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To evaluate whether incorporating mandatory prior authorization for Clostridioides difficile testing into antimicrobial stewardship pharmacist workflow could reduce testing in patients with alternative etiologies for diarrhea.
Single center, quasi-experimental before-and-after study.
Tertiary-care, academic medical center in Ann Arbor, Michigan.
Adult and pediatric patients admitted between September 11, 2019 and December 10, 2019 were included if they had an order placed for 1 of the following: (1) C. difficile enzyme immunoassay (EIA) in patients hospitalized >72 hours and received laxatives, oral contrast, or initiated tube feeds within the prior 48 hours, (2) repeat molecular multiplex gastrointestinal pathogen panel (GIPAN) testing, or (3) GIPAN testing in patients hospitalized >72 hours.
A best-practice alert prompting prior authorization by the antimicrobial stewardship program (ASP) for EIA or GIPAN testing was implemented. Approval required the provider to page the ASP pharmacist and discuss rationale for testing. The provider could not proceed with the order if ASP approval was not obtained.
An average of 2.5 requests per day were received over the 3-month intervention period. The weekly rate of EIA and GIPAN orders per 1,000 patient days decreased significantly from 6.05 ± 0.94 to 4.87 ± 0.78 (IRR, 0.72; 95% CI, 0.56–0.93; P = .010) and from 1.72 ± 0.37 to 0.89 ± 0.29 (IRR, 0.53; 95% CI, 0.37–0.77; P = .001), respectively.
We identified an efficient, effective C. difficile and GIPAN diagnostic stewardship approval model.
The aim of the current study was to explore the changing interrelationships among clinical variables through the stages of schizophrenia in order to assemble a comprehensive and meaningful disease model.
Twenty-nine centers from 25 countries participated and included 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Multiple linear regression analysis and visual inspection of plots were performed.
The results suggest that with progression stages, there are changing correlations among Positive and Negative Syndrome Scale factors at each stage and each factor correlates with all the others in that particular stage, in which this factor is dominant. This internal structure further supports the validity of an already proposed four stages model, with positive symptoms dominating the first stage, excitement/hostility the second, depression the third, and neurocognitive decline the last stage.
The current study investigated the mental organization and functioning in patients with schizophrenia in relation to different stages of illness progression. It revealed two distinct “cores” of schizophrenia, the “Positive” and the “Negative,” while neurocognitive decline escalates during the later stages. Future research should focus on the therapeutic implications of such a model. Stopping the progress of the illness could demand to stop the succession of stages. This could be achieved not only by both halting the triggering effect of positive and negative symptoms, but also by stopping the sensitization effect on the neural pathways responsible for the development of hostility, excitement, anxiety, and depression as well as the deleterious effect on neural networks responsible for neurocognition.
The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health measures. The success of these policies will largely depend on the public's willingness to comply with new rules. A key factor in citizens’ willingness to comply is their understanding of the data that motivate government action. In this study, we examine how different ways of presenting these data visually can affect citizen's perceptions, attitudes and support for public policy.
Research on psychotic illness is loosening emphasis on diagnostic stringency in favour of including a more dimensionally based conceptualization of psychopathology and pathobiology. However, to clarify these notions requires investigation of the full scope of psychotic diagnoses.
The Cavan–Monaghan First Episode Psychosis Study ascertained cases of first episode psychosis across all 12 DSM-IV psychotic diagnoses via all routes to care: public, private or forensic; home-based, outpatient or inpatient. There was no arbitrary upper age cut-off and minimal impact of factors associated with variations in social milieu, ethnicity or urbanicity. Cases were evaluated epidemiologically and assessed for psychopathology, neuropsychology, neurology, antecedent factors, insight and quality of life.
Among 432 cases, the annual incidence of any DSM-IV psychotic diagnosis was 34.1/100 000 of population and encompassed functional psychotic diagnoses, substance-induced psychopathology and psychopathology due to general medical conditions, through to psychotic illness that defied contemporary diagnostic algorithms. These 12 DSM-IV diagnostic categories, including psychotic disorder not otherwise specified, showed clinical profiles that were consistently more similar than distinct.
There are considerable similarities and overlaps across a broad range of diagnostic categories in the absence of robust discontinuities between them. Thus, psychotic illness may be of such continuity that it cannot be fully captured by operational diagnostic algorithms that, at least in part, assume discontinuities. This may reflect the impact of diverse factors each of which acts on one or more overlapping components of a common, dysfunctional neuronal network implicated in the pathobiology of psychotic illness.
As research into psychotic illness evolves along established lines, insights are emerging that deviate from those lines and challenge more fundamentally our understanding. On the background of a new generation of studies on first-episode psychosis, investigations across the gene–environment interface and the intersection with ‘normal’ human mentation heighten these concerns. Using findings from the Cavan-Monaghan First Episode Psychosis Study (CAMFEPS) as an exemplar, we here review the complexity of these challenges from the perspective of this real-world setting. They range from trans-diagnostic epidemiology and clinical characterisation, through molecular genetics, social milieu, developmental pathobiology and functional outcome across arbitrary diagnostic boundaries, to the evidence base for early intervention and more radical conceptualisations and structures for provision of mental health care.
Culture-based studies, which focus on individual organisms, have implicated stethoscopes as potential vectors of nosocomial bacterial transmission. However, the full bacterial communities that contaminate in-use stethoscopes have not been investigated.
We used bacterial 16S rRNA gene deep-sequencing, analysis, and quantification to profile entire bacterial populations on stethoscopes in use in an intensive care unit (ICU), including practitioner stethoscopes, individual-use patient-room stethoscopes, and clean unused individual-use stethoscopes. Two additional sets of practitioner stethoscopes were sampled before and after cleaning using standardized or practitioner-preferred methods.
Bacterial contamination levels were highest on practitioner stethoscopes, followed by patient-room stethoscopes, whereas clean stethoscopes were indistinguishable from background controls. Bacterial communities on stethoscopes were complex, and community analysis by weighted UniFrac showed that physician and patient-room stethoscopes were indistinguishable and significantly different from clean stethoscopes and background controls. Genera relevant to healthcare-associated infections (HAIs) were common on practitioner stethoscopes, among which Staphylococcus was ubiquitous and had the highest relative abundance (6.8%–14% of contaminating bacterial sequences). Other HAI-related genera were also widespread although lower in abundance. Cleaning of practitioner stethoscopes resulted in a significant reduction in bacterial contamination levels, but these levels reached those of clean stethoscopes in only a few cases with either standardized or practitioner-preferred methods, and bacterial community composition did not significantly change.
Stethoscopes used in an ICU carry bacterial DNA reflecting complex microbial communities that include nosocomially important taxa. Commonly used cleaning practices reduce contamination but are only partially successful at modifying or eliminating these communities.
Adverse exposures during fetal life and the postnatal period influence physical, cognitive and emotional development, and predispose to an increased risk of various chronic diseases throughout the life course. Findings from large observational studies in various populations and experimental animal studies have identified different modifiable risk factors in early life. Adverse maternal lifestyle factors, including overweight, unhealthy diet, sedentary behavior, smoking, alcohol consumption and stress in the preconception period and during pregnancy, are the most common modifiable risk factors leading to a suboptimal in-utero environment for fetal development. In the postnatal period, breastfeeding, infant growth and infant dietary intake are important modifiable factors influencing long-term offspring health outcomes. Despite the large amount of findings from observational studies, translation to lifestyle interventions seems to be challenging. Currently, randomized controlled trials focused on the influence of lifestyle interventions in these critical periods on short-term and long-term maternal and offspring health outcomes are scarce, have major limitations and do not show strong effects on maternal and offspring outcomes. New and innovative approaches are needed to move from describing these causes of ill-health to start tackling them using intervention approaches. Future randomized controlled lifestyle intervention studies and innovative observational studies, using quasi-experimental designs, are needed focused on the effects of an integrated lifestyle advice from preconception onwards on pregnancy outcomes and long-term health outcomes in offspring on a population level.
Long-term forest dynamics plots in the tropics tend to be situated on stable terrain. This study investigated forest dynamics on the north coast of New Guinea where active subduction zones are uplifting lowland basins and exposing relatively young sediments to rapid weathering. We examined forest dynamics in relation to disturbance history, topography and soil nutrients based on partial re-census of the 50-ha Wanang Forest Dynamics Plot in Papua New Guinea. The plot is relatively high in cations and phosphorus but low in nitrogen. Soil nutrients and topography accounted for 29% of variation in species composition but only 4% of variation in basal area. There were few areas of high biomass and most of the forest was comprised of small-diameter stems. Approximately 18% of the forest was less than 30 y old and the annual tree mortality rate of nearly 4% was higher than in other tropical forests in South-East Asia and the neotropics. These results support the reputation of New Guinea's forests as highly dynamic, with frequent natural disturbance. Empirical documentation of this hypothesis expands our understanding of tropical forest dynamics and suggests that geomorphology might be incorporated in models of global carbon storage especially in regions of unstable terrain.
