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Background The optimal diagnostic strategy for Clostridium difficile infection (CDI) is not known, and no test is shown to clearly differentiate colonization from symptomatic infection. We hypothesized that detection and/or quantification of stool toxins would associate with severe disease and adverse outcomes. Methods We conducted a retrospective cohort study among subjects with CDI diagnosed in 2016 at the University of Michigan. The clinical microbiology laboratory tested for glutamate dehydrogenase antigen and toxins A/B by enzyme immunoassay (EIA). Discordant results reflexed to PCR for the tcdB gene. Stool toxin levels were quantified via a modified cell cytotoxicity assay (CCA). C. difficile was isolated by anaerobic culture and ribotyped. Severe CDI was defined by the IDSA criteria: white blood cell count >15,000 cells/µL or a 1.5-fold increase in serum creatinine above baseline. The primary outcomes were all-cause 30-day mortality and a composite of colectomy, ICU admission, and/or death attributable to CDI within 30 days. Analysis included standard bivariable tests and adjusted models via logistic regression. Results From 565 adult patients, we obtained 646 samples; 199 (30.8%) contained toxins by EIA. Toxin positivity associated with IDSA severity (Table 1), but not our primary outcomes on unadjusted analysis. After adjustment for putative confounders, we still did not observe an association between toxin positivity and our primary outcomes. Stool toxin levels by CCA >6.4 ng/mL associated with IDSA severity (Table 1), but not the primary outcomes. Compared with the period from 2010 to 2013, the circulating ribotypes of C. difficile at our institution changed in 2016. Notably ribotype 106 newly emerged, accounting for 10.6% of strains, and ribotype 027 fell to 9.3% (Table 2). The incidence of ribotype 014-027 has remained stable at 18.9%, but this strain was associated with both IDSA severity and 30-day mortality (OR = 3.32; P = 0.001). Conclusion Toxin detection by EIA/CCA associated with IDSA severity, but this study was unable to confirm an association with subsequent adverse outcomes. The molecular epidemiology of C. difficile has shifted, and this may have implications for the optimal diagnostic strategy for CDI. Disclosures All authors: No reported disclosures.

Background Annually in the US alone, Clostridioides difficile infection (CDI) afflicts nearly 500,000 patients causing 29,000 deaths. Since early and aggressive interventions could save lives but are not optimally deployed in all patients, numerous studies have published predictive models for adverse outcomes. These models are usually developed at a single institution, and largely are not externally validated. This aim of this study was to validate the predictability for severe CDI with previously published risk scores in a multicenter cohort of patients with CDI. Methods We conducted a retrospective study on four separate inpatient cohorts with CDI from three distinct sites: the Universities of Michigan (2010–2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive test. Structured query and manual chart review abstracted data from the medical record at each site. Published CDI severity scores were assessed and compared with each other and the IDSA guideline definition of severe CDI. Sensitivity, specificity, area under the receiver operator characteristic curve (AuROC), precision-recall curves, and net reclassification index (NRI) were calculated to compare models. Results We included 3,775 patients from the four cohorts (Table 1) and evaluated eight severity scores (Table 2). The IDSA (baseline comparator) model showed poor performance across cohorts(Table 3). Of the binary classification models, including those that were most predictive of the primary composite outcome, Jardin, performed poorly with minimal to no NRI improvement compared with IDSA. The continuous score models, Toro and ATLAS, performed better, but the AuROC varied by site by up to 17% (Table 3). The Gujja model varied the most: from most predictive in the University of Michigan 2010–2012 cohort to having no predictive value in the 2016 cohort (Table 3). Conclusion No published CDI severity score showed stable, acceptable predictive ability across multiple cohorts/institutions. To maximize performance and clinical utility, future efforts should focus on a multicenter-derived and validated scoring system, and/or incorporate novel biomarkers. Disclosures All authors: No reported disclosures.

Background Clostridium difficile infection (CDI) can result in severe disease and death. We are currently unable to identify patients at risk for developing adverse outcomes. We previously showed multiple inflammatory mediators were associated with severity and adverse outcomes. Here, we set out to validate these findings in patients and a murine model of CDI. Methods CDI was diagnosed by the clinical microbiology laboratory. Sera were collected ≤48 hours after diagnosis from pilot (October 2010–November 2012) and validation (January–September 2016) cohorts. Inflammatory mediators were measured with a custom multiplex assay. IDSA severity was defined as serum creatinine >1.5-fold above baseline or white blood cell count >15,000 cells/mL. The 30-day outcomes were all-cause mortality and disease-related complications (DRCs): ICU admission, colectomy, or death attributed to CDI. We sought to validate our patient findings in a murine model of CDI: 67 antibiotic-treated mice were infected with 630 g (37 mice), a low virulence strain, or VPI 10463 (30 mice), a highly virulent strain. Host responses were assessed with a murine version of the multiplex panel. Unadjusted and adjusted models were built using logistic and L1 regression, respectively. Results The pilot cohort had 156 CDI cases; 63 (40%) with IDSA severity. The inflammatory response in IDSA severe cases was distinct based on redundancy analysis of all measured analytes (P = 0.01). In unadjusted analysis, IL-2R, IL-6, and procalcitonin associated with severity (P < 0.001, P = 0.003, and P = 0.003, respectively). The same findings were seen in the validation cohort of 272 cases (Figure 1). Unadjusted analyses revealed several predictors of severity and outcomes (Table 1). Adjusted models performed well (Figure 2) with AUCs of 0.74 [0.67–0.81] (IDSA severity), 0.89 [0.83–0.95] (death), and 0.84 [0.74–0.95] (DRCs). Application of each model to the mouse cohort for high vs. low virulence infections revealed AUCs of 0.59 [0.44–0.74], 0.96 [0.90–1.0], and 0.89 [0.81–0.97] (Figure 3). Conclusion In both humans and a murine CDI model, a panel of biomarkers from sera associated with severe CDI and predicted adverse outcomes. Our results support the possibility of a serum-based biomarker panel to inform medical decision-making for patients with CDI. Disclosures All Authors: No reported Disclosures.

Public Act 8849 entitled \"Connecticut Solid Waste Management Services Act\" has been relatively obscured by statewide debates on the Hospital Cost Commission, the Abortion Issue and the Drunk Driver Bill. Yet, the price tag on bill 8849 has...

AbstractObjectivesTo summarise and compare the accuracy of physical examination, computed tomography (CT), sonography of the optic nerve sheath diameter (ONSD), and transcranial Doppler pulsatility index (TCD-PI) for the diagnosis of elevated intracranial pressure (ICP) in critically ill patients.DesignSystematic review and meta-analysis.Data sourcesSix databases, including Medline, EMBASE, and PubMed, from inception to 1 September 2018.Study selection criteriaEnglish language studies investigating accuracy of physical examination, imaging, or non-invasive tests among critically ill patients. The reference standard was ICP of 20 mm Hg or more using invasive ICP monitoring, or intraoperative diagnosis of raised ICP.Data extractionTwo reviewers independently extracted data and assessed study quality using the quality assessment of diagnostic accuracy studies tool. Summary estimates were generated using a hierarchical summary receiver operating characteristic (ROC) model.Results40 studies (n=5123) were included. Of physical examination signs, pooled sensitivity and specificity for increased ICP were 28.2% (95% confidence interval 16.0% to 44.8%) and 85.9% (74.9% to 92.5%) for pupillary dilation, respectively; 54.3% (36.6% to 71.0%) and 63.6% (46.5% to 77.8%) for posturing; and 75.8% (62.4% to 85.5%) and 39.9% (26.9% to 54.5%) for Glasgow coma scale of 8 or less. Among CT findings, sensitivity and specificity were 85.9% (58.0% to 96.4%) and 61.0% (29.1% to 85.6%) for compression of basal cisterns, respectively; 80.9% (64.3% to 90.9%) and 42.7% (24.0% to 63.7%) for any midline shift; and 20.7% (13.0% to 31.3%) and 89.2% (77.5% to 95.2%) for midline shift of at least 10 mm. The pooled area under the ROC (AUROC) curve for ONSD sonography was 0.94 (0.91 to 0.96). Patient level data from studies using TCD-PI showed poor performance for detecting raised ICP (AUROC for individual studies ranging from 0.55 to 0.72).ConclusionsAbsence of any one physical examination feature is not sufficient to rule out elevated ICP. Substantial midline shift could suggest elevated ICP, but the absence of shift cannot rule it out. ONSD sonography might have use, but further studies are needed. Suspicion of elevated ICP could necessitate treatment and transfer, regardless of individual non-invasive tests.RegistrationPROSPERO CRD42018105642.

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of “lifestyle” diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be “mismatched” and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit “genotype by environment” (GxE) interactions, with different health effects in “ancestral” versus “modern” environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the “matched” to “mismatched” spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.

