scholarly journals Risk Factors for Extended-Spectrum-β-Lactamase-Producing Escherichia coli in Community-Onset Bloodstream Infection: Impact on Long-Term Care Hospitals in Korea

2021 ◽  
Vol 41 (5) ◽  
pp. 455-462
Author(s):  
Yae Jee Baek ◽  
Young Ah Kim ◽  
Dokyun Kim ◽  
Jong Hee Shin ◽  
Young Uh ◽  
...  
Keyword(s):  
Risk Factors ◽  
Escherichia Coli ◽  
Bloodstream Infection ◽  
Long Term Care ◽  
Term Care ◽  
Extended Spectrum ◽  
Community Onset

scholarly journals Long-Term Care Facilities Are Reservoirs for Antimicrobial-Resistant Sequence Type 131 Escherichia coli

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Mary J. Burgess ◽  
James R. Johnson ◽  
Stephen B. Porter ◽  
Brian Johnston ◽  
Connie Clabots ◽  
...  
Keyword(s):  
Risk Factors ◽  
Escherichia Coli ◽  
Gel Electrophoresis ◽  
Long Term Care ◽  
Pulsed Field Gel Electrophoresis ◽  
Sequence Type ◽  
Term Care ◽  
E Coli ◽  
Care Facilities

Abstract Background.  Emerging data implicate long-term care facilities (LTCFs) as reservoirs of fluoroquinolone-resistant (FQ-R) Escherichia coli of sequence type 131 (ST131). We screened for ST131 among LTCF residents, characterized isolates molecularly, and identified risk factors for colonization. Methods.  We conducted a cross-sectional study using a single perianal swab or stool sample per resident in 2 LTCFs in Olmsted County, Minnesota, from April to July 2013. Confirmed FQ-R E. coli isolates underwent polymerase chain reaction-based phylotyping, detection of ST131 and its H30 and H30-Rx subclones, extended virulence genotyping, and pulsed-field gel electrophoresis (PFGE) analysis. Epidemiological data were collected from medical records. Results.  Of 133 fecal samples, 33 (25%) yielded FQ-R E. coli, 32 (97%) of which were ST131. The overall proportion with ST131 intestinal colonization was 32 of 133 (24%), which differed by facility: 17 of 41 (42%) in facility 1 vs 15 of 92 (16%) in facility 2 (P = .002). All ST131 isolates represented the H30 subclone, with virulence gene and PFGE profiles resembling those of previously described ST131 clinical isolates. By PFGE, certain isolates clustered both within and across LTCFs. Multivariable predictors of ST131 colonization included inability to sign consent (odds ratio [OR], 4.16 [P = .005]), decubitus ulcer (OR, 4.87 [ P = .04]), and fecal incontinence (OR, 2.59 [P = .06]). Conclusions.  Approximately one fourth of LTCF residents carried FQ-R ST131 E. coli resembling ST131 clinical isolates. Pulsed-field gel electrophoresis suggested intra- and interfacility transmission. The identified risk factors suggest that LTCF residents who require increased nursing care are at greatest risk for ST131 colonization, possibly due to healthcare-associated transmission.

scholarly journals Prevalence and Risk Factors for Multidrug-Resistant Organisms Colonization in Long-Term Care Facilities Around the World: A Review

Antibiotics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 680
Author(s):  
Ángel Rodríguez-Villodres ◽  
Cecilia Martín-Gandul ◽  
Germán Peñalva ◽  
Ana Belén Guisado-Gil ◽  
Juan Carlos Crespo-Rivas ◽  
...  
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Multidrug Resistant ◽  
Term Care ◽  
Extended Spectrum ◽  
Increased Risk ◽  
Modifiable Factors ◽  
Care Facilities ◽  
Multidrug Resistant Organisms

