Dataset Information

Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017.

ABSTRACT: Objective:To describe the epidemiology of carbapenem-resistant Enterobacteriaceae (CRE) healthcare-associated infections (HAI) in Egyptian hospitals reporting to the national HAI surveillance system. Methods:Design: Descriptive analysis of CRE HAIs and retrospective observational cohort study using national HAI surveillance data. Setting: Egyptian hospitals participating in the HAI surveillance system. The patient population included patients admitted to the intensive care unit (ICU) in participating hospitals. Enterobacteriaceae HAI cases were Klebsiella, Escherichia coli, and Enterobacter isolates from blood, urine, wound or respiratory specimen collected on or after day 3 of ICU admission. CRE HAI cases were those resistant to at least one carbapenem. For CRE HAI cases reported during 2011-2017, a hospital-level and patient-level analysis were conducted using only the first CRE isolate by pathogen and specimen type for each patient. For facility, microbiology, and clinical characteristics, frequencies and means were calculated among CRE HAI cases and compared with carbapenem-susceptible Enterobacteriaceae HAI cases through univariate and multivariate logistic regression using STATA 13. Results:There were 1598 Enterobacteriaceae HAI cases, of which 871 (54.1%) were carbapenem resistant. The multivariate regression analysis demonstrated that carbapenem resistance was associated with specimen type, pathogen, location prior to admission, and length of ICU stay. Between 2011 and 2017, there was an increase in the proportion of Enterobacteriaceae HAI cases due to CRE (p-value?=?0.003) and the incidence of CRE HAIs (p-value?=?0.09). Conclusions:This analysis demonstrated a high and increasing burden of CRE in Egyptian hospitals, highlighting the importance of enhancing infection prevention and control (IPC) programs and antimicrobial stewardship activities and guiding the implementation of targeted IPC measures to contain CRE in Egyptian ICU's .

SUBMITTER: Kotb S

PROVIDER: S-EPMC6942386 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017.

Kotb Sara S Lyman Meghan M Ismail Ghada G Abd El Fattah Mohammad M Girgis Samia A SA Etman Ahmed A Hafez Soad S El-Kholy Jehan J Zaki Maysaa El Sayed MES Rashed Hebat-Allah G HG Khalil Ghada M GM Sayyouh Omar O Talaat Maha M

Antimicrobial resistance and infection control 20200103 1

<h4>Objective</h4>To describe the epidemiology of carbapenem-resistant Enterobacteriaceae (CRE) healthcare-associated infections (HAI) in Egyptian hospitals reporting to the national HAI surveillance system.<h4>Methods</h4>Design<b>:</b> Descriptive analysis of CRE HAIs and retrospective observational cohort study using national HAI surveillance data<b>.</b> Setting: Egyptian hospitals participating in the HAI surveillance system. The patient population included patients admitted to the intensiv ...[more]

PMID: 31911830

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Project description:BACKGROUND:Healthcare-associated infections (HAIs) represent serious complications for patients within pediatric cardiac intensive care units (CICU). HAIs are associated with increased morbidity, mortality and resource utilization. There are few studies describing the epidemiology of HAIs across the entire spectrum of patients (surgical and nonsurgical) receiving care in dedicated pediatric CICUs. METHODS:Retrospective analyses of 22,839 CICU encounters from October 2013 to September 2016 across 22 North American CICUs contributing data to the Pediatric Cardiac Critical Care Consortium clinical registry. RESULTS:HAIs occurred in 2.4% of CICU encounters at a rate of 3.3 HAIs/1000 CICU days, with 73% of HAIs occurring in children <1 year. Eighty encounters (14%) had ?2 HAIs. Aggregate rates for the 4 primary HAIs are as follows: central line-associated blood stream infection, 1.1/1000 line days; catheter-associated urinary tract infections, 1.5/1000 catheter days; ventilator-associated pneumonia, 1.9/1000 ventilator days; surgical site infections, 0.81/100 operations. Surgical and nonsurgical patients had similar HAIs rates/1000 CICU days. Incidence was twice as high in surgical encounters and increased with surgical complexity; postoperative infection occurred in 2.8% of encounters. Prematurity, younger age, presence of congenital anomaly, Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality Categories (STAT) 4-5 surgery, admission with an active medical condition, open sternum and extracorporeal membrane oxygenation were independently associated with HAIs. In univariable analysis, HAI was associated with longer hospital length of stay and durations of urinary catheter, central venous catheter and ventilation. Mortality was 24.4% in patients with HAIs versus 3.4% in those without, P < 0.0001. CONCLUSIONS:We provide comprehensive multicenter benchmark data regarding rates of HAIs within dedicated pediatric CICUs. We confirm that although rare, HAIs of all types are associated with significant resource utilization and mortality.

