scholarly journals Using Machine Learning to Predict Antimicrobial Resistance of Acinetobacter Baumannii, Klebsiella Pneumoniae and Pseudomonas Aeruginosa Strains

Author(s):  
Georgios Feretzakis ◽  
Aikaterini Sakagianni ◽  
Evangelos Loupelis ◽  
Dimitris Kalles ◽  
Maria Martsoukou ◽  
...  

Hospital-acquired infections, particularly in ICU, are becoming more frequent in recent years, with the most serious of them being Gram-negative bacterial infections. Among them, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa are considered the most resistant bacteria encountered in ICU and other wards. Given the fact that about 24 hours are usually required to perform common antibiotic resistance tests after the bacteria identification, the use of machine learning techniques could be an additional decision support tool in selecting empirical antibiotic treatment based on the sample type, bacteria, and patient’s basic characteristics. In this article, five machine learning (ML) models were evaluated to predict antimicrobial resistance of Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. We suggest implementing ML techniques to forecast antibiotic resistance using data from the clinical microbiology laboratory, available in the Laboratory Information System (LIS).

2021 ◽  
Vol 24 (2) ◽  
pp. 83-86
Author(s):  
Lucian Giubelan ◽  

Objectives. Classification on multiple criteria of Gram-negative bacilli (GNBs) according to antibiotic resistance. Material and method. Retrospective study (January 2017-December 2018) carried out in the Infectious Diseases Clinic from Craiova; GNBs were identified using the Vitek 2 automated system, which subsequently established their sensitivity to antimicrobials; GNBs were classified based on an arbitrary score from 1 (minimum) to 5 (maximum) based on the multiple antibiotic resistance index (MAR), the percentage of multidrug resistant strains (MDR) and the percentage of extended resistance strains (XDR). The final classification represents the sum of the points awarded for each category considered. Results. The following GNBs were considered: Escherichia coli (n = 720), Klebsiella pneumoniae (n = 335), Pseudomonas aeruginosa (n = 139), Proteus mirabilis (n = 60) and Acinetobacter baumannii (n = 29). MAR values are: Acinetobacter baumannii (Ab) – 0.6, Proteus mirabilis (Pm) – 0.52, Pseudomonas aeruginosa (Pa) – 0.51, Klebsiella pneumoniae (Kp) - 0.37 and Escherichia coli (Ec) – 0.23. The percentage of MDR strains is: Pm – 76.67%, Kp – 68.86%, Pa - 58.71%, Ec – 51.94% and Ab – 51.72%; XDR strains were identified for Ab - 17.24% and Pa – 6.47%. The final classification of GNBs is as follows: Pa – 12p, Ab - 11 p, Pm – 7p, Kp – 6p, Ec – 3p. Conclusions. Depending on the resistance profile on multiple criteria, the classification of the studied Gram-negative bacteria is as follows: Pa, Ab, Pm, Kp, Ec.


2007 ◽  
Vol 60 (1) ◽  
pp. 78-82 ◽  
Author(s):  
David Landman ◽  
Simona Bratu ◽  
Sandeep Kochar ◽  
Monica Panwar ◽  
Manoj Trehan ◽  
...  

Antibiotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 62 ◽  
Author(s):  
Georgios Feretzakis ◽  
Evangelos Loupelis ◽  
Aikaterini Sakagianni ◽  
Nikoletta Skarmoutsou ◽  
Sophia Michelidou ◽  
...  

Hospital-acquired infections, particularly in the critical care setting, are becoming 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. As treatment options become limited, antimicrobial stewardship programs aim to optimize the appropriate use of currently available antimicrobial agents and decrease hospital costs. Pseudomonas aeruginosa, Acinetobacter baumannii and Klebsiella pneumoniae are the most common resistant bacteria encountered in intensive care units (ICUs) and other wards. To establish preventive measures, it is important to know the prevalence of Gram-negative isolated bacteria and antibiotic resistance profiles in each ward separately, compared with ICUs. In our single centre study, we compared the resistance levels per antibiotic of P. aeruginosa, A. baumannii and K.pneumoniae clinical strains between the ICU and other facilities during a 2-year period in one of the largest public tertiary hospitals in Greece. The analysis revealed a statistically significant higher antibiotic resistance of the three bacteria in the ICU isolates compared with those from other wards. ICU strains of P. aeruginosa presented the highest resistance rates to gentamycin (57.97%) and cefepime (56.67%), followed by fluoroquinolones (55.11%) and carbapenems (55.02%), while a sensitivity rate of 97.41% was reported to colistin. A high resistance rate of over 80% of A. baumannii isolates to most classes of antibiotics was identified in both the ICU environment and regular wards, with the lowest resistance rates reported to colistin (53.37% in ICU versus an average value of 31.40% in the wards). Statistically significant higher levels of resistance to most antibiotics were noted in ICU isolates of K. pneumoniae compared with non-ICU isolates, with the highest difference—up to 48.86%—reported to carbapenems. The maximum overall antibiotic resistance in our ICU was reported for Acinetobacter spp. (93.00%), followed by Klebsiella spp. (72.30%) and Pseudomonas spp. (49.03%).


2019 ◽  
Author(s):  
Ariane Khaledi ◽  
Aaron Weimann ◽  
Monika Schniederjans ◽  
Ehsaneddin Asgari ◽  
Tzu-Hao Kuo ◽  
...  

AbstractThe growing importance of antibiotic resistance on clinical outcomes and cost of care underscores the need for optimization of current diagnostics. For a number of bacterial species antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and gene expression profiles, we generated predictive models and identified biomarkers of susceptibility or resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8-0.9) or very high (>0.9) sensitivity and predictive values, where the relative contribution of the different categories of biomarkers strongly depended on the antibiotic. For all drugs except for ciprofloxacin, gene expression information substantially improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. The implementation of a molecular susceptibility test system in routine clinical microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.


Author(s):  
Huda Zaid Al-Shami ◽  
Muhamed Ahmed Al-Haimi ◽  
Omar Ahmed Esma’il Al-dossary ◽  
Abeer Abdulmahmood Mohamed Nasher ◽  
Mohammed Mohammed Ali Al-Najhi ◽  
...  

Background and objectives: At the present time, antimicrobial resistance (AMR) is a major public health hazard, with antimicrobial resistance bacteria increasing exponentially. This study estimates the epidemiological profiles and antimicrobial resistance of Gram-positive bacteria (GPB) and Gram-negative bacteria (GNB)  isolated from clinical samples among patients admitted to two University hospitals in Sana'a city for one year (2019). Methods: This was a retrospective study of clinical samples of patients collected from January 1, 2019 to December 30, 2019. All samples were appraised to determine presence of infectious agents using standard methods for isolation and identification of bacteria and yeasts from clinical samples of patients admitted to Al-Gumhouri University Hospital and Al-Kuwait University Hospital in Sana'a city. Antibiotic resistance was done using Kirby-Bauer disc diffusion methods. Results:  2,931 different pathogenic bacteria were detected from 24,690 different clinical specimens. The samples had an overall detection rate of 11.9% (2931/24,690). Among the bacterial pathogens isolated from clinical samples, 52.4% (n=1536) had GPB and 41.2% (n=1207) had GNB. The predominant GNB isolates were E.coli (22.04%), Klebsiella spp (6.03%), Pseudomonas aeruginosa (7.1%), Acinetobacter baumannii (1.46%), Enterobacter spp. (1.09%), Citrobacter spp. (1.16%), respectively. Among the GPB, S.aureus was the most common (26.3%), Coagulase-negative Staphylococcus (8.1%), Non-hemolytic Streptococcus (9.1%), Other alpha-hemolytic Streptococcus (3.9%), Streptococcus pyogenes (1.9%), and Streptococcus pneumoniae (0.5% ). A high rate of antibiotic resistance was recorded for sulfamethoxazole/trimethoprim (85.5%), ceftazidime (81.07%), ampicillin (70.4%), cefuroxime (66.4%). Conclusions:  The current study results revealed that the rate of resistance between GNB and GPB is associated with the incidence of different infections in patients attending two major tertiary hospitals in Sana'a city is very high. These results indicate ongoing screening and follow-up programs to detect antibiotic resistance, and also suggest the development of antimicrobial stewardship programs in Sana'a, Yemen.                     Peer Review History: Received: 9 September 2021; Revised: 11 October; Accepted: 23 October, Available online: 15 November 2021 Academic Editor:  Dr. A.A. Mgbahurike, University of Port Harcourt, Nigeria, [email protected] UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main purpose of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency.  Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 6.0/10 Average Peer review marks at publication stage: 7.5/10 Reviewers: Rima Benatoui, Laboratory of Applied Neuroendocrinology, Department of Biology, Faculty of Science, Badji Mokhtar University Annaba, BP12 E L Hadjar–Algeria, [email protected] Dr. Wadhah Hassan Ali Edrees, Hajja University, Yemen, [email protected] Rola Jadallah, Arab American University, Palestine, [email protected] Similar Articles: PREVALENCE OF PSEUDOMONAS AERUGINOSA (P. AERUGINOSA) AND ANTIMICROBIAL SUSCEPTIBILITY PATTERNS AT A PRIVATE HOSPITAL IN SANA'A, YEMEN EVALUATION OF ANTIBACTERIAL RESISTANCE OF BIOFILM FORMS OF AVIAN SALMONELLA GALLINARUM TO FLUOROQUINOLONES


2015 ◽  
Vol 1 (3) ◽  
pp. 11
Author(s):  
Marcos André Siqueira de Sousa ◽  
Thays Rezende Lima ◽  
Alvaro Francisco Lopes de Sousa ◽  
Marcelo de Moura Carvalho ◽  
Giselle Mary Ibiapina Brito ◽  
...  