Elderly people confined to chronic care facilities face an increased risk of acquiring infections by multidrug-resistant organisms (MDROs). This review presents the current knowledge of the prevalence and risk factors for colonization by MDROs in long-term care facilities (LTCF), thereby providing a useful reference to establish objectives for implementing successful antimicrobial stewardship programs (ASPs). We searched in PubMed and Scopus for studies examining the prevalence of MDROs and/or risk factors for the acquisition of MDROs in LTCF. One hundred and thirty-four studies published from 1987 to 2020 were included. The prevalence of MDROs in LTCF varies between the different continents, where Asia reported the highest prevalence of extended-spectrum ß-lactamase (ESBL) Enterobacterales (71.6%), carbapenem resistant (CR) Enterobacterales (6.9%) and methicillin-resistant Staphylococcus aureus (MRSA) (25.6%) and North America the highest prevalence to MDR Pseudomonas aeruginosa (5.4%), MDR Acinetobacter baumannii (15.0%), vancomycin-resistant Enterococcus spp. (VRE) (4.0%), and Clostridioides difficile (26.1%). Furthermore, MDRO prevalence has experienced changes over time, with increases in MDR P. aeruginosa and extended spectrum ß-lactamase producing Enterobacterales observed starting in 2015 and decreases of CR Enterobacterales, MDR A. baumannii, VRE, MRSA and C. difficile. Several risk factors have been found, such as male sex, chronic wounds, the use of medical devices, and previous antibiotic use. The last of these aspects represents one of the most important modifiable factors for reducing colonization with MDROs through implementing ASPs in LTCF.

scholarly journals Colonization with Extended-Spectrum β-Lactamase-ProducingEscherichia coliandKlebsiellaSpecies in Long-Term Care Facility Residents

2012 ◽  
Vol 33 (3) ◽  
pp. 302-304 ◽  
Author(s):  
Ebbing Lautenbach ◽  
Jennifer Han ◽  
Evelyn Santana ◽  
Pam Tolomeo ◽  
Warren B. Bilker ◽  
...  
Keyword(s):  
Risk Factors ◽  
Fecal Incontinence ◽  
Long Term Care ◽  
Care Facility ◽  
Infect Control Hosp ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility ◽  
Extended Spectrum

We describe the prevalence of and risk factors for colonization with extended-spectrum (3-lactamase-producing Enterobacteriaceae (ESBL-EB) in the long-term care facility (LTCF) setting. Colonization prevalence differed significantly across the 3 LTCFs evaluated in the study, with recent use of levofloxacin and fecal incontinence demonstrating borderline significant associations with ESBL-EB colonization.Infect Control Hosp Epidemiol2012;33(3):302-304

scholarly journals Surveillance of Community-Based Reservoirs Reveals the Presence of CTX-M, Imported AmpC, and OXA-30 β-Lactamases in Urine Isolates of Klebsiella pneumoniae and Escherichia coli in a U.S. Community

2008 ◽  
Vol 52 (10) ◽  
pp. 3814-3816 ◽  
Author(s):  
Nancy D. Hanson ◽  
Ellen Smith Moland ◽  
S. G. Hong ◽  
Katie Propst ◽  
Deborah J. Novak ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Klebsiella Pneumoniae ◽  
Long Term Care ◽  
Outpatient Clinics ◽  
Community Based ◽  
Term Care ◽  
Extended Spectrum ◽  
Care Facilities

ABSTRACT β-Lactamases produced by urine isolates from patients in long-term care facilities (LTCFs), outpatient, clinics, and one hospital in a U.S. community were characterized. A total of 1.3% of all Escherichia coli and Klebsiella pneumoniae isolates collected from patients in 30 LTCFs and various outpatient clinics produced extended-spectrum β-lactamases (ESBLs) and/or imported AmpC β-lactamases.

scholarly journals 476. Risk Factors of Community-Onset Extended-Spectrum β-Lactamase-Producing Klebsiella pneumoniae Bacteremia in South Korea Using National Health Insurance Claims Data

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S232-S233
Author(s):  
Yongseop Lee ◽  
Yoon Soo Park ◽  
Dokyun Kim ◽  
Young Ah Kim ◽  
Jong Hee Shin ◽  
...  
Keyword(s):  
Risk Factors ◽  
South Korea ◽  
Long Term Care ◽  
Care Hospital ◽  
Term Care ◽  
Insurance Claims Data ◽  
Health Insurance Claims Data ◽  
Health Insurance Claims ◽  
Community Onset