An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. To date, research has focused on developing risk prediction models for CDI that work well across institutions. However, this one-size-fits-all approach ignores important hospital-specific factors. We focus on a generalizable method for building facility-specific models. We demonstrate the applicability of the approach using electronic health records (EHR) from the University of Michigan Hospitals (UM) and the Massachusetts General Hospital (MGH).
We utilized EHR data from 191,014 adult admissions to UM and 65,718 adult admissions to MGH. We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 4,836 features from patients at UM and 1,837 from patients at MGH. We used L2 regularized logistic regression to learn the models, and we measured the discriminative performance of the models on held-out data from each hospital.
Using the UM and MGH test data, the models achieved area under the receiver operating characteristic curve (AUROC) values of 0.82 (95% confidence interval [CI], 0.80–0.84) and 0.75 ( 95% CI, 0.73–0.78), respectively. Some predictive factors were shared between the 2 models, but many of the top predictive factors differed between facilities.
A data-driven approach to building models for estimating daily patient risk for CDI was used to build institution-specific models at 2 large hospitals with different patient populations and EHR systems. In contrast to traditional approaches that focus on developing models that apply across hospitals, our generalizable approach yields risk-stratification models tailored to an institution. These hospital-specific models allow for earlier and more accurate identification of high-risk patients and better targeting of infection prevention strategies.
There is growing interest in linking vitamin D deficiency with autism spectrum disorders (ASDs). The association between vitamin D deficiency during gestation, a critical period in neurodevelopment, and ASD is not well understood.
To determine the association between gestational vitamin D status and ASD.
Based on a birth cohort (n=4334), we examined the association between 25-hydroxyvitamin D (25OHD), assessed from both maternal mid-gestation sera and neonatal sera, and ASD (defined by clinical records; n=68 cases).
Individuals in the 25OHD-deficient group at mid-gestation had more than twofold increased risk of ASD (odds ratio (OR)=2.42, 95% confidence interval (CI) 1.09 to 5.07, P=0.03) compared with the sufficient group. The findings persisted in analyses including children of European ethnicity only.
Mid-gestational vitamin D deficiency was associated with an increased risk of ASD. Because gestational vitamin D deficiency is readily preventable with safe, inexpensive and readily available supplementation, this risk factor warrants closer scrutiny.
There has been much recent excitement about the possibility that some cases of psychosis may be wholly due to brain-reactive antibodies, with antibodies to N-methyl-D-aspartate receptor (NMDAR) and the voltage-gated potassium channel (VGKC)-complex reported in a few patients with first-episode psychosis (FEP).
Participants were recruited from psychiatric services in South London, UK, from 2009 to 2011 as part of the Genetics and Psychosis study. We conducted a case–control study to examine NMDAR and VGKC-complex antibody levels and rates of antibody positivity in 96 patients presenting with FEP and 98 controls matched for age and sex. Leucine-rich glioma inactiviated-1 (LGI1) and contactin-associated protein (CASPR) antibodies were also measured. Notably, patients with suspicion of organic disease were excluded.
VGKC-complex antibodies were found in both cases (n = 3) and controls (n = 2). NMDAR antibody positivity was seen in one case and one control. Either LGI1-Abs or CASPR2-Abs were found in three cases and three controls. Neuronal antibody staining, consistent with the above results or indicating potential novel antigens, was overall positive in four patients but also in six controls. Overall, antibody positivity was at low levels only and not higher in cases than in controls.
This case–control study of the prevalence of antibodies in FEP does not provide evidence to support the hypothesis that FEP is associated with an immune-mediated process in a subgroup of patients. Nevertheless, as other bio-clinical factors may influence the effect of such antibodies in a given individual, and patients with organic neurological disease may be misdiagnosed as FEP, the field requires more research to put these findings in context.
Predicting recurrent Clostridium difficile infection (rCDI) remains difficult. METHODS. We employed a retrospective cohort design. Granular electronic medical record (EMR) data had been collected from patients hospitalized at 21 Kaiser Permanente Northern California hospitals. The derivation dataset (2007–2013) included data from 9,386 patients who experienced incident CDI (iCDI) and 1,311 who experienced their first CDI recurrences (rCDI). The validation dataset (2014) included data from 1,865 patients who experienced incident CDI and 144 who experienced rCDI. Using multiple techniques, including machine learning, we evaluated more than 150 potential predictors. Our final analyses evaluated 3 models with varying degrees of complexity and 1 previously published model.
Despite having a large multicenter cohort and access to granular EMR data (eg, vital signs, and laboratory test results), none of the models discriminated well (c statistics, 0.591–0.605), had good calibration, or had good explanatory power.
Our ability to predict rCDI remains limited. Given currently available EMR technology, improvements in prediction will require incorporating new variables because currently available data elements lack adequate explanatory power.