Frequent users of hospital emergency departments (EDs) are a medically and socially vulnerable population. The Coordinated Access to Care from Hospital EDs (CATCH-ED) study examined the effectiveness of a brief case management intervention in reducing ED use and improving health outcomes among frequent ED users with mental health or addiction challenges in a large urban centre. Adults (≥18 years of age) who had five or more ED visits in the past 12-months, with at least one visit for mental health or addictions problems were randomized to either brief case management (N = 83) or usual care (N = 83) and followed for 12 months. The primary outcome of effectiveness was the frequency of ED visits during 12 months after study enrolment. Secondary outcomes included days in hospital, mental health and addiction symptom severity and health-related quality of life, measured by the SF-12. Compared to usual care, CATCH-ED participants saw a 14% reduction in frequency of ED visits during the 12-month post-randomization period , however, this finding did not reach statistical significance. There were also no statistically significant differences between the groups at 12 months in the number of days spent in hospital , physical  or mental  component scores of the SF-12, severity of psychiatric symptoms , alcohol (0.053 95% -0.017–0.12) or drug  use. Compared to usual care, a brief case management intervention did not result in significantly reduced ED use or improved health outcomes among frequent ED users with mental health or addictions challenges in a large urban centre in Canada. Future studies need to evaluate the availability and accessibility of community-based resources for individuals with frequent ED use. Frequent users of emergency departments (EDs), often defined as those with four or more visits in a year , comprisMany jurisdictions have implemented interventions to reduce frequent ED use in effort to reduce costs and improve health outcomes for this population. To date, case management has been the most studied intervention for frequent ED users , 14, resThe goal of the CATCH-ED trial was to assess the effectiveness of brief intensive case management in reducing ED utilization among frequent ED users with mental health or addiction challenges, in Toronto, Canada, over 12 months of follow up. Secondary outcomes of interest included days in hospital, physical and mental health status, alcohol and drug use. Exploratory outcomes included disease-specific quality of life and the number of hospital admissions. We hypothesized that brief intensive case management would lead to reduced acute health care use and improved health outcomes in this population, when compared to usual care.We conducted a non-blinded parallel-group randomised controlled trial of a brief intensive case management intervention for frequent ED users implemented across 6 EDs in Toronto, Canada. Participants were recruited from November 2012 and September 2013 and followed for 12 months. The study protocol  was apprToronto is Canada’s largest city, with 2.6 million residents in 2011 . Access Study participants were identified by ED clinicians at participating hospitals either via frequent user lists or automated flagging systems, and referred to the study team with participant consent. Study eligibility was further assessed by a member of the research team, who obtained written informed consent from eligible participants prior to study enrolment. Study eligibility criteria included: adult age (≥ 18 years of age), a history of 5 or more ED visits in the past year to any one of 6-participating hospital EDs and at least one ED visits in the past year for a mental health or addictions-related condition. Participants who had a history of 5 or more ED visits in the past but did not have at least one visits for a mental health or addictions-related condition were excluded. All study participants provided written informed consent.Randomization was performed upon completion of the eligibility screening and baseline interviews using a computer connected to the study data coordination centre. The participants’ allocation was communicated to participants as it was revealed, and those randomized to the intervention group were immediately referred to a CATCH-ED case manager. Block randomization was utilized, with a 1:1 allocation ratio and randomly selected block sizes, to maintain balance in the allocation of participants to the treatment groups at intermediate points in the recruitment process . AlthougParticipants who met study inclusion criteria were randomly assigned to the CATCH-ED intervention or a usual care group and met with a member of the research team to complete a series of questionnaires at 3-month intervals over 12 months. Participant responses were uploaded to the data coordinating centre’s secure server, using tablet computers. Participant interviews were conducted in various locations, based on participant preference, including the research team’s office, service provider locations and public settings.Participant interviews alternated between longer interviews at baseline, 6- and 12- months (approximately one hour) and shorter interviews at 3- and 9-months (approximately 15 min). In months without a scheduled interview, participants were contacted for a very brief monthly check-in. Participants were compensated with a cash honorarium ($25–50) and transit fare upon completion of each follow-up interview. To improve retention, participants were asked to provide current contact information for family members, friends and service providers, at each contact point.Participants randomized to the intervention group were connected to CATCH-ED case managers, seconded from three community mental health agencies in Toronto. Case managers had access to a range of dedicated community support options, including primary care, peer support, mental health and addictions counselling, and other health and social services as needed, through partnerships with four community health centres and one peer outreach agency. A CATCH-ED program manager supervised case managers and ensured they maintained small caseloads of approximately 15 clients each. The CATCH-ED intervention was informed by the Critical Time Intervention (CTI) model , 24, an All participants, including usual care participants, received an education session and a resource guide that described available community-based services