Effect of mycophenolate mofetil on the white blood cell count and the frequency of infection in systemic lupus erythematosus.

Leukopenia is a common manifestation of SLE. Addition of immunosuppressive therapy in a SLE patient who is already leukopenic is a clinical concern. It could worsen leukopenia, increase the risk of infection, or both. The aim of this study was to analyze the immediate effect of mycophenolate mofetil on the white blood cell count and the rate of infection in SLE patients. Two hundred and forty-four patients within the Hopkins Lupus Cohort who were newly started on mycophenolate mofetil were included in the study. The white blood cell count and interval infection history on the day mycophenolate mofetil was started were compared with the white blood cell count and interval infection history at the next visit. The study was based on 244 patients who began taking mycophenolate mofetil in the cohort. The study population included 47 % African Americans, 44 % Caucasians, and 9 % other ethnicities. There was a slight but not statistically significant increase in the white blood cell count (6.63 vs. 7.01), after starting mycophenolate mofetil. Patients with a baseline white blood cell count \u3c3000/mm(3) did have a statistically significant increase in the white blood cell count after starting mycophenolate mofetil (2.57 vs. 5.13, P = 0.0047). We also found a statistically significant increase in the risk of bacterial infection (but not viral infection) after starting mycophenolate mofetil (4 vs. 9 %, P = 0.0036). Leukopenia does not worsen with mycophenolate mofetil. However, mycophenolate mofetil appears to slightly increase the rate of bacterial (but not viral) infection

The effect of adding comorbidities to current centers for disease control and prevention central-line–associated bloodstream infection risk-adjustment methodology

BACKGROUNDRisk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.METHODSUsing a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.RESULTSOverall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.CONCLUSIONSOur risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.Infect Control Hosp Epidemiol 2017;38:1019–1024</jats:sec

Electronically available patient claims data improve models for comparing antibiotic use across hospitals: Results from 576 US facilities

BACKGROUND: The Centers for Disease Control and Prevention (CDC) uses standardized antimicrobial administration ratios (SAARs)-that is, observed-to-predicted ratios-to compare antibiotic use across facilities. CDC models adjust for facility characteristics when predicting antibiotic use but do not include patient diagnoses and comorbidities that may also affect utilization. This study aimed to identify comorbidities causally related to appropriate antibiotic use and to compare models that include these comorbidities and other patient-level claims variables to a facility model for risk-adjusting inpatient antibiotic utilization. METHODS: The study included adults discharged from Premier Database hospitals in 2016-2017. For each admission, we extracted facility, claims, and antibiotic data. We evaluated 7 models to predict an admission\u27s antibiotic days of therapy (DOTs): a CDC facility model, models that added patient clinical constructs in varying layers of complexity, and an external validation of a published patient-variable model. We calculated hospital-specific SAARs to quantify effects on hospital rankings. Separately, we used Delphi Consensus methodology to identify Elixhauser comorbidities associated with appropriate antibiotic use. RESULTS: The study included 11 701 326 admissions across 576 hospitals. Compared to a CDC-facility model, a model that added Delphi-selected comorbidities and a bacterial infection indicator was more accurate for all antibiotic outcomes. For total antibiotic use, it was 24% more accurate (respective mean absolute errors: 3.11 vs 2.35 DOTs), resulting in 31-33% more hospitals moving into bottom or top usage quartiles postadjustment. CONCLUSIONS: Adding electronically available patient claims data to facility models consistently improved antibiotic utilization predictions and yielded substantial movement in hospitals\u27 utilization rankings

Significant regional differences in antibiotic use across 576 US hospitals and 11 701 326 adult admissions, 2016-2017