Abstract Background Antibiotic resistance is a significant threat to public health not only in healthcare setting but also in community because antimicrobial-resistant infections can be transmitted in community. Although it is essential to know whether there are particular reasons that caused antibiotic-resistant infection in community, there is lack of evidence regarding risk factors for community-onset extended-spectrum β-lactamase-producing Klebsiella pneumoniae bloodstream infection (ESBL-KP BSI) in South Korea. In the present study, we aimed to reveal risk factors for community-onset ESBL-KP BSI. Methods From May 2016 to April 2017, patients with community-onset KP BSI (n = 408) from six sentinel hospitals in South Korea were included. The hospitals are located in different districts throughout South Korea, and had a total of 5,194 beds, ranged from 715 to 1,050 beds per hospital. Admission history and previous usage of antibiotics and medical devices before bacteremia were acquired from National Health Insurance claims data. Risk factors of ESBL-KP BSI were analyzed with a multivariable logistic regression model. PCR and sequencing for the identification of genes encoding ESBLs, and multilocus sequence typing were performed. Results Of 408 patient of community-onset KP BSI, 70 (17%) were ESBL-KP BSI patients. ESBL-KP isolates most frequently carried CTX-M-1-group ESBLs (74%, n = 52), followed by CTX-M-9-group ESBLs (16%, n = 11). Most prevalent sequence type (ST) among ESBL-KP isolates was ST48 (14%, n = 10). Among non-ESBL-KP isolates, ST23 was most prevalent (21%, n = 70). Analyzing with multivariate analysis, recent admission to long-term care hospital within 3 months (OR, 5.7; 95% CI, 2.1–15.6; P = 0.001), previous usage of trimethoprim-sulfamethoxazole (OR, 11.5; 95% CI, 2.7–48.6; P = 0.001), expanded-spectrum cephalosporin (OR, 2.2; 95% CI, 1.2–3.9; P = 0.01), and previous use of urinary catheter (OR, 2.3; 95% CI, 1.1–4.5; P = 0.02) were identified as independent risk factors for community-onset ESBL-KP BSI. Conclusion Recent admission to long-term care hospital, use of urinary catheter, recent usage of antibiotics were identified as risk factors for community-onset ESBL-KP BSI. Strict antibiotic stewardship and infection control measures in long-term care hospital are needed. Disclosures All authors: No reported disclosures.

Design and Development of a Web-based Delirium Preventive Application for Long-term Care Facilities: A Methodological Study (Preprint)

2020 ◽  
Author(s):  
Kyoung Ja Moon ◽  
Chang-Sik Son ◽  
Jong-Ha Lee ◽  
Mina Park
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Cloud System ◽  
Evidence Based ◽  
Methodological Study ◽  
Term Care ◽  
Web Based ◽  
Care Facilities ◽  
Delirium Prevention

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

scholarly journals Risk factors for COVID-19 diagnosis, hospitalization, and subsequent all-cause mortality in Sweden: a nationwide study

2021 ◽  
Vol 36 (3) ◽  
pp. 287-298
Author(s):  
Jonathan Bergman ◽  
Marcel Ballin ◽  
Anna Nordström ◽  
Peter Nordström
Keyword(s):  
Risk Factors ◽  
Down Syndrome ◽  
Long Term Care ◽  
Care Facility ◽  
Prescription Medication ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility ◽  
All Cause Mortality

AbstractWe conducted a nationwide, registry-based study to investigate the importance of 34 potential risk factors for coronavirus disease 2019 (COVID-19) diagnosis, hospitalization (with or without intensive care unit [ICU] admission), and subsequent all-cause mortality. The study population comprised all COVID-19 cases confirmed in Sweden by mid-September 2020 (68,575 non-hospitalized, 2494 ICU hospitalized, and 13,589 non-ICU hospitalized) and 434,081 randomly sampled general-population controls. Older age was the strongest risk factor for hospitalization, although the odds of ICU hospitalization decreased after 60–69 years and, after controlling for other risk factors, the odds of non-ICU hospitalization showed no trend after 40–49 years. Residence in a long-term care facility was associated with non-ICU hospitalization. Male sex and the presence of at least one investigated comorbidity or prescription medication were associated with both ICU and non-ICU hospitalization. Three comorbidities associated with both ICU and non-ICU hospitalization were asthma, hypertension, and Down syndrome. History of cancer was not associated with COVID-19 hospitalization, but cancer in the past year was associated with non-ICU hospitalization, after controlling for other risk factors. Cardiovascular disease was weakly associated with non-ICU hospitalization for COVID-19, but not with ICU hospitalization, after adjustment for other risk factors. Excess mortality was observed in both hospitalized and non-hospitalized COVID-19 cases. These results confirm that severe COVID-19 is related to age, sex, and comorbidity in general. The study provides new evidence that hypertension, asthma, Down syndrome, and residence in a long-term care facility are associated with severe COVID-19.

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