and resources, which they were able to access at their discretion.The primary outcome measure was the frequency of ED visits during the 12-month period following randomization. Secondary outcomes assessed at 12 months included past month mental health symptom severity, measured by the modified Colorado Symptom Index ; alcoholAll health care use outcomes  were analysed for consenting participants using administrative data held at the Institute of Clinical Evaluative Sciences (ICES). All other participant outcomes used participant self-report data captured during interviews with research staff.More detailed descriptions of the measures are found elsewhere .To account for the over-dispersed distribution of our primary outcome, as well as the natural reduction in ED visits over time, sample size was calculated using the usual care group outcomes of a previously published randomized controlled trial of case management among frequent ED users (≥5 visits/year) . Using pData was analysed using the intent-to-treat principle. Of the 166 participants enrolled in the study, 160 (96%) gave consent to access their administrative health data records, of whom 159 were successfully linked  using personal health identifiers (unique OHIP numbers or name and date of birth). Count outcomes included administrative health care use data  which were modelled using an analysis of covariance framework that compared the number of outcome events in the CATCH-ED group compared to the TAU group during the 12-month post-randomization period, adjusting for baseline number of events accrued in the 12-month pre-randomization period, as well as participant age and sex. Models used a negative binomial distribution due to the over-dispersion of the data (variance greater than the mean) and generated rate ratios (RR) and their 95% CI for the 12-month post-randomization period. Rate ratios calculated the ratio of the estimated frequency of CATCH-ED events divided by the frequency of TAU events for the 12-month post-randomization period, adjusting for baseline frequencies.Normally distributed outcomes included self-reported continuous secondary and exploratory outcomes which approximated the normal distribution  were analysed using an analysis of covariance framework to model difference in means (95% CI) between CATCH-ED and TAU groups at 12-month post-randomization, adjusting for baseline values.https://www.r-project.org/). Significance level for all tests was set at 5%.All analyses were completed using R  = 0.86, 95% CI 0.64–1.15)], adjusting for baseline values, age and sex. This reduction did not reach statistical significance P = 0.31)  during the 12-month post-randomization period did not differ statistically between the intervention and TAU group (RR = 1.16 95% CI 0.59–2.29).There were no statistically significant differences between the groups at 12 months for SF-12 physical  or mental  component scores, the overall health VAS of the EQ-5D  and the severity of psychiatric symptoms , adjusted for their corresponding baseline values. Similarly, there was no significant reduction in the severity of alcohol use or drug use, either when including all participants  or when limiting analyses only to participants with ASI scores greater than zero on alcohol and drug use scales , adjusting for baseline values.Neither the frequency of hospital admissions (RR = 0.78 95% CI 0.46–1.30) nor the number of visits to primary care providers  differed by allocation group at 12-months post-randomization. Compared to TAU, CATCH-ED participants saw a reduction in disease-specific quality of life  , however, this instrument had a substantial number of missing data  and should be considered cautiously. Due to the extent of missing item-level data, the analysis was repeated with the global indicator (“How do you feel about your life as a whole?”), which has a reliability coefficient α >0.90 with the 20-item scale [Our study found that after 12 months, frequent ED users with mental health conditions who received a brief intensive case management intervention had a 14% decrease in ED visits compared to those who received usual care, however, this decrease was not statistically significant. We also did not observe statistically significant differences between intervention and usual care participant groups for any other service use or health related secondary or exploratory outcome. The finding of a reduction in disease specific  quality of life, which decreased in the intervention compared to usual care group, should be interpreted with caution given the extent of missing data for this outcome.Our findings are supported by a recent systematic review and meta-analysis, noting that care coordination strategies, including case management, are not effective in reducing hospital use among adults with mental illness . Nonethehomeless adults when provided at the point of discharge from various institutions, perhaps because these participants were specifically lacking connections to community-based resources. In contrast, community-dwelling frequent-ED users who are already well-connected to health and social services, including primary care [The lack of consistent findings by this and earlier studies suggests the need to re-examine the use of targeted case management interventions for frequent ED-user populations. Firstly, not all frequent ED use may be preventable or inappropriate , 7, and ary care , may notary care . Roland ary care , questioary care .Our study is not without limitations. Firstly, due to the nature of the intervention, participants and research staff were not blinded to treatment allocation. Secondly, the intervention’s effectiveness was assessed at 12-months, which may not have been long enough for potential benefits to show group differences in this population. However, an earlier trial demonstrated cost-effectiveness of case management for frequent ED users at both 12- and 24-months .In conclusion, we found that compared to usual care, a brief intensive case management intervention did not result in reduced ED use among a population of frequent ED users with mental illness or addictions in Toronto, Canada. Future studies need to examine the availability, accessibility and appropriateness of existing community based services for people with complex health, mental health or addiction needs.S1 File(DOC)Click here for additional data file.S1 Table(DOC)Click here for additional data file.


