).

scholarly journals Using Machine Learning Techniques to Aid Empirical Antibiotic Therapy Decisions in the Intensive Care Unit of a General Hospital in Greece

Antibiotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 50 ◽  
Author(s):  
Georgios Feretzakis ◽  
Evangelos Loupelis ◽  
Aikaterini Sakagianni ◽  
Dimitris Kalles ◽  
Maria Martsoukou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Antibiotic Therapy ◽  
Antibiotic Susceptibility ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
High Morbidity ◽  
Empirical Antibiotic Therapy ◽  
Gram Negative

Hospital-acquired infections, particularly in the critical care setting, have become increasingly common during the last decade, with Gram-negative bacterial infections presenting the highest incidence among them. Multi-drug-resistant (MDR) Gram-negative infections are associated with high morbidity and mortality with significant direct and indirect costs resulting from long hospitalization due to antibiotic failure. Time is critical to identifying bacteria and their resistance to antibiotics due to the critical health status of patients in the intensive care unit (ICU). As common antibiotic resistance tests require more than 24 h after the sample is collected to determine sensitivity in specific antibiotics, we suggest applying machine learning (ML) techniques to assist the clinician in determining whether bacteria are resistant to individual antimicrobials by knowing only a sample’s Gram stain, site of infection, and patient demographics. In our single center study, we compared the performance of eight machine learning algorithms to assess antibiotic susceptibility predictions. The demographic characteristics of the patients are considered for this study, as well as data from cultures and susceptibility testing. Applying machine learning algorithms to patient antimicrobial susceptibility data, readily available, solely from the Microbiology Laboratory without any of the patient’s clinical data, even in resource-limited hospital settings, can provide informative antibiotic susceptibility predictions to aid clinicians in selecting appropriate empirical antibiotic therapy. These strategies, when used as a decision support tool, have the potential to improve empiric therapy selection and reduce the antimicrobial resistance burden.

scholarly journals Antibiotic-Resistant Gram-negative Bacteria Carriage in Healthcare Workers Working in an Intensive Care Unit

2021 ◽  
Vol 53 ◽  
Author(s):  
Bich Thuy Duong ◽  
Minh Cuong Duong ◽  
James Campbell ◽  
Van Minh Hoang Nguyen ◽  
Huu Hien Nguyen ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Healthcare Workers ◽  
Gram Negative Bacteria ◽  
Antibiotic Resistant ◽  
Gram Negative

scholarly journals THE STUDY OF MULTIDRUG-RESISTANCE IN NEONATAL INTENSIVE CARE UNIT AT THE CENTRAL JAVA HOSPITAL

2017 ◽  
Vol 10 (14) ◽  
pp. 80 ◽  
Author(s):  
Ika Puspita Sari ◽  
Titik Nuryastuti ◽  
Djoko Wahyono
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Multidrug Resistance ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Intensive Care ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Gram Positive Bacteria ◽  
Central Java ◽  
Culture And Sensitivity

Objective: Multidrug-resistance (MDR) is defined as an acquired non-susceptibility to at least one agent in three or more antimicrobial categories. MDR can be caused by several factors, including the misuse of antibiotics.  Resistance to antibiotics still poses a global challenge, especially in Indonesia. This study aimed to identify patterns of MDR in Neonatal Intensive Care Unit (NICU) at the Central Java Hospital, during the period of January 2014 to December 2015.Methods: The study was conducted using a descriptive retrospective design. The research population comprised of 225 patients. Patient inclusion criteria were neonatal patients treated in NICU ward with infection diagnosis. All patients had culture and sensitivity examinations on their bloods. The culture and sensitivity examinations were performed by microbiology clinicians.Results: The most common infection type was sepsis (60%). The most common bacteria found in the blood specimen of patients in the NICU ward was Gram-negative bacteria with a 72% rate, the other was Gram-positive bacteria. Bacteria which infected patients include; Klebsiellapneumoniaessppneumoniae, Pseudomonas aeruginosa, Bulkholderiacepacia, Acinetobacterbaumannii, Enterobactercloacae ssp cloacae, Serratiamarcescens, Staphylococcus haemolyticusand Staphylococcus epidermidis. The research result showed that 97.8% MDR cases were reported in the NICU ward. Antibiotics which were still potent for all bacteria found in NICU patients were tigecycline, meropenem and ciprofloxacin (for Gram-negative bacteria) and tigecycline, linezolid, nitrofurantoin, moxifloksacin and vancomycin (for Gram-positive bacteria).Conclusion: A high percentage of MDR occurred in NICU patients. Sepsis is the most common diagnosis in NICU patients. The usage of third generation antibiotics should be limited and regulated systematically.   

scholarly journals PATIENTS' MICROFLORA COMPARATIVE CHARACTERISTICS OF DIFFERENT DEPARTMENTS AT THE NATIONAL HOSPITAL OF PEDIATRICS IN HANOI, VIETNAM

2019 ◽  
pp. 43-48
Author(s):  
L.V. Kataeva ◽  
A.P. Rebeshchenko ◽  
T.F. Stepanova ◽  
O.V. Posoiuznykh ◽  
Le Thanh Hai ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Infectious Diseases ◽  
Hospital Environment ◽  
Clinical Samples ◽  
Gram Negative Bacteria ◽  
National Hospital ◽  
Statistical Research ◽  
Gram Positive ◽  
Gram Negative

We studied the microflora structure and resistance gathered from the biomaterial of patients and the environment objects of various departments at the National hospital of Pediatrics in Hanoi. 140 clinical samples of biomaterials from 74 patients treated in the intensive care unit, the infectious diseases and the gastroenterology departments were studied. A systematic approach including microbiological, epidemiological and statistical research methods was used in carrying out the study. Bacteria of the Enterobacteriaceae family (38.5 per cent) prevailed in the biomaterial of intensive care unit patients. Nonfermentative Gram-negative bacteria (46.5 per cent) occupied the leading positions in the infectious diseases department and Gram-positive bacteria (39.3 per cent) were in the gastroenterology department. Gram-positive flora (60.2 per cent in the intensive care unit and 50.7 per cent in the infectious diseases department) prevailed in the microflora structure gathered from hospital environment objects. We identified the prevalence of bacteria of the genus Enterobacteriaceae and non-fermentative Gram-negative bacteria with a wide spectrum of resistance in the departments of the National Hospital of Pediatrics.

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