scholarly journals Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yi Li ◽  
Hui Shen ◽  
Cheng Zhu ◽  
Yuetian Yu
Keyword(s):  
Risk Factors ◽  
Antimicrobial Resistance ◽  
Klebsiella Pneumoniae ◽  
Prediction Model ◽  
Resistance Gene ◽  
Characteristic Curve ◽  
Central China ◽  
Icu Admission ◽  
Carbapenem Resistant ◽  
Antimicrobial Resistance Gene

Objective. To investigate the prevalence of infections due to carbapenem-resistant Klebsiella pneumoniae (CRKP) among ICU admission patients in central China and develop a reliable prediction model. Methods. Five hundred and seven consecutive ICU admission patients with Klebsiella pneumoniae (KP) infection were enrolled in this retrospective multicenter case-control study from January 2014 to June 2018. The prevalence and antimicrobial susceptibility pattern were analyzed. Multivariate analysis was performed by logistic regression modeling to determine the risk factors. A prediction model was developed and verified using data from six hospitals in central China. Results. Of the total 507 isolates of KP, 244 (48.1%) strains were carbapenem resistant. The majority of these isolates were from sputum (30.9%) and blood (20.9%) samples. Tigecycline had good activity against CRKP (95.5%). The most common sequence type (ST) of CRKP was ST11 (84.4%), and 98.6% of them had the blaKPC-2 antimicrobial resistance gene. Thirteen variables were identified as independent risk factors for CRKP infection, including KP colonization or infection in the preceding year (OR=3.32, 95% CI 2.01-4.38), CD4/CD8 ratio <1 (OR=2.98, 95% CI 2.02-4.19), and parenteral nutrition ⩾48 h (OR=1.88, 95% CI 1.22-3.04). The model developed to predict CRKP infection was effective, with an area under the receiver-operating characteristic curve of 0.854 (95% CI 0.821-0.884, p<0.001). Conclusions. ST11 carrying the blaKPC-2 antimicrobial resistance gene was the most common type of CRKP among the ICU admission patients in central China. The model demonstrated excellent predictive performance and exhibited good discrimination.

scholarly journals Carbapenem-Resistant Klebsiella Pneumoniae  in Southwest China: Molecular Characterizations and Risk Factors Caused by NDM and KPC Producers

2021 ◽  
Author(s):  
Zhaoyinqian Li ◽  
Zixuan Ding ◽  
Jia Yang ◽  
Yao Liu ◽  
Xinrui Jin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Klebsiella Pneumoniae ◽  
Resistance Gene ◽  
Southwest China ◽  
Gene Cassettes ◽  
Conserved Regions ◽  
Carbapenem Resistant ◽  
Extended Spectrum ◽  
Synergy Test ◽  
Epidemiological Characteristics

Abstract Background: Klebsiella pneumoniae is one of the most common Enterobacteriaceae. In recent years, carbapenem-resistant Klebsiella pneumoniae (CRKP) has become one of the most important carbapenem-resistant Enterobacteriaceae. CRKP are usually resistant to antibiotics. Up to this day, the emergence of carbapenemase-producing K. pneumoniae has been a challenge for treatment of clinical infection.Methods: (i) 66 non-repetitive clinical CRKP isolates were identified by matrix-assisted laser analytical ionization time-of-flight mass spectrometer (MALDI-TOF-MS) and drug sensitivity analysis was performed by Vitek2 Compact. EDTA-synergy test and mCIM / eCIM test were used to detect drug-resistant phenotypes. (ii) Carbapenemase genes, extended-spectrum β-lactamase genes (ESBLs), cephalosporinase gene (AmpC), virulence genes, integron and resistance gene cassettes were amplified by PCR. (iii) Plasmid typing was performed by plasmid conjugation assay and PCR-based replicon typing (PBRT) method. (iv) The genetic environments of KPC-2 and NDM-1 were analyzed by using overlapping PCR. (v) MLST was used to analyze the molecular epidemiological characteristics of CRKP. (vi) Risk factors of CRKP infection by logistic regression model.Results: Our study revealed that 42 of the 66 CRKP isolates obtained from patients were identified as blaKPC-2, 24 blaNDM-1-positive strains were identified (20 blaNDM-1 and 4 blaNDM-5), of which 18 were from the neonatal departments. And CRKP strains were ESBL (extended-spectrum β-lactamases) and AmpC enzymes producer, Notably, we found two CR-hvKp (carbapenem-resistant hypervirulent klebsiella pneumoniae) strains, which contains blaKPC-2 gene and other resistant genes. Two of the 42 KPC-2-producing CRKP strains were positive for transconjugants, and the plasmid typing was the IncFII type. And two NDM-producing CRKP strains tested positive for transconjugants, which belonged to the lncX3 plasmid. Analysis of the genetic environment of these two genes has revealed that the highly conserved regions (tnpA-tnpR-ISkpn8-blaKPC-2) and conserved regions (blaNDM−1-bleMBL-trpF-tat) are associated with the dissemination of KPC-2 and NDM-1. Intl1 carrying drug resistance gene cassettes were widely distributed in CRKP. According to the MLST results, a total of 13 ST types were measured in 66 CRKP strains, ST11 and ST4495 were the main ST types, and the latter was the newly discovered ST type. Hematological disease, tracheal cannula and prior use of β-lactams and β-lactamase inhibitor combination were identified as independent risk factors for CRKP infections.Conclusion: These findings manifested the need for intensive surveillance and precautions to monitor the further spread of KPC and NDM in southwest China.