GCLC , the gene of limiting synthesizing enzyme for GSH, are both associated with schizophrenia. In the present study, we aimed at determining if xCT regulation by the redox system is involved in schizophrenia pathophysiology. We assessed whether modulating GCLC expression impact on xCT expression and activity (i) in fibroblasts from patients and controls with different GCLC genotypes which are known to affect GCLC regulation and GSH levels; (ii) in rat brain glial cells, i.e., astrocytes and oligodendrocytes, with a knock-down of GCLC. Our results highlight that decreased GCLC expression leads to an upregulation of xCT levels in patients’ fibroblasts as well as in astrocytes. These results support the implication of xCT dysregulation in illness pathophysiology and further indicate that it can result from redox changes. Additionally, we showed that these anomalies may already take place at early stages of psychosis and be more prominent in a subgroup of patients with GCLC high-risk genotypes. These data add to the existing evidence identifying the inflammatory/redox systems as important targets to treat schizophrenia already at early stages.xCT is the specific chain of the cystine/glutamate antiporter, which is widely reported to support anti-oxidant defenses in vivo. xCT is therefore at the crossroads between two processes that are involved in schizophrenia: oxidative stress and glutamatergic neurotransmission. But data from human studies implicating xCT in the illness and clarifying the upstream mechanisms of xCT imbalance are still scarce. Low glutathione (GSH) levels and genetic risk in  Deficit of antioxidant synthesis in schizophrenia leads to oxidative stress and changes in neurotransmitter transporter. Led by Kim Do, a team of researchers from Lausanne University in Switzerland investigated the role of the cell-surface transport protein xCT in schizophrenia. They found that an enzyme responsible for antioxidant production is disturbed in patients. This leads to decreased antioxidant levels and consequently to oxidative stress—i.e. the accumulation of reactive oxygen molecules, damaging the cells component and impairing cell functioning—which in turn affects the functioning of the antioxidant pathway, including xCT. xCT, which exports the neurotransmitter glutamate, is thus overproduced in schizophrenia. The resulting increase of neurotransmitter activity, alongside the increase in oxidative stress, is thought to play a major role in the pathophysiology of schizophrenia, including at early stages of the disease. Accordingly, xc- is widely reported to support anti-oxidant defenses in vivo.3 xc- is a heterodimer formed by the association of xCT (coded by SLC7A11) and 4F2hc (SLC3A2). xCT is the specific chain and an increase of gene expression often reflects an enhancement of cystine transport.5 xCT is stabilized at the membrane by CD44, a receptor for hyaluronic acid, whose expression increases intracellular levels of cysteine and GSH.6The system xc- is a sodium-independent antiporter, which imports cystine and exports glutamate in a 1:1 ratio.3 The transcription factor Nrf2 is well described as a master regulator for the up-regulation of genes in response to oxidative stress.7 In basal conditions, Keap1 binds to Nrf2 and promotes its degradation by the ubiquitin-proteasome system.8 In case of oxidative stress, Keap1 dissociates, allowing Nrf2 accumulation, translocation to the nucleus, and binding to antioxidant response elements (ARE) in the promoter regions of target genes.11 The promoter of SLC7A11 contains four ARE13 and activation of SLC7A11 expression by oxidation depends on Nrf2 as shown in Nrf2-/- mice.12 The Nrf2 inducer tert-butyl-hydroquinone (tBHQ), as well as the inhibitor of GSH synthesis buthionine sulfoximine (BSO), robustly increase xCT protein levels in cell culture.15Oxidative stress induces the expression of xCT.17 where it is expressed by astrocytes18 while mature neurons show no or little expression.18 xCT in rodent brain modulates extracellular glutamate levels through non vesicular release: over half of the non synaptic release of glutamate is attributed to the antiporter.21 Changes in xCT levels are linked to many neurological and psychiatric disorders, including schizophrenia based on two human studies.23 In 'postmortem' tissue of dorso lateral-prefrontal cortex, xCT protein levels are increased in schizophrenia patients compared to control individuals.24 A recent study reported that SLC7A11 gene expression is decreased compared to controls in peripheral white blood cells from Chinese Han patients.25 The authors of both studies excluded a confounding effect of antipsychotic treatment but did not identify potential upstream pathways which may lead to xCT impairment in patients.xCT expression is high in the brain28 Many studies revealed markers of oxidative stress in patients, both in the brain and in peripheral samples such as blood or fibroblasts.29 In line with these observations, levels of the anti-oxidant defenses differ between patients and control individuals.30 These data indicate that induction of the response to oxidative stress, despite being present to some extent, is not efficiently regulated in patients. The gene coding