Dataset Information

Acinetobacter baumannii strains isolated from patients in intensive care units in Goiania, Brazil: Molecular and drug susceptibility profiles.

ABSTRACT: Resistance to antimicrobial agents is increasing worldwide and imposes significant life-threatening risks to several different populations, especially those in intensive care units (ICUs). Bacteria can quickly develop or acquire resistance to antimicrobial drugs, and combined with their intrinsic potential to cause disease in humans, these bacteria can become deadly. Among Gram-negative bacteria, Acinetobacter baumannii is notorious as a frequent opportunistic pathogen associated with critically ill patients, and understanding the genetic basis of A. baumannii resistance to beta-lactams among patients in ICUs will result in better protocols to prevent the development of resistance as well as improved treatment regimens. In this study, we assessed 1333 patients in five ICUs, 56 of whom developed A. baumannii infections. Most of the A. baumannii isolates were resistant to beta-lactam antimicrobial drugs, specifically, 3rd- and 4th-generation cephalosporins and carbapenems, and 91.1% of the isolates were multi-drug resistant (MDR). The most frequent OXA gene present was OXA-23 (55.1%), which is significantly associated with MDR strains. Most of the A. baumannii isolates (76.8%) were capable of forming a biofilm. The antimicrobial drug classes that were effective against most of these isolates were polymyxins and tigecycline. The molecular profile of the isolates allowed detection of 12 different clusters comprising 2 to 8 isolates each. In conclusion, our data indicate a high incidence of resistance to carbapenems as well as MDR strains among the observed A. baumannii isolates, most of which exhibited a high prevalence of OXA-23 gene expression. Only a few selective drugs were effective, reinforcing the notion that bacterial resistance is an emerging problem that should be prioritized in every healthcare facility.

SUBMITTER: Castilho SRA

PROVIDER: S-EPMC5419545 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Acinetobacter baumannii strains isolated from patients in intensive care units in Goiânia, Brazil: Molecular and drug susceptibility profiles.

Castilho Suellen Rocha Araújo SRA Godoy Cássia Silva de Miranda CSM Guilarde Adriana Oliveira AO Cardoso Juliana Lamaro JL André Maria Cláudia Porfirio MCP Junqueira-Kipnis Ana Paula AP Kipnis André A

PloS one 20170505 5

Resistance to antimicrobial agents is increasing worldwide and imposes significant life-threatening risks to several different populations, especially those in intensive care units (ICUs). Bacteria can quickly develop or acquire resistance to antimicrobial drugs, and combined with their intrinsic potential to cause disease in humans, these bacteria can become deadly. Among Gram-negative bacteria, Acinetobacter baumannii is notorious as a frequent opportunistic pathogen associated with critically ...[more]

PMID: 28475585

Similar Datasets

Project description:Little is known about the transmission dynamics of Acinetobacter baumannii in hospitals, despite such information being critical for designing effective infection control measures. In the absence of comprehensive epidemiological data, mathematical modelling is an attractive approach to understanding transmission process. The statistical challenge in estimating transmission parameters from infection data arises from the fact that most patients are colonised asymptomatically and therefore the transmission process is not fully observed. Hidden Markov models (HMMs) can overcome this problem. We developed a continuous-time structured HMM to characterise the transmission dynamics, and to quantify the relative importance of different acquisition sources of A. baumannii in intensive care units (ICUs) in three hospitals in Melbourne, Australia. The hidden states were the total number of patients colonised with A. baumannii (both detected and undetected). The model input was monthly incidence data of the number of detected colonised patients (observations). A Bayesian framework with Markov chain Monte Carlo algorithm was used for parameter estimations. We estimated that 96-98% of acquisition in Hospital 1 and 3 was due to cross-transmission between patients; whereas most colonisation in Hospital 2 was due to other sources (sporadic acquisition). On average, it takes 20 and 31 days for each susceptible individual in Hospital 1 and Hospital 3 to become colonised as a result of cross-transmission, respectively; whereas it takes 17 days to observe one new colonisation from sporadic acquisition in Hospital 2. The basic reproduction ratio (R0) for Hospital 1, 2 and 3 was 1.5, 0.02 and 1.6, respectively. Our study is the first to characterise the transmission dynamics of A. baumannii using mathematical modelling. We showed that HMMs can be applied to sparse hospital infection data to estimate transmission parameters despite unobserved events and imperfect detection of the organism. Our results highlight the need to optimise infection control in ICUs.

Dataset Information

Acinetobacter baumannii strains isolated from patients in intensive care units in Goiania, Brazil: Molecular and drug susceptibility profiles.

Publications

Acinetobacter baumannii strains isolated from patients in intensive care units in Goiânia, Brazil: Molecular and drug susceptibility profiles.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets