Gut Microbiota Features on Nursing Home Admission Are Associated With Subsequent Acquisition of Antibiotic-resistant Organism Colonization.
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ABSTRACT:
SUBMITTER: Wang J
PROVIDER: S-EPMC7819526 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Prevalence of multidrug resistant organisms (MDRO) in nursing homes in Ireland and the Netherlands
| PRJEB31196 | ENA
Project description:RationaleCognitive impairment is common among older adults, yet little is known about the association of pre-intensive care unit cognitive status with outcomes relevant to older adults maintaining independence after a critical illness.ObjectivesTo evaluate whether pre-intensive care unit cognitive status is associated with post-intensive care unit disability, new nursing home admission, and mortality after a critical illness among older adults.MethodsIn this prospective cohort study, 754 persons aged 70 years or more were monitored from March 1998 to December 2013 with monthly assessments of disability. Cognitive status was assessed every 18 months, using the Mini-Mental State Examination (range, 0-30), with scores classified as 28 or higher (cognitively intact), 24-27 (minimal impairment), and less than 24 (moderate impairment). The primary outcome was disability count (range, 0-13), assessed monthly over 6 months after an intensive care unit stay. The secondary outcomes were incident nursing home admission and time to death after intensive care unit admission. The analytic sample included 391 intensive care unit admissions.ResultsThe mean age was 83.5 years. The prevalence of moderate impairment, minimal impairment, and intact cognition (the comparison group) was 17.3, 46.2, and 36.5%, respectively. In the multivariable analysis, moderate impairment was associated with nearly a 20% increase in disability over the 6-month follow-up period (adjusted relative risk, 1.19; 95% confidence interval, 1.04-1.36), and minimal impairment was associated with a 16% increase in post-intensive care unit disability (adjusted relative risk, 1.16; 95% confidence interval, 1.02-1.32). Moderate impairment was associated with more than double the likelihood of a new nursing home admission (adjusted odds ratio, 2.37; 95% confidence interval, 1.01-5.55). Survival differed significantly across the three cognitive groups (log-rank P = 0.002), but neither moderate impairment (adjusted hazard ratio, 1.19; 95% confidence interval, 0.65-2.19) nor minimal impairment (adjusted hazard ratio, 1.00; 95% confidence interval, 0.61-1.62) was significantly associated with mortality in the multivariable analysis.ConclusionsAmong older adults, any impairment (even minimal) in pre-intensive care unit cognitive status was associated with an increase in post-intensive care unit disability over the 6 months after a critical illness; moderate cognitive impairment doubled the likelihood of a new nursing home admission. Pre-intensive care unit cognitive impairment was not associated with mortality from intensive care unit admission through 6 months of follow-up. Pre-intensive care unit cognitive status may provide prognostic information about the likelihood of older adults maintaining independence after a critical illness.
| S-EPMC5949607 | biostudies-literature
Project description: Not available
| S-EPMC5801742 | biostudies-literature
Project description:UnlabelledPerturbations to the gut microbiota can result in a loss of colonization resistance against gastrointestinal pathogens such as Clostridium difficile. Although C. difficile infection is commonly associated with antibiotic use, the precise alterations to the microbiota associated with this loss in function are unknown. We used a variety of antibiotic perturbations to generate a diverse array of gut microbiota structures, which were then challenged with C. difficile spores. Across these treatments we observed that C. difficile resistance was never attributable to a single organism, but rather it was the result of multiple microbiota members interacting in a context-dependent manner. Using relative abundance data, we built a machine learning regression model to predict the levels of C. difficile that were found 24 h after challenging the perturbed communities. This model was able to explain 77.2% of the variation in the observed number of C. difficile per gram of feces. This model revealed important bacterial populations within the microbiota, which correlation analysis alone did not detect. Specifically, we observed that populations associated with the Porphyromonadaceae, Lachnospiraceae, Lactobacillus, and Alistipes were protective and populations associated with Escherichia and Streptococcus were associated with high levels of colonization. In addition, a population affiliated with the Akkermansia indicated a strong context dependency on other members of the microbiota. Together, these results indicate that individual bacterial populations do not drive colonization resistance to C. difficile. Rather, multiple diverse assemblages act in concert to mediate colonization resistance.ImportanceThe gastrointestinal tract harbors a complex community of bacteria, known as the microbiota, which plays an integral role preventing its colonization by gut pathogens. This resistance has been shown to be crucial for protection against Clostridium difficile infections (CDI), which are the leading source of hospital-acquired infections in the United States. Antibiotics are a major risk factor for acquiring CDI due to their effect on the normal structure of the indigenous gut microbiota. We found that diverse antibiotic perturbations gave rise to altered communities that varied in their susceptibility to C. difficile colonization. We found that multiple coexisting populations, not one specific population of bacteria, conferred resistance. By understanding the relationships between C. difficile and members of the microbiota, it will be possible to better manage this important infection.
| S-EPMC4502226 | biostudies-literature
Project description:ObjectiveTo explore the association between baseline life-space mobility and nursing home (NH) admission among community-dwelling older adults over 6 years.MethodsUsing data from a prospective, observational cohort study consisting of a random sample of 1,000 Medicare beneficiaries ≥ 65 years of age stratified by race (African American and non-Hispanic White), sex, and rural/urban residence. Baseline life-space mobility was assessed during in-home interviews. Participants were contacted by telephone every 6 months to ascertain NH admissions, Life-Space Assessment (LSA) scores, and vital status (living or deceased). Using multivariate logistic regression, the significance and independence of the relationship of life-space mobility with NH admission were examined.ResultsOver 6 years, the odds of NH admission increased 2% for every one point lower baseline life-space score independent of previously recognized risk factors.DiscussionThe LSA may be a useful tool to identify older adults at risk of NH admission.
| S-EPMC4071297 | biostudies-literature
Project description:ObjectiveTo examine whether disaggregated activities of daily living (ADL) limitations better predict the risk of nursing home admission compared to conventionally used ADL disability counts.Data sourcesWe used panel data from the Health and Retirement Study (HRS) for years 1998-2010. The HRS is a nationally representative survey of adults older than 50 years (n = 18,801).Study designWe fitted Cox regressions in a continuous time survival model with age at first nursing home admission as the outcome. Time-varying ADL disability types were the key explanatory variables.Principal findingsOf the six ADL limitations, bathing difficulty emerged as the strongest predictor of subsequent nursing home placement across cohorts. Eating and dressing limitations were also influential in driving admissions among more recent cohorts. Using simple ADL counts for analysis yielded similar adjusted R(2) s; however, the amount of explained variance doubled when we allowed the ADL disability measures to time-vary rather than remain static.ConclusionsLooking beyond simple ADL counts can provide health professionals insights into which specific disability types trigger long-term nursing home use. Functional disabilities measured closer in time carry more prognostic power than static measures.
| S-EPMC4369222 | biostudies-literature
Project description:Permanent nursing home (NH) admissions are a frequent and major life event aimed at maintaining quality of life in old age. Yet, insights into the impact of a NH admission on well-being are scarce and inconclusive. We evaluate the effect of a NH admission on domains of well-being among those who are admitted using event study methodology for cross-sections combined with inverse probability weighting. We apply this doubly robust approach to Dutch survey data on well-being linked to extensive administrative data on NH admissions, health, and socio-economic status. We find that a NH admission leads to a temporary increase in loneliness, the risk of anxiety and depression, and a loss of control over one's life. However, these scores revert to pre-admission levels after 6 months. These findings may contribute to better-informed individual-level and policy decisions about potential NH entry and aging in place policies.