for the limiting enzyme for GSH synthesis  was associated with schizophrenia and variants of the tri-nucleotide repeat polymorphism in GCLC were more frequent in schizophrenia patients than in controls (GCLC high-risk genotypes).31 The GCLC high-risk genotypes are associated with a decrease of GSH levels in medial prefrontal cortex32 and in fibroblasts.31 Moreover a metabolomic study with patients’ fibroblasts showed altered reactivity to oxidative stress in GCLC high-risk genotypes.33Mounting evidence suggests oxidative stress and impairment of fast-spiking GABAergic interneurons as interdependent mechanisms forming a hub in schizophrenia physiopathology on which genetic and environmental factors converge.GCLC high-risk genotypes on xCT expression and activity, either in control conditions or by tBHQ-induced anti-oxidant response. Second, we investigated whether impairment of GCLC expression may alter xCT function in rat brain glial cells, astrocytes and oligodendrocytes.Therefore xCT is at the crossroads between oxidative stress and glutamatergic neurotransmission, two processes that are involved in schizophrenia. But data from human studies implicating xCT in the illness are still scarce, and the upstream mechanisms leading to xCT imbalance deserve further clarification. We hypothesize that oxidative stress induces xCT function, which subsequently participates in the dysregulation of glutamatergic signaling. In the present study, we aimed at determining if xCT regulation by the redox system is involved in schizophrenia physiopathology. First, we used fibroblasts from patients and controls to assess the impact of GCLC high-risk or GCLC low-risk genotypes  expression showed a 7.9-fold increase  was also increased by tBHQ, suggesting an overall enhancement of amino-acid uptake .In the top five genes that were up-regulated by SLC7A11 and SLC3A2 were similar between patients and controls both in vehicle  and tBHQ-treated condition .Levels of GCLC high-risk and GCLC low-risk genotypes, SLC7A11 was the most up-regulated gene associated with GCLC high-risk variants, with a 2-fold increase of expression already at basal level , however the gene CD44 was slightly increased . For SLC7A11, the interaction between tBHQ treatment and genotype was significant ; examining the means of expression indicates that the up-regulation in response to tBHQ was less in the GCLC high-risk genotypes than in the GCLC low-risk genotypes  with pes Fig. .GCLC high-risk genotypes. Therefore GCLC high-risk schizophrenia patients may represent a distinct subgroup with more pronounced anomalies of xCT regulation than GCLC low-risk patients. In a next step, we aimed at validating this finding at the functional level in early psychosis patients. In order to maximize the power and to avoid bias due to sex, we analyzed only male early psychosis patients.Altogether these data indicated that regulation of xCT expression was altered in individuals with GCLC low-risk, high-risk early psychosis patients and age-matched GCLC low-risk controls . The tBHQ-induced cystine uptake was comparable for the three groups. After tBHQ treatment, cystine uptake remained higher in GCLC high-risk patients compared with GCLC low-risk controls  and astrocytes). To impair the regulation of GCLC, cells were transduced by lentivirus to overexpress shRNA as previously described.34Because xc- system is mostly present in astrocytes and not in neurons,34 OPCs had a slow uptake of cystine, which reached a maximum after 30 min and was inhibited by the addition of glutamate . In dbcAMP-treated astrocytes, knock-down with shRNA decreased GCLC mRNA by 46%  as dbcAMP-treated astrocytes may resemble more closely the differentiated astrocytes present in brain tissue.46% Fig. . GCLC knGCLC high-risk genotypes, which are associated with lower brain GSH brain levels and higher risk for schizophrenia32 displayed higher expression and higher activity of xCT than fibroblasts with GCLC low-risk genotypes. The tBHQ-induced increase of cystine uptake appeared to be similar across genotypes. In a translational approach, we confirmed that GCLC knock-down increased the activity of xCT in primary culture of rodent astrocytes. We did not observe the same response to GCLC knock-down in oligodendrocyte precursors, therefore underlining that xCT regulation by GCLC levels was cell type dependent. Altogether, the results indicate that impaired GSH synthesis leads to the upregulation of xCT activity in specific glial cells, a mechanism already relevant to early stages of schizophrenia.We studied the regulation of xCT by genetic impairment of GSH synthesis. We found that fibroblasts with GCLC high-risk genotypes. Previous works indicate that these high-risk genotypes, without an additional oxidative stress, affect at least two metabolic pathways in cultured fibroblasts: the redox system33 and lysolipids levels.33 Importantly, the redox pathway is also affected in blood39 and in the brain as shown by the 14% decrease of GSH concentration in prefrontal cortex of GCLC high-risk individuals.32 Here we show that the GCLC high-risk genotypes are also associated with an increased activity of xCT in fibroblasts. Frequencies of GCLC high-risk genotypes are higher