Disease Severity Is an Independent Risk Factor of Mortality and Outcomes in Critically Ill Patients With Carbapenem-resistant Klebsiella Pneumoniae Bloodstream Infections: a 5-year Retrospective Analysis

2021 ◽  
Author(s):  
Yuzhen Qiu ◽  
Wen Xu ◽  
Yunqi Dai ◽  
Ruoming Tan ◽  
Jialin Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Septic Shock ◽  
Klebsiella Pneumoniae ◽  
Critically Ill Patients ◽  
Bloodstream Infections ◽  
Polymyxin B ◽  
Mortality Rates ◽  
Carbapenem Resistant ◽  
All Cause Mortality ◽  
Independent Risk Factors

Abstract Background: Carbapenem-resistant Klebsiella pneumoniae bloodstream infections (CRKP-BSIs) are associated with high morbidity and mortality rates, especially in critically ill patients. Comprehensive mortality risk analyses and therapeutic assessment in real-world practice are beneficial to guide individual treatment.Methods: We retrospectively analyzed 87 patients with CRKP-BSIs (between July 2016 and June 2020) to identify the independent risk factors for 28-day all-cause mortality. The therapeutic efficacies of tigecycline-and polymyxin B-based therapies were analyzed.Results: The 28-day all-cause mortality and in-hospital mortality rates were 52.87% and 67.82%, respectively, arising predominantly from intra-abdominal (56.32%) and respiratory tract infections (21.84%). A multivariate analysis showed that 28-day all-cause mortality was independently associated with the patient’s APACHE II score (p = 0.002) and presence of septic shock at BSI onset (p = 0.006). All-cause mortality was not significantly different between patients receiving tigecycline- or polymyxin B-based therapy (55.81% vs. 53.85%, p = 0.873), and between subgroups mortality rates were also similar. Conclusions: Critical illness indicators (APACHE II scores and presence of septic shock at BSI onset) were independent risk factors for 28-day all-cause mortality. There was no significant difference between tigecycline- and polymyxin B-based therapy outcomes. Prompt and appropriate infection control should be implemented to prevent CRKP infections.

Machine Learning Algorithms to Predict the Mortality of Carbapenem Resistant Klebsiella Pneumoniae bacteremia

2019 ◽  
Author(s):  
Qiqiang Liang ◽  
Fang Qian ◽  
Yibing Chen ◽  
Zhijun Xu ◽  
Zhijiang Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Septic Shock ◽  
High Risk ◽  
Klebsiella Pneumoniae ◽  
Severe Thrombocytopenia ◽  
Acute Renal Injury ◽  
High Risk Factors ◽  
Carbapenem Resistant ◽  
Logical Regression