| S-EPMC9826495 | biostudies-literature
Project description:Objective: Determine the prevalence of methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum beta-lactamase producing organisms (ESBLs), and carbapenem-resistant Enterobacteriaceae (CRE) among residents and in the environment of nursing homes (NHs).Design: Point prevalence sampling of residents and environmental sampling of high-touch objects in resident rooms and common areas.Setting: Twenty-eight NHs in Southern California from 2016 to 2017.Participants: NH participants in Project PROTECT, a cluster-randomized trial of enhanced bathing and decolonization vs routine care.Methods: Fifty residents were randomly sampled per NH. Twenty objects were sampled, including 5 common room objects plus 5 objects in each of 3 rooms (ambulatory, total care, and dementia care residents).Results: A total of 2797 swabs were obtained from 1400 residents in 28 NHs. Median prevalence of multidrug-resistant organism (MDRO) carriage per NH was 50% (range: 24%-70%). Median prevalence of specific MDROs were as follows: MRSA, 36% (range: 20%-54%); ESBL, 16% (range: 2%-34%); VRE, 5% (range: 0%-30%); and CRE, 0% (range: 0%-8%). A median of 45% of residents (range: 24%-67%) harbored an MDRO without a known MDRO history. Environmental MDRO contamination was found in 74% of resident rooms and 93% of common areas.Conclusions and implications: In more than half of the NHs, more than 50% of residents were colonized with MDROs of clinical and public health significance, most commonly MRSA and ESBL. Additionally, the vast majority of resident rooms and common areas were MDRO contaminated. The unknown submerged portion of the iceberg of MDRO carriers in NHs may warrant changes to infection prevention and control practices, particularly high-fidelity adoption of universal strategies such as hand hygiene, environmental cleaning, and decolonization.
| S-EPMC7708431 | biostudies-literature
Project description:Several studies have recently identified the main factors contributing to the bacterial colonization of newborns and the dynamics of the infant microbiome development. However, most of these studies address large time periods of weeks or months after birth, thereby missing on important aspects of the early microbiome maturation, such as the acquisition of antibiotic resistance determinants during postpartum hospitalization. The pioneer bacterial colonization and the extent of its associated antibiotic resistance gene (ARG) dissemination during this early phase of life are largely unknown. Studies addressing resistant bacteria or ARGs in neonates often focus only on the presence of particular bacteria or genes from a specific group of antibiotics. In the present study, we investigated the gut-, the oral-, and the skin-microbiota of neonates within the first 72 h after birth using 16S rDNA sequencing approaches. In addition, we screened the neonates and their mothers for the presence of 20 different ARGs by directed TaqMan qPCR assays. The taxonomic analysis of the newborn samples revealed an important shift of the microbiota during the first 72 h after birth, showing a clear site-specific colonization pattern in this very early time frame. Moreover, we report a substantial acquisition of ARGs during postpartum hospitalization, with a very high incidence of macrolide resistance determinants and mecA detection across different body sites of the newborns. This study highlights the importance of antibiotic resistance determinant dissemination in neonates during hospitalization, and the need to investigate the implication of the mothers and the hospital environment as potential sources of ARGs.
| S-EPMC7366792 | biostudies-literature
Project description:In previous years a substantial number of studies have identified statistically important predictors of nursing home admission (NHA). However, as far as we know, the analyses have been done at the population-level. No prior research has analysed the prediction accuracy of a NHA model for individuals.This study is an analysis of 3056 longer-term home care customers in the city of Tampere, Finland. Data were collected from the records of social and health service usage and RAI-HC (Resident Assessment Instrument - Home Care) assessment system during January 2011 and September 2015. The aim was to find out the most efficient variable subsets to predict NHA for individuals and validate the accuracy. The variable subsets of predicting NHA were searched by sequential forward selection (SFS) method, a variable ranking metric and the classifiers of logistic regression (LR), support vector machine (SVM) and Gaussian naive Bayes (GNB). The validation of the results was guaranteed using randomly balanced data sets and cross-validation. The primary performance metrics for the classifiers were the prediction accuracy and AUC (average area under the curve).The LR and GNB classifiers achieved 78% accuracy for predicting NHA. The most important variables were RAI MAPLE (Method for Assigning Priority Levels), functional impairment (RAI IADL, Activities of Daily Living), cognitive impairment (RAI CPS, Cognitive Performance Scale), memory disorders (diagnoses G30-G32 and F00-F03) and the use of community-based health-service and prior hospital use (emergency visits and periods of care).The accuracy of the classifier for individuals was high enough to convince the officials of the city of Tampere to integrate the predictive model based on the findings of this study as a part of home care information system. Further work need to be done to evaluate variables that are modifiable and responsive to interventions.
| S-EPMC5390435 | biostudies-other