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.

Risk factors for fecal carriage of IMP-6-producing Enterobacteriaceae at a long-term care hospital in Japan: A follow-up report from the northern Osaka multicentre study group

2018 ◽  
Vol 24 (9) ◽  
pp. 769-772 ◽  
Author(s):  
Hideharu Hagiya ◽  
Norihisa Yamamoto ◽  
Ryuji Kawahara ◽  
Yukihiro Akeda ◽  
Rathina Kumar Shanmugakani ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multicentre Study ◽  
Long Term Care ◽  
Study Group ◽  
Care Hospital ◽  
Term Care ◽  
Fecal Carriage

Risk factors for recurrence of scabies: A retrospective study of scabies patients in a long-term care hospital

2011 ◽  
pp. no-no ◽  
Author(s):  
Kuniko MAKIGAMI ◽  
Noriko OHTAKI ◽  
Norihisa ISHII ◽  
Tetsuko TAMASHIRO ◽  
Sadao YOSHIDA ◽  
...  
Keyword(s):  
Risk Factors ◽  
Retrospective Study ◽  
Long Term Care ◽  
Care Hospital ◽  
Term Care ◽  
Risk Factors For Recurrence

scholarly journals EPIDEMIOLOGY AND TRANSMISSION OF CARBAPENEMASE-PRODUCING ENTEROBACTERIACEAE IN A HEALTHCARE NETWORK OF AN ACUTE HOSPITAL AND ITS AFFILIATED INTERMEDIATE- AND LONG-TERM CARE FACILITIES IN SINGAPORE

2021 ◽  
Author(s):  
Aung-Hein Aung ◽  
Kala Kanagasabai ◽  
Jocelyn Koh ◽  
Pei-Yun Hon ◽  
Brenda Ang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Acute Care Hospital ◽  
Care Hospital ◽  
Cross Sectional ◽  
Term Care ◽  
Healthcare Network ◽  
Care Facilities ◽  
Facility Type

BACKGROUND Movement of patients in a healthcare network poses challenges for the control of carbapenemase-producing Enterobacteriaceae (CPE). We aimed to identify intra- and inter-facility transmission events and facility type-specific risk factors of CPE in an acute care hospital (ACH) and its intermediate-term and long-term care facilities (ILTCFs). METHODS Serial cross-sectional studies were conducted in June-July of 2014-2016 to screen for CPE. Whole genome sequencing was done to identify strain relatedness and CPE genes (blaIMI; blaIMP-1; blaKPC-2; blaNDM-1; blaOXA-48). Multivariable logistic regression models, stratified by facility type were used to determine independent risk factors. RESULTS Of 5357 patients, half (55%) were from the ACH. CPE prevalence was 1.3% in the ACH and 0.7% in ILTCFs (p=0.029). After adjusting for socio-demographics, screening year, and facility type, the odds of CPE colonization increased significantly with hospital stay ≥ 3 weeks (aOR 2.67, 95%CI 1.17-6.05), penicillins use (aOR 3.00, 95%CI 1.05–8.56), proton pump inhibitors use (aOR 3.20, 95%CI 1.05–9.80), dementia (aOR 3.42, 95%CI 1.38–8.49), connective tissue disease (aOR 5.10, 95%CI 1.19-21.81), and prior carbapenem-resistant Enterobacteriaceae (CRE) carriage (aOR 109.02, 95%CI 28.47–417.44) in the ACH. For ILTCFs, presence of wound (aOR 5.30, 95%CI 1.01–27.72), respiratory procedures (aOR 4.97, 95%CI 1.09-22.71), vancomycin-resistant Enterococci carriage (aOR 16.42, 95%CI 1.52–177.48), and CRE carriage (aOR 758.30, 95%CI 33.86-16982.52) showed significant association. Genomic analysis revealed only possible intra-ACH transmission, and no evidence for ACH-to-ILTCFs transmission. CONCLUSIONS Although CPE colonization was predominantly in the ACH, risk factors varied between facilities. Targeted screening and precautionary measures are warranted.

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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