Dataset Information

Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

ABSTRACT:

Background

We developed a clinical bedside tool to simultaneously estimate the probabilities of third-generation cephalosporin-resistant Enterobacteriaceae (3GC-R), carbapenem-resistant Enterobacteriaceae (CRE), and multidrug-resistant Pseudomonas aeruginosa (MDRP) among hospitalized adult patients with Gram-negative infections.

Methods

Data were obtained from a retrospective observational study of the Premier Hospital that included hospitalized adult patients with a complicated urinary tract infection (cUTI), complicated intra-abdominal infection (cIAI), hospital-acquired/ventilator-associated pneumonia (HAP/VAP), or bloodstream infection (BSI) due to Gram-negative bacteria between 2011 and 2015. Risk factors for 3GC-R, CRE, and MDRP were ascertained by multivariate logistic regression, and separate models were developed for patients with community-acquired versus hospital-acquired infections for each resistance phenotype (N?=?6). Models were converted to a singular user-friendly interface to estimate the probabilities of a patient having an infection due to 3GC-R, CRE, or MDRP when???1 risk factor was present.

Results

Overall, 124,068 patients contributed to the dataset. Percentages of patients admitted for cUTI, cIAI, HAP/VAP, and BSI were 61.6, 4.6, 16.5, and 26.4%, respectively (some patients contributed >?1 infection type). Resistant infection rates were 1.90% for CRE, 12.09% for 3GC-R, and 3.91% for MDRP. A greater percentage of the resistant infections were community-acquired relative to hospital-acquired (CRE, 1.30% vs 0.62% of 1.90%; 3GC-R, 9.27% vs 3.42% of 12.09%; MDRP, 2.39% vs 1.59% of 3.91%). The most important predictors of having an 3GC-R, CRE or MDRP infection were prior number of antibiotics; infection site; infection during the previous 3?months; and hospital prevalence of 3GC-R, CRE, or MDRP. To enable application of the six predictive multivariate logistic regression models to real-world clinical practice, we developed a user-friendly interface that estimates the risk of 3GC-R, CRE, and MDRP simultaneously in a given patient with a Gram-negative infection based on their risk (Additional file 1).

Conclusions

We developed a clinical prediction tool to estimate the probabilities of 3GC-R, CRE, and MDRP among hospitalized adult patients with confirmed community- and hospital-acquired Gram-negative infections. Our predictive model has been implemented as a user-friendly bedside tool for use by clinicians/healthcare professionals to predict the probability of resistant infections in individual patients, to guide early appropriate therapy.

SUBMITTER: Lodise TP

PROVIDER: S-EPMC6694572 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

Lodise Thomas P TP Bonine Nicole Gidaya NG Ye Jiatao Michael JM Folse Henry J HJ Gillard Patrick P

BMC infectious diseases 20190814 1

<h4>Background</h4>We developed a clinical bedside tool to simultaneously estimate the probabilities of third-generation cephalosporin-resistant Enterobacteriaceae (3GC-R), carbapenem-resistant Enterobacteriaceae (CRE), and multidrug-resistant Pseudomonas aeruginosa (MDRP) among hospitalized adult patients with Gram-negative infections.<h4>Methods</h4>Data were obtained from a retrospective observational study of the Premier Hospital that included hospitalized adult patients with a complicated u ...[more]

PMID: 31412809

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Project description:Purpose:Carbapenems are considered the most efficient antibiotic used in the treatment of nosocomial infections. Carbapenem-resistant Gram-negative rods are becoming a serious hazard in hospitals threatening public health. The aim of the current study was to investigate the prevalence of carbapenem-resistant Gram-negative pathogens incriminated in healthcare-associated infections, along with antimicrobial resistance profiles, carbapenemase and metallo-?-lactamase production, and their molecular characterization. Methods:A total of 186 clinical specimens were collected from 133 patients at various hospitals in Cairo, Egypt. The obtained specimens were subjected to bacteriological examination, antimicrobial susceptibility testing, detection of carbapenemase production using the modified Hodge test (MHT), the metallo-?-lactamase production using the EDTA combined disc test (CDT), and PCR-based detection of the bla KPC and bla GES resistance genes. The identification of the highly resistant retrieved isolates was then confirmed by 16S rRNA gene sequencing. Results:The most common isolated Gram-negative species was Klebsiella pneumoniae (40.9%), followed by Acinetobacter baumannii (18.8%), Pseudomonas aeruginosa (17.3%), Escherichia coli (15.4%), Enterobacter aerogenes (5.3%), and Proteus mirabilis (2.4%). The prevalence of carbapenem-resistant isolates was 36.1% (n=75). However, 86.5% of the recovered clinical isolates were susceptible to colistin. The MHT revealed that 33.6% (n=70) of the tested strains were positive for carbapenemase production, while the CDT showed that 33.17% (n=69) of the examined strains were metallo-?-lactamase producers. The PCR revealed that 98.6% (74/75) of the tested strains possessed the bla KPC gene; moreover, 97.3% (73/75) of the examined strains harbored the bla GES gene. Conclusion:This study displayed the emergence of carbapenem-resistant Gram-negative pathogens incriminated in healthcare-associated infections. The accurate identification of carbapenem-resistant bacterial pathogens is pivotal for the treatment of patients, in addition to propelling appropriate contamination control measures to restrain the fast spread of such pathogens. Colistin showed a potent in vitro antimicrobial activity against the carbapenem-resistant strains.

Project description:PurposeMetallo β-lactamases (MβL) production is a worldwide problem, particularly in gram-negative bacteria. As scanty data is available on the prevalence of MBL, the present study is being undertaken to determine the prevalence, antibacterial sensitivity patterns, and molecular characterization of MβL associated resistant genes in gram-negative bacteria isolated from ocular infections.Material and methodsAt a tertiary eye care center in south India, 359 gram-negative pathogens, 200 isolates from eye infections, and 159 isolates from normal flora of the eye were studied. A gold standard microbiology method was used to identify the isolates. An antibiotic double disc synergy test and a combination disc test were used to detect MβL production. Multiplex PCR was used to investigate the molecular characteristics of the MβL encoding genes bla VIM, bla IMP, and bla NDM.ResultsOf the 359 gram-negative bacterial pathogens, Pseudomonas aeruginosa 108 (30.1%) and Enterobacter agglomerans 46 (12.8%) were commonly isolated. High prevalence of P. aeruginosa 81% (17 strains) was detected as an MβL producer and it shows 100% resistance to 2nd and 3rd generation cephalosporins and meropenem. Multiplex PCR detected only the bla VIM gene in 56 (28%) of various eye infections and 27 (17%) of normal flora of the gram-negative bacteria (GNB). The bla VIM gene is detected predominantly in 51.8% of keratitis and 21.4% of postoperative endophthalmitis. High prevalence of the gene was detected in P. aeruginosa 42.9% (24 of 56) and Alcaligens denitrificans 10.7% (6 of 56) from eye infections. Whereas, in the control group, P. aeruginosa and E. coli each had 14.8% (4 of 27) that were shown positive.ConclusionThe emerging MβLs mediated resistance among P. aeruginosa is a challenging task for ophthalmologists, especially in patients with endophthalmitis and bacterial keratitis. This local knowledge will aid in advising appropriate antibiotic use and avoiding unnecessary antibiotic prescriptions, which are highly warranted.

Dataset Information

Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

Background

Methods

Results

Conclusions

Publications

Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

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