BACKGROUND: Quantifying the amount and diversity of antibiotic use in United States hospitals assists antibiotic stewardship efforts but is hampered by limited national surveillance. Our study aimed to address this knowledge gap by examining adult antibiotic use across 576 hospitals and nearly 12 million encounters in 2016-2017. METHODS: We conducted a retrospective study of patients aged ≥ 18 years discharged from hospitals in the Premier Healthcare Database between 1 January 2016 and 31 December 2017. Using daily antibiotic charge data, we mapped antibiotics to mutually exclusive classes and to spectrum of activity categories. We evaluated relationships between facility and case-mix characteristics and antibiotic use in negative binomial regression models. RESULTS: The study included 11 701 326 admissions, totaling 64 064 632 patient-days, across 576 hospitals. Overall, patients received antibiotics in 65% of hospitalizations, at a crude rate of 870 days of therapy (DOT) per 1000 patient-days. By class, use was highest among β-lactam/β-lactamase inhibitor combinations, third- and fourth-generation cephalosporins, and glycopeptides. Teaching hospitals averaged lower rates of total antibiotic use than nonteaching hospitals (834 vs 957 DOT per 1000 patient-days; P \u3c .001). In adjusted models, teaching hospitals remained associated with lower use of third- and fourth-generation cephalosporins and antipseudomonal agents (adjusted incidence rate ratio [95% confidence interval], 0.92 [.86-.97] and 0.91 [.85-.98], respectively). Significant regional differences in total and class-specific antibiotic use also persisted in adjusted models. CONCLUSIONS: Adult inpatient antibiotic use remains high, driven predominantly by broad-spectrum agents. Better understanding reasons for interhospital usage differences, including by region and teaching status, may inform efforts to reduce inappropriate antibiotic prescribing

Survival associated pathway identification with group Lp penalized global AUC maximization

It has been demonstrated that genes in a cell do not act independently. They interact with one another to complete certain biological processes or to implement certain molecular functions. How to incorporate biological pathways or functional groups into the model and identify survival associated gene pathways is still a challenging problem. In this paper, we propose a novel iterative gradient based method for survival analysis with group Lp penalized global AUC summary maximization. Unlike LASSO, Lp (p < 1) (with its special implementation entitled adaptive LASSO) is asymptotic unbiased and has oracle properties [1]. We first extend Lp for individual gene identification to group Lp penalty for pathway selection, and then develop a novel iterative gradient algorithm for penalized global AUC summary maximization (IGGAUCS). This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes. The tuning parameters are determined using 10-fold cross validation with training data only. The prediction performance is evaluated using test data. We apply the proposed method to survival outcome analysis with gene expression profile and identify multiple pathways simultaneously. Experimental results with simulation and gene expression data demonstrate that the proposed procedures can be used for identifying important biological pathways that are related to survival phenotype and for building a parsimonious model for predicting the survival times

Age-Associated Heterogeneity of Ty21a-Induced T Cell Responses to HLA-E Restricted Salmonella Typhi Antigen Presentation

Human-restricted Salmonella enterica serovar Typhi (S. Typhi) is the causative agent of typhoid fever—a life-threatening disease of great global health significance, particularly in the developing world. Ty21a is an oral live-attenuated vaccine that protects against the development of typhoid disease in part by inducing robust T cell responses, among which multifunctional CD8+ cytotoxic T lymphocytes (CTL) play an important role. Following Ty21a vaccination, a significant component of adult CTL have shown to be targeted to S. Typhi antigen presented by the conserved major histocompatibility complex (MHC) class Ib molecule, human leukocyte antigen-E (HLA-E). S. Typhi challenge studies have shown that baseline, multifunctional HLA-E responsive T cells are associated with protection from, and delayed onset of, typhoid disease. However, despite the overwhelming burden of typhoid fever in school-aged children, and due to limited availability of pediatric samples, incomplete information is available regarding these important HLA-E-restricted responses in children, even though studies have shown that younger children may be less likely to develop protective cell mediated immune (CMI) responses than adults following vaccination. To address this gap, we have studied this phenomenon in depth by using mass cytometry to analyze pediatric and adult T cell responses to HLA-E-restricted S. Typhi antigen presentation, before and after Ty21a vaccination. Herein, we show variable responses in all age strata following vaccination among T effector memory (TEM) and T effector memory CD45RA+ (TEMRA) cells based on conventional gating analysis. However, by utilizing the dimensionality reduction tool tSNE (t-distributed Stochastic Neighbor Embedding), we are able to identify diverse, highly multifunctional gut-homing- TEM and TEMRA clusters of cells which are more abundant in adult and older pediatric participants than in younger children. These findings highlight a potential age-associated maturation of otherwise conserved HLA-E restricted T cell responses. Such insights, coupled with the marked importance of multifunctional T cell responses to combat infection, may better inform future pediatric vaccination strategies against S. Typhi and other infectious diseases