Project description:Widespread use of antibiotics has resulted in an increase in antimicrobial-resistant microorganisms. Although not all bacterial contact results in infection, patients can become asymptomatically colonized, increasing the risk of infection and pathogen transmission. Consequently, many institutions have begun active surveillance, but in non-research settings, the resulting data are often incomplete and may include non-random testing, making conventional epidemiological analysis problematic. We describe a mathematical model and inference method for in-hospital bacterial colonization and transmission of carbapenem-resistant Enterobacteriaceae that is tailored for analysis of active surveillance data with incomplete observations. The model and inference method make use of the full detailed state of the hospital unit, which takes into account the colonization status of each individual in the unit and not only the number of colonized patients at any given time. The inference method computes the exact likelihood of all possible histories consistent with partial observations (despite the exponential increase in possible states that can make likelihood calculation intractable for large hospital units), includes techniques to improve computational efficiency, is tested by computer simulation, and is applied to active surveillance data from a 13-bed rehabilitation unit in New York City. The inference method for exact likelihood calculation is applicable to other Markov models incorporating incomplete observations. The parameters that we identify are the patient-patient transmission rate, pre-existing colonization probability, and prior-to-new-patient transmission probability. Besides identifying the parameters, we predict the effects on the total prevalence (0.07 of the total colonized patient-days) of changing the parameters and estimate the increase in total prevalence attributable to patient-patient transmission (0.02) above the baseline pre-existing colonization (0.05). Simulations with a colonized versus uncolonized long-stay patient had 44% higher total prevalence, suggesting that the long-stay patient may have been a reservoir of transmission. High-priority interventions may include isolation of incoming colonized patients and repeated screening of long-stay patients.

Project description:Background. Gram negative antibiotic resistance is increasing worldwide as both carbapenem-resistant enterobacteriaceae (CREs) and Enterobacteriaceae producing extended spectrum ß-lactamases (ESBLs) become more common. Objective. We analyzed clinicians' knowledge regarding resistant gram-negative organisms with respect to infection control practices, prescribing practices and assessment of their patients' risk for resistant infections. Design. Online survey. Participants. Target population included clinicians who prescribe antibiotics i.e., medical doctors and mid-level practitioners, at three Massachusetts hospitals. Methods. Questionnaires were sent to 3 Tufts-affiliated teaching hospitals to assess level of knowledge and elucidate perceptions about gram-negative resistance. Results. We received 434 responses from 3332 non-infectious disease clinicians (13%) surveyed at the three hospitals. 51.1% of clinicians correctly scored 50% or greater on the knowledge questions. Internal medicine clinicians had higher knowledge scores than non-internal medicine clinicians (62% vs 45%; OR = 1.67, p = 0.02). Clinicians within three years of training had higher scores than those with more than 10 years of training (64.3% vs 44%; OR = 2.3, p = 0.002). Clinicians with fewer years since training and those with higher knowledge scores were more likely to appropriately consider certain patients at risk for resistant infections (p < 0.05). 54.4% of clinicians were very concerned about gram-negative antibiotic resistance. 64.6% of clinicians felt comfortable de-escalating antibiotics as cultures are available. Conclusion. We found overall low knowledge scores and much variability in the way clinicians assess whether certain patient populations are at risk for antibiotic resistance. Internal medicine clinicians and those with fewer years since completion of their training scored higher and more appropriately considered patients at risk for resistance. The majority of clinicians are concerned about gram-negative resistance and indicated they would de-escalate antibiotic therapy if they had susceptibility information. These results will help focus and target our teaching and awareness-raising strategies.

Dataset Information

Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017.

Publications

Epidemiology of Carbapenem-resistant Enterobacteriaceae in Egyptian intensive care units using National Healthcare-associated Infections Surveillance Data, 2011-2017.

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