Abstract Purpose To establish mortality prediction models in 14 days of Carbapenem-Resistant Klebsiella Pneumoniae bacteremia using Machine learning.Materials and Methods It is a single-center retrospective study. We collect the relevant clinical information of all patients with Carbapenem-Resistant Klebsiella Pneumoniae (CRKP) bacteremia in the past 5 years using the local database. Data analysis and verification are carried out by multiple logical regression, decision tree, random forest, support vector machine (SVM), and XGBoost.Result This study includes 187 patients with 40 related variables. In multiple logical regression, acute renal injury (P=0.003), Apache II score (P=0.036), immunodeficiency (P=0.025), severe thrombocytopenia (P=0.025) and septic shock (P=0.044) are the high-risk factors for 14 days mortality of CRKP bloodstream infections. According to the importance of those parameters, risk scoring is established to predict the survival rate of CRKP bacteremia. The analysis of the five models, with 70% training set and 30% test set, show the comprehensive performance of random forest (AUROC=0.953, precision=91.85%) is slightly better than that of XGBoost (AUROC=0.912, precision=86.41%) and SVM (AUROC=0.936, precision=79.89%) in predicting 14-day mortality of CRKP bacteremia. The multiple logical regression model (AUROC=0.825, precision=81.52%) is the second, and the decision tree model (AUROC=0.712, precision=79.89%) is not very ideal.Conclusion Machine learning has good performances in predicting 14-day mortality of CRKP bacteremia than multiple logical regression. Acute renal injury, severe thrombocytopenia, and septic shock are the high-risk factors of CRKP bacteremia mortality.

Outcomes of Carbapenem-Resistant Klebsiella pneumoniae Infection and the Impact of Antimicrobial and Adjunctive Therapies

2008 ◽  
Vol 29 (12) ◽  
pp. 1099-1106 ◽  
Author(s):  
Gopi Patel ◽  
Shirish Huprikar ◽  
Stephanie H. Factor ◽  
Stephen G. Jenkins ◽  
David P. Calfee
Keyword(s):  
Risk Factors ◽  
Klebsiella Pneumoniae ◽  
Case Control Study ◽  
Patient Survival ◽  
Case Control ◽  
Factors Associated ◽  
Carbapenem Resistant ◽  
Matched Case ◽  
The Impact ◽  
Control Study

Background.Carbapenem-resistant Klebsiella pneumoniae is an emerging healthcare-associated pathogen.Objective.To describe the epidemiology of and clinical outcomes associated with carbapenem-resistant K. pneumoniae infection and to identify risk factors associated with mortality among patients with this type of infection.Setting.Mount Sinai Hospital, a 1,171-bed tertiary care teaching hospital in New York City.Design.Two matched case-control studies.Methods.In the first matched case-control study, case patients with carbapenem-resistant K. pneumoniae infection were compared with control patients with carbapenem-susceptible K. pneumoniae infection. In the second case-control study, patients who survived carbapenem-resistant K. pneumoniae infection were compared with those who did not survive, to identify risk factors associated with mortality among patients with carbapenem-resistant K. pneumoniae infection.Results.There were 99 case patients and 99 control patients identified. Carbapenem-resistant K. pneumoniae infection was independently associated with recent organ or stem-cell transplantation (P = .008), receipt of mechanical ventilation (P = .04), longer length of stay before infection (P = .01), and exposure to cephalosporins (P = .02) and carbapenems (P < .001). Case patients were more likely than control patients to die during hospitalization (48% vs 20%; P < .001) and to die from infection (38% vs 12%; P < .001). Removal of the focus of infection (ie, debridement) was independently associated with patient survival (P = .002). The timely administration of antibiotics with in vitro activity against carbapenem-resistant K. pneumoniae was not associated with patient survival.Conclusions.Carbapenem-resistant K. pneumoniae infection is associated with numerous healthcare-related risk factors and with high mortality. The mortality rate associated with carbapenem-resistant K. pneumoniae infection and the limited antimicrobial options for treatment of carbapenem-resistant K. pneumoniae infection highlight the need for improved detection of carbapenem-resistant K. pneumoniae infection, identification of effective preventive measures, and development of novel agents with reliable clinical efficacy against carbapenem-resistant K. pneumoniae.

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