Microbiota that affect risk for shigellosis in children in low-income countries

Pathogens in the gastrointestinal tract exist within a vast population of microbes. We examined associations between pathogens and composition of gut microbiota as they relate to Shigella spp./enteroinvasive Escherichia coli infection. We analyzed 3,035 stool specimens (1,735 nondiarrheal and 1,300 moderate-to-severe diarrheal) from the Global Enteric Multicenter Study for 9 enteropathogens. Diarrheal specimens had a higher number of enteropathogens (diarrheal mean 1.4, nondiarrheal mean 0.95; p<0.0001). Rotavirus showed a negative association with Shigella spp. in cases of diarrhea (odds ratio 0.31, 95% CI 0.17–0.55) and had a large combined effect on moderate-to-severe diarrhea (odds ratio 29, 95% CI 3.8–220). In 4 Lactobacillus taxa identified by 16S rRNA gene sequencing, the association between pathogen and disease was decreased, which is consistent with the possibility that Lactobacillus spp. are protective against Shigella spp.–induced diarrhea. Bacterial diversity of gut microbiota was associated with diarrhea status, not high levels of the Shigella spp. ipaH gene.publishedVersio

Statewide Molecular Epidemiology of Mycobacterium tuberculosis Transmission in a Moderate- to Low-Incidence State: Are Contact Investigations Enough?

To assess the circumstances of recent transmission of tuberculosis (TB) (progression to active disease <2 years after infection), we obtained DNA fingerprints for 1,172 (99%) of 1,179 Mycobacterium tuberculosis isolates collected from Maryland TB patients from 1996 to 2000. We also reviewed medical records and interviewed patients with genetically matching M. tuberculosis strains to identify epidemiologic links (cluster investigation). Traditional settings for transmission were defined as households or close relatives and friends; all other settings were considered nontraditional. Of 436 clustered patients, 114 had recently acquired TB. Cluster investigations were significantly more likely than contact investigations to identify patients who recently acquired TB in nontraditional settings (33/42 vs. 23/72, respectively; p<0.001). Transmission from a foreign-born person to a U.S.-born person was rare and occurred mainly in public settings. The time from symptom onset to diagnosis was twice as long for transmitters as for nontransmitters (16.8 vs. 8.5 weeks, respectively; p<0.01). Molecular epidemiologic studies showed that eliminating diagnostic delays can prevent TB transmission in nontraditional settings, which elude contact investigations

Brugia malayi microfilariae adhere to human vascular endothelial cells in a C3-dependent manner

Brugia malayi causes the human tropical disease, lymphatic filariasis. Microfilariae (Mf) of this nematode live in the bloodstream and are ingested by a feeding mosquito vector. Interestingly, in a remarkable co-evolutionary adaptation, Mf appearance in the peripheral blood follows a circadian periodicity and reaches a peak when the mosquito is most likely to feed. For the remaining hours, the majority of Mf sequester in the lung capillaries. This circadian phenomenon has been widely reported and is likely to maximise parasite fitness and optimise transmission potential. However, the mechanism of Mf sequestration in the lungs remains largely unresolved. In this study, we demonstrate that B. malayi Mf can, directly adhere to vascular endothelial cells under static conditions and under flow conditions, they can bind at high (but not low) flow rates. High flow rates are more likely to be experienced diurnally. Furthermore, a non-periodic nematode adheres less efficiently to endothelial cells. Strikingly C3, the central component of complement, plays a crucial role in the adherence interaction. These novel results show that microfilariae have the ability to bind to endothelial cells, which may explain their sequestration in the lungs, and this binding is increased in the presence of inflammatory mediators