in schizophrenia patients than in controls31 and vary with the ethnicity.40 Controlling for this confounding factor in case-control studies is thus important as it may explain discrepancies between studies.These data add to the characterization of GCLC expression tightly controls GSH levels, and the high-risk variants are associated with lower GSH.32 Depletion of cysteine or GSH may lead to oxidative stress, to the activation of Nrf2, and to the enhancement of xCT activity.12 Consistently, previous work showed that depletion of intracellular cysteine or GSH enhanced the activity of the cystine-glutamate antiporter.41 Although Nrf2 is the most studied antioxidant regulator, other pathways may also be involved.15 For instance, SLC7A11 promoter also contains binding sites for ATF4, a transcription factor typically activated by amino acid starvation.42 Activation of ATF4 pathway up-regulates xCT, increases intracellular GSH levels, and confers resistance to oxidative stress.43The decrease of GCLC expression (by genetic variants or by knock-down) may increase xc- activity through the Nrf2 signaling pathway. Indeed 22 Glutamate levels in various brain regions are higher in early psychosis patients than in matched healthy controls.44 Accordingly, impairment of glutamate transport has been suggested by 'postmortem' brain studies of schizophrenia patients.46 The upregulation of xCT may thus participate in the impairment of glutamate transport and in the increase of brain glutamate in schizophrenia. xc- activity has been shown to significantly affect glutamate levels as knock-out mice for Slc7a11 have decreased levels of extracellular glutamate.21 Gene deletion leads to minor spatial memory deficits,47 and impaired hippocampal LTP47 and acute inhibition of xc- is associated with anxiety-related behaviors.49 Inactivation of the glial glutamate transporter GLAST, which likely leads to an increase of extracellular glutamate, also leads to endophenotypes that are associated with schizophrenia such as memory deficits and impaired acoustic startle.47An interesting downstream effect of enhanced xc- activity is the increased efflux of glutamate, which may participate to schizophrenia physiopathology by affecting the inhibitory/excitatory balance.2 levels in culture compared to in vivo conditions,3 interpretation of this work is limited by the in vitro setting. Nevertheless, regulatory mechanisms of xCT expression have been largely deciphered by studies using cell culture,1 thus highlighting that our conclusions can be transposed to in vivo conditions. Moreover, our observation that OPCs did not display an increase of xCT function following GCLC knock-down is also in favor of a specific regulation.Interpretation of the results is limited by the use of rodent cells, as it is not clear to which extent rat primary glial cells reflect human brain physiology. Because xCT is induced by the higher OGCLC expression, the limiting synthesizing enzyme for GSH, leads to an upregulation of xCT levels in patients’ fibroblasts as well as in astrocytes. These results from schizophrenia patients support the emerging data involving xCT dysregulation in illness physiopathology and further indicate that it can result from redox changes such as lower GSH levels, which have been previously associated with schizophrenia. According to our results, xCT dysregulation already takes place at early stages of psychosis and is more prominent in a subgroup of patients with GCLC high-risk genotypes. Investigating consequences of xCT dysregulation at the clinical level would shed light on the symptoms that may respond to molecules targeting the immune and/or redox system.In conclusion, our data show that a decrease of 33 Early psychosis patients were diagnosed according to DSM-IV criteria after a 3-years follow-up in the TIPP program . Patients included in the TIPP program had less than 6 months of anti-psychotic medication. Less female than male patients have been recruited in this cohort; therefore we focused on men the study of early psychosis patients. Control subjects were assessed and selected with the Diagnostic Interview for Genetic Studies. Individuals with a neurological, major mood, psychotic, or substance-use disorder and a first-degree relative with a psychotic disorder were excluded. All enrolled subjects provided a fully informed written consent; all procedures, including biopsy, were in accordance with the ethical standards of the Helsinki Declaration as revised in 1983, and was approved by the ethical committee of Lausanne University Hospital on human experimentation.All individuals were recruited in Lausanne area, Switzerland.33 Skin-derived fibroblasts from patients with early psychosis and age-matched, sex-matched controls were processed in parallel as described previously.33 We could not match for GCLC genotypes as control individuals with GCLC high-risk genotypes were not frequent enough in our cohort. After thawing, cells were amplified in Dulbecco’s Modified Eagle Medium , 2% Ultroser™G , 1% penicilline-streptomycine (Gibco). After five passages, we plated the fibroblasts at 5,104 cells/well (12-wells plate); we treated the cells the day after  or 0.05% dimethylsulfoxide (Sigma) for