Prevalence, Risk Factors, Treatment Outcome and Molecular Epidemiology of Gastrointestinal Carbapenem-Resistant Klebsiella Pneumoniae from Infections in China

2021 ◽  
Author(s):  
Congcong Liu ◽  
Chang Cai ◽  
Ning Dong ◽  
Ling Huang ◽  
Danxia Gu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Treatment Outcome ◽  
Klebsiella Pneumoniae ◽  
Molecular Epidemiology ◽  
Carbapenem Resistant

Risk Factors and Molecular Epidemiology of Complicated Intra-Abdominal Infections With Carbapenem-Resistant Enterobacteriaceae: A Multicenter Study in China

2020 ◽  
Vol 221 (Supplement_2) ◽  
pp. S156-S163 ◽  
Author(s):  
Jiao Liu ◽  
Lidi Zhang ◽  
Jingye Pan ◽  
Man Huang ◽  
Yingchuan Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Klebsiella Pneumoniae ◽  
Hospital Mortality ◽  
Molecular Epidemiology ◽  
Carbapenem Resistance ◽  
Resistance Mechanisms ◽  
Carbapenem Resistant ◽  
Abdominal Infections ◽  
Hospital Acquired ◽  
Carbapenem Resistant Enterobacteriaceae

Abstract Background Carbapenem-resistant Enterobacteriaceae (CRE) infections are associated with poor patient outcomes. Data on risk factors and molecular epidemiology of CRE in complicated intra-abdominal infections (cIAI) in China are limited. This study examined the risk factors of cIAI with CRE and the associated mortality based on carbapenem resistance mechanisms. Methods In this retrospective analysis, we identified 1024 cIAI patients hospitalized from January 1, 2013 to October 31, 2018 in 14 intensive care units in China. Thirty CRE isolates were genotyped to identify β-lactamase-encoding genes. Results Escherichia coli (34.5%) and Klebsiella pneumoniae (21.2%) were the leading pathogens. Patients with hospital-acquired cIAI had a lower rate of E coli (26.0% vs 49.1%; P < .001) and higher rate of carbapenem-resistant Gram-negative bacteria (31.7% vs 18.8%; P = .002) than those with community-acquired cIAI. Of the isolates, 16.0% and 23.4% of Enterobacteriaceae and K pneumoniae, respectively, were resistant to carbapenem. Most carbapenemase-producing (CP)-CRE isolates carried blaKPC (80.9%), followed by blaNMD (19.1%). The 28-day mortality was 31.1% and 9.0% in patients with CRE vs non-CRE (P < .001). In-hospital mortality was 4.7-fold higher for CP-CRE vs non-CP-CRE infection (P = .049). Carbapenem-containing combinations did not significantly influence in-hospital mortality of CP and non-CP-CRE. The risk factors for 28-day mortality in CRE-cIAI included septic shock, antibiotic exposure during the preceding 30 days, and comorbidities. Conclusions Klebsiella pneumoniae had the highest prevalence in CRE. Infection with CRE, especially CP-CRE, was associated with increased mortality in cIAI.

scholarly journals Risk Factors and Outcomes for Carbapenem-Resistant Klebsiella pneumoniae Isolation, Stratified by Its Multilocus Sequence Typing: ST258 Versus Non-ST258

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Sorabh Dhar ◽  
Emily T. Martin ◽  
Paul R. Lephart ◽  
John P. McRoberts ◽  
Teena Chopra ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Klebsiella Pneumoniae ◽  
Molecular Epidemiology ◽  
Clinical Outcomes ◽  
Multilocus Sequence Typing ◽  
Clinical Impact ◽  
Sequence Type ◽  
Epidemiological Investigation ◽  
Carbapenem Resistant

Abstract A “high risk” clone of carbapenem-resistant Klebsiella pneumoniae (CRKP) identified by multilocus sequence typing (MLST) as sequence type (ST) 258 has disseminated worldwide. As the molecular epidemiology of the CRE pandemic continues to evolve, the clinical impact of non-ST258 strains is less well defined. We conducted an epidemiological investigation of CRKP based on strains MLST. Among 68 CRKP patients, 61 were ST258 and 7 belonged to non-ST258. Klebsiella pneumoniae ST258 strains were significantly associated with blaKPC production and with resistance to an increased number of antimicrobials. Clinical outcomes were not different. Based on this analysis, one cannot rely solely on the presence of blaKPC in order to diagnose CRKP.

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.

Sign in / Sign up

Export Citation Format

Share Document