Objetivo: identificar a prevalência de infecção da corrente sanguínea em idosos internados em um clinica cirúrgica de um Hospital Geral. Metodologia: Trata-se de um estudo epidemiológico, retrospectivo, descritivo com abordagem quantitativa. A amostra constou de 68 pacientes internados no ano de 2013 em um Hospital de referência e ensino de Teresina-PI. Os dados foram analisados pelo SPSS Versão 10.0 e o projeto de pesquisa foi aprovado pelo Comitê de Ética em Pesquisa da Universidade Federal do Piauí (CAAE:18110614.10000.5214). Resultados: Dos 68 pacientes diagnosticados com cultura positiva pra ICS a prevalência de idosos(60 anos ou mais) foi de 49%. Houve predominância do sexo feminino (58%) e estado civil casado (43%). Os microrganismos mais prevalentes foram Acinetobacter baumannii (23,5%), Klebsiella pneumoniae (19,65), Pseudomonas aeruginosa (19,05%) e Staphylococcus coagulase-negativo(17,3%). Conclusão: A prevalência de ICS elevada revela a necessidade de se avaliar medidas de prevenção para esta faixa etária.


Author(s):  
I. I. Myrko ◽  
T. I. Chaban ◽  
V. V. Ogurtsov ◽  
V. S. Matiychuk

Мета роботи. Здійснити синтез деяких нових піразолзаміщених 7H-[1,2,4]триазоло[3,4-b][1,3,4]тіадіазинів та провести дослідження антимікробних властивостей синтезованих сполук. Матеріали і методи. Органічний синтез, ЯМР-спектроскопія, елементний аналіз, фармакологічний скринінг. Результати й обговорення. У результаті взаємодії eтил (2Z)-хлоро(фенілгідразоно)ацетатів з ацетилацетоном було отримано етил 4-ацетил-5-метил-1-феніл-1H-піразол-3-карбоксилати. Зазначені сполуки піддали бромуванню, що дозволило одержати цільові бромкетони. Синтезовані на даній стадії етил 1-арил-4-(бромацетил)-5-метил-1Н-піразол-3-карбоксилати було введено у взаємодію з 4-аміно-5-арил(гетарил)-2,4-дигідро-3Н-1,2,4-триазол-3-тіонами з подальшим формуванням 1,3,4-тіадіазольного циклу та отриманням відповідних етил 1-арил-4-{3-арил(гетарил)-7H-[1,2,4]триазоло[3,4-b][1,3,4]тіадіазин-6-іл)}-5-метил-1H-піразол-3-карбоксилатів. Структура синтезованих сполук підтверджена даними елементного аналізу та ЯМР спектроскопією. В рамках міжнародного проекту "The Community for Antimicrobial Drug Discovery" (CO-ADD) за підтримки Wellcome Trust (Великобританія) і університету Квінсленда (Австралія) для синтезованих сполук здійснено скринінг антимікробної активності. Як тестові мікроорганізми використовували п'ять штамів бактерій: Escherichia coli ATCC 25922, Klebsiella pneumoniae ATCC 700603, Acinetobacter baumannii ATCC 19606, Pseudomonas aeruginosa ATCC 27853, Staphylococcus aureus ATCC 43300 та двох штамів грибків: Candida albicans ATCC 90028 і Cryptococcus neoformans ATCC 208821. Встановлено, що досліджувані сполуки виявляють різноманітну дію, від практично повної її відсутності до виразного антимікробного ефекту. Висновки. Здійснено синтез 12 нових етил 1-арил-4-{3-арил(гетарил)-7H-[1,2,4]триазоло[3,4-b][1,3,4]тіадіазин-6-іл)}-5-метил-1H-піразол-3-карбоксилатів. Зазначені речовини отримані шляхом взаємодії відповідних етил 1-арил-4-(бромацетил)-5-метил-1Н-піразол-3-карбоксилатів з 4-аміно-5-арил(гетарил)-2,4-дигідро-3Н-1,2,4-триазол-3-тіонами. Дослідження антимікробної активності синтезованих сполук демонструють потенціал пошуку антимікробних агентів серед зазначеного класу сполук.


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