vehicle).Secondary cultures of fibroblasts were established from skin biopsies.51 in R . Log2 normalized expression signals were calculated using RMA algorithm52 . Sub-sequent analyses were based on Gene Ontology Annotation (UniProt-GOA).RNA was purified with RNAeasy column (Qiagen); quality was checked by Aligent 2100 bioanalyzer chips. Affymetrix, 1.0ST GeneChips were processed at Lausanne Genomic Technologies Facility according to manufacturer recommendation. Hybridization quality was assessed using the Bioconductor package affy34 Cells were cultured in DMEM, 10% fetal calf serum (FCS), 1% penicillin-streptomycin at 37 °C, 5% CO2. After 7 days in vitro (DIV), cells were infected with lentiviruses (multiplicity of infection: 5) to overexpress GCLC shRNA: GGAGGCTACTTCTATATTA or scrambled shRNA: CTTACAATCAGACTGGCGA. Puromycin was added 48 h post-infection . After 10 DIV, oligodendrocytes progenitor cells (OPCs) were separated from astrocytes and microglia by overnight shaking. OPCs were plated at 1.2,105 cells/well in 12-wells plate , 50 ug/ml apotransferrin, 5 ug/ml insulin (Sigma), 30 nM sodium selenate (Sigma), 10 nM hydrocortisone (Sigma), 10 nM D-biotine (Sigma), 1 mg/ml bovine serum albumin (Sigma), 10 ng/ml PDGF-AA (Sigma), 10ng/ml human fibroblast growth factor-basic (Sigma)); experiments were performed 14 DIV. In parallel, astrocytes which remained attached after shaking were plated at 7.5,104 cells/well in 12-wells plates in normal culture media  or in differentiation media  for 8 days).All animal procedures were approved by the Swiss cantonal veterinary office. Primary glial cells were dissociated from cortex of males and females Wistar Han rat pups at 3-days postnatal as previously described.53 Briefly, cells were washed with Hank’s balanced salt solution pH 7.4 ) and equilibrated in HBSS for 10 min at 37 °C, eventually with transporter inhibitor ; glutamate 2.5 mM). Medium was then changed for uptake buffer  in HBSS). Uptake was done at 37 °C and terminated on ice by removing uptake buffer and adding cold phosphate buffer saline (PBS). Cells were lysed with 500 μL of warm PBS with 0.5% sodium-dodecyl-sulfate. Incorporated radioactivity was quantified by liquid scintillation counting (Tricarb 2900TR Packard). Levels of radioactivity are normalized for protein content assessed with Bicinchoninic acid assay, the mean of technical duplicates was calculated. Data presented are representative of two experimental replicationsXc- activity was assessed based on previously published protocol.M-values (log base 2 of the fold change between two conditions), moderated t-statistic , p-values derived from moderated t, and adjusted p-value . For uptake experiments, we used student t-test in R on log-transformed data.For microarray data, we calculated for each probe set The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.Supplementary Figure 1Supplementary Figure 2


Some individuals with metabolically healthy obesity (MHO) convert to metabolically unhealthy obesity (MUO) phenotype, and visceral adiposity is one of proposed mechanisms underlying such conversion. Visceral adipose index (VAI) is a novel mathematical model which estimates visceral adiposity based on anthropometric and lipid profiles. We aimed to determine the association of VAI-estimated visceral adiposity with the MHO-to-MUO conversion and the predictive value of VAI in estimating such unfavorable outcomes.A total of 2,204 Korean subjects with the MHO phenotype were enrolled and stratified by body mass index and metabolic health state according to Wildman criteria at baseline and last follow-up examinations. VAI was calculated at baseline.Over a median follow-up period of 41.1 months, 46.0% of subjects converted to MUO phenotype. Higher VAI quartiles were associated with a greater proportion of subjects who underwent MHO-to-MUO conversion, and also with increased odds ratios for such conversion even after multivariate analyses. The optimal VAI cut off value was around 1.00, and VAI had a greater power in the prediction of MHO-to MUO conversion than waist circumference in both genders.MHO phenotypes with high VAI values are associated with poor future metabolic outcomes. VAI-estimated visceral adiposity is well correlated with the prognosis of MHO subjects, and VAI has a good predictive value in determining the MHO-to-MUO conversion. Recently, a unique obesity phenotype called the “metabolically healthy obesity (MHO)” state was introduced, which displays favorable cardiometabolic profiles and similar risk of cardiovascular morbidity and mortality compared to normal weight individuals –3. HowevA complex interconnection among genetic, environmental, and behavioral factors is thought to be the underlying mechanism of MHO phenotype . ProposeAmong multiple factors that might contribute to metabolic health in the MHO state, one of the most frequently reported key characteristics is the reduced accumulation of visceral fat . A more Visceral adiposity index (VAI) is a reliable formula, serving as an useful indicator of visceral fat function associated with cardiometabolic risk that does not require costly and inconvenient imaging studies . This siStudy subjects were recruited from those individuals aged more than 