The severity of allergic asthma is driven by the balance between allergen-specific T regulatory (Treg) and T helper (Th)2 cells. However, it is unclear whether specific subsets of conventional dendritic cells (cDCs) promote the differentiation of Tregs. We have identified a subset of lung resident type 2 cDCs (cDC2s) that display high levels of CD301b and have potent Treg-inducing activity ex vivo. Single-cell RNA sequencing and adoptive transfer experiments show that during allergic sensitization, many CD301b + cDC2s transition in a stepwise manner to CD200 + cDC2s that selectively promote Th2 differentiation. GM-CSF augments the development and maintenance of CD301b + cDC2s in vivo, and also selectively expands Treg-inducing CD301b + cDC2s derived from bone marrow. Upon their adoptive transfer to recipient mice, lung-derived CD301b + cDC2s confer immunological tolerance to inhaled allergens. Thus, GM-CSF maintains lung homeostasis by increasing numbers of Treg-inducing CD301b + cDC2s. Distinct subsets of conventional DCs (cDCs) promote the differentiation of distinct helper T cell lineages. Here, the authors identify a GM-CSF-dependent cDC2 population in the mouse lung that expresses CD301b at steady state and promotes the differentiation of Treg cells, whereas during the initiation of allergic responses, these cDC2s transition to CD200 +  cDC2s, promoting Th2 differentiation.

Background Mammalian cells are flexible and can rapidly change shape when they contract, adhere, or migrate. The nucleus must be stiff enough to withstand cytoskeletal forces, but flexible enough to remodel as the cell changes shape. This is particularly important for cells migrating through confined spaces, where the nuclear shape must change in order to fit through a constriction. This occurs many times in the life cycle of a neutrophil, which must protect its chromatin from damage and disruption associated with migration. Here we characterized the effects of constricted migration in neutrophil-like cells. Results Total RNA sequencing identified that migration of neutrophil-like cells through 5- or 14-μm pores was associated with changes in the transcript levels of inflammation and chemotaxis-related genes when compared to unmigrated cells. Differentially expressed transcripts specific to migration with constriction were enriched for groups of genes associated with cytoskeletal remodeling. Hi-C was used to capture the genome organization in control and migrated cells. Limited switching was observed between the active (A) and inactive (B) compartments after migration. However, global depletion of short-range contacts was observed following migration with constriction compared to migration without constriction. Regions with disrupted contacts, TADs, and compartments were enriched for inactive chromatin. Conclusion Short-range genome organization is preferentially altered in inactive chromatin, possibly protecting transcriptionally active contacts from the disruptive effects of migration with constriction. This is consistent with current hypotheses implicating heterochromatin as the mechanoresponsive form of chromatin. Further investigation concerning the contribution of heterochromatin to stiffness, flexibility, and protection of nuclear function will be important for understanding cell migration in relation to human health and disease.

The kidneys facilitate energy conservation through reabsorption of nutrients including glucose. Almost all the filtered blood glucose is reabsorbed by the kidneys. Loss of glucose in urine (glycosuria) is offset by an increase in endogenous glucose production to maintain normal energy supply in the body. How the body senses this glucose loss and consequently enhances glucose production is unclear. Using renal Slc2a2 (also known as Glut2 ) knockout mice, we demonstrate that elevated glycosuria activates the hypothalamic-pituitary-adrenal axis, which in turn drives endogenous glucose production. This phenotype was attenuated by selective afferent renal denervation, indicating the involvement of the afferent nerves in promoting the compensatory increase in glucose production. In addition, through plasma proteomics analyses we observed that acute phase proteins - which are usually involved in the body’s defense mechanisms against a threat – were the top candidates which were either upregulated or downregulated in renal Slc2a2 KO mice. Overall, afferent renal nerves contribute to promoting endogenous glucose production in response to elevated glycosuria and loss of glucose in urine is sensed as a biological threat in mice. These findings may be useful in improving the efficiency of drugs like SGLT2 inhibitors that are intended to treat hyperglycemia by enhancing glycosuria but are met with a compensatory increase in endogenous glucose production.

Wildfires statistics for the conterminous United States (U.S.) are examined in a spatially and temporally explicit manner. We use a high-resolution data set consisting of 88,916 U.S. Department of Agriculture Forest Service wildfires over the time period 1970-2000 and consider wildfire occurrence as a function of ecoregion (land units classified by climate, vegetation, and topography), ignition source (anthropogenic vs. lightning), and decade. For the conterminous U.S., we (i) find that wildfires exhibit robust frequency-area power-law behavior in 18 different ecoregions; (ii) use normalized power-law exponents to compare the scaling of wildfire-burned areas between ecoregions, finding a systematic change from east to west; (iii) find that wildfires in the eastern third of the U.S. have higher power-law exponents for anthropogenic vs. lightning ignition sources; and (iv) calculate recurrence intervals for wildfires of a given burned area or larger for each ecoregion, allowing for the classification of wildfire regimes for probabilistic hazard estimation in the same vein as is now used for earthquakes.