20 years old who visited the Health Screening and Promotion Center of Asan Medical Center  between March 2007 and December 2013 for routine medical examinations. During this period, 46,490 subjects received medical examinations on at least two occasions. Among the total of 46,490 subjects, we excluded 2,791 subjects who had taken drugs that could potentially affect lipid metabolism for more than 6 months or within the previous 12 months at a baseline examination. We also excluded 987 subjects with a history of cardiovascular disease (CVD) at baseline examination. In addition, subjects with the absence of data  were excluded. Finally, subjects with a high-sensitivity C-reactive protein (hsCRP) level greater than 10 mg/L (n = 623) were omitted to exclude occult infection or other systemic inflammatory processes . SeveralAll subjects completed a questionnaire on their previous medical and/or surgical diseases, medications, and drinking and smoking habits. Drinking habits were categorized as frequency per week ; smoking habits as noncurrent or current; and exercise habits as frequency per week  . PostmenAnthropometric examinations were performed while subjects were wearing light-weight clothing provided by the institution with shoes removed. The body mass index (BMI) was calculated by dividing the weight in kilograms by the square of the height in meters. The waist circumference  was measured midway between the costal margin and the iliac crest at the end of a normal expiration. Following a resting period of at least 15 minutes, blood pressure (BP) was measured on the right arm by automatic manometry using a Vital Sign Monitor 300 Series  with an appropriate cuff size. The measured BP was the average value of the three consecutive readings, with a 5-minute break between each measurement. After overnight fasting, blood samples were drawn from subjects’ antecubital veins into vacuum-sealed tubes and were transferred to a central, certified laboratory at Asan Medical Center. Measurements included the concentration of fasting glucose, insulin, hsCRP, several lipid parameters, and liver enzymes.Fasting total cholesterol, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), uric acid, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were measured by an enzymatic colorimetric method using a Toshiba 200 FR Neo autoanalyzer . Gamma-glutamyltransferase (GGT) was measured using the L-γ-glutamyl-p-nitroanilide method (Toshiba). HsCRP and fasting plasma glucose (FPG) were measured using the immunoturbidimetric method (Toshiba) and by an enzymatic colorimetric method using a Toshiba 200 FR autoanalyzer (Toshiba), respectively. Serum insulin was measured by immunoradiometric assay . Ion-exchange high-performance liquid chromatography  was used to measure HbA1c levels. The intra- and inter-assay coefficients of variation of these analyses were consistently <3.5%. The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated as the product of the fasting serum insulin (μU/mL) and FPG (mmol) concentrations divided by 22.5. All enzyme activities were measured at 37°C.2 and obesity ≥25 kg/m2) that were established by the World Health Organization Western Pacific Region [In this study, Asia-Pacific BMI criteria (non-obesity<25 kg/mc Region  and offic Region  were usec Region : (1) a sVisceral adiposity was assessed by calculating VAI according to previously validated equations . VAI wasVAI was formulated assuming a VAI of 1 for healthy subjects without obesity with normal adipose distribution and normal TG and HDL-C levels.t-test or the Mann-Whitney U test (for continuous variables) and the chi-squared test  were used to compare the demographic and biochemical characteristics of the two groups of study subjects  at the follow-up examination. The odds ratios (ORs) of conversion to the MUO state in subjects who were originally categorized as MHO at baseline were calculated using multivariate logistic regression analysis, in which various adjustment models consisting of different confounding variables were applied. To assess the utility of VAI as a marker for predicting the MHO-to-MUO conversion, receiver operating characteristics (ROC) curves were constructed and the areas under the curve (AUC) were calculated accordingly. The distance on the ROC curve of VAI was calculated by plotting the sensitivity against (1-specificity). To compare the predictive value of VAI and WC, ROC curve was also constructed for WC and the difference between the AUC was additionally analyzed. The AUC and the crucial points were determined using Med-Calc® version 11.6.1.0 for Windows . All other statistical analyses were performed using SPSS version 20.0 for Windows . A P-value < 0.05 was considered statistically significant.Subjects were categorized into four gender-specific quartile groups according to the baseline VAI values. Continuous variables with normal and skewed distribution are expressed as mean ± SD and median (and interquartile range), respectively. Categorical variables are expressed as proportions (%). The demographic and biochemical characteristics of the study population according to the metabolic health and obesity state at baseline were compared using one-way analysis of variance (ANOVA) with Scheffe’s method as the post-hoc analysis or the Kruskal-Wallis test with the Dunn procedure for continuous variables and the chi-square test for categorical variables as the post-hoc analysis. Student’s The baseline clinical and biochemical characteristics of the total study subjects according to baseline metabolic health and obesity are shown in Compared with subjects categorized as MUO, MHO subjects were characterized by younger age, higher degree of physical activity, and lower current rates of smoking and drinking . They alAmong the 2,204 MHO subjects in the study, 46.0%  of subjects converted to the MUO state at their last follow-up visit, whereas 33.6% (n = 740) of subjects remained within the MHO category. A total of 20.4% out of 2,204 MHO subjects converted to non-obese group . During the median follow-up period of 41.1 months, the crude incidence rates of MUO conversion according to VAI quartiles in men were 50.2% in Q1, 58.3% in Q2, 65.0% in Q3, and 70.9% in Q4, showing that an increase in the VAI quartiles was associated with an increased incidence of MUO conversion from MHO state . In womeP < 0.001) in men, while 1.01, which had a sensitivity of 62.5% and a specificity of 56.2% (P<0.001) in women. Using this cut-off value, the ORs for future conversion to MUO from baseline MHO state were 1.88  in men after adjusting for age, smoking and drinking habits, physical activities, uric acid, AST, ALT, GGT, and follow-up months and 1.91  in women after further adjusting for menopause state (Data not shown). VAI had a greater predictive power than that of WC  recently reported that approximately two-thirds of the MHO population underwent conversion to the MUO phenotype after 10 years of follow-up [P = 0.021) [The degree of the contribution of visceral adiposity to metabolic deterioration is well known from the results of previous cross-sectional studies –29. For ollow-up . In thatollow-up . Althoug= 0.021) . SimilarVAI is a gender-specific mathematical model, which originates from the observation in a healthy normal/overweight population of a linear relationship between BMI and WC, from which a linear equation has been extrapolated . VAI wasUpper body fat accumulation, decreased peripheral fat deposition and ectopic fat storage are the examples of altered body composition during the transition to menopause, and these alterations are considered as the major mediator of menopause-related cardiometabolic morbidity and mortality , 33. In In our analysis, uric acid was one of the independent factors associated with the conversion of MHO to MUO state in both genders . This might underestimate or overestimate the conversion rate of the obese phenotypes, although we adjusted the follow-up months in our multivariate logistic regression analysis . Third, In conclusion, a substantial proportion of MHO individuals cannot maintain healthy cardiometabolic outcomes and subsequently convert to the MUO phenotype in the near future. The visceral adiposity evaluated by VAI correlates well with this metabolic deterioration. The availability of visceral adiposity evaluation without costly and time-consuming imaging studies might be more practical in a clinical setting. However, future prospective longitudinal studies investigating the predictive value of VAI in determining the composite metabolic outcomes of MHO individuals with a longer-term follow-up period are warranted.


Klebsiella pneumoniae, a gram-negative bacillus of the Enterobacteriaceae family, is a component of the normal human microbiota and a common cause of community- and healthcare-associated infections. The increasing prevalence of antimicrobial resistance amongK. pneumoniae isolates, particularly among those causing healthcare-associated infections, is an important public health concern. Infections caused by these multidrug-resistant organisms, for which safe and effective antimicrobial therapy options are extremely limited, are associated with poor outcomes for patients. The optimal approach to the treatment of infections caused by these multidrug-resistant strains remains undefined, and treatment decisions for an individual patient should be based on a number of organism-  and patient-specific  factors. The emergence of pandrug-resistant strains ofK. pneumoniae highlights the critical need for consistent implementation of effective strategies for prevention of transmission and infection and for the development of new antimicrobials with activity against these emerging pathogens. Klebsiella pneumoniae, a member of the Enterobacteriaceae family of gram-negative bacilli, is part of the normal microbiome of many humans. Among 242 healthy volunteer participants in the National Institutes of Health Human Microbiome Project,K. pneumoniae was identified in 3.8% and 9.5% of stool and nasal samples, respectively1. Colonization was also detected at cutaneous, oral, and vaginal sites. There appears to be substantial geographic variation in the proportion of persons in whom the normal intestinal microbiota includesK. pneumoniae. For example, in a Korean study,K. pneumoniae was detected in stool samples obtained from 21.1% of 1,174 healthy persons at least 16 years of age2.K. pneumoniae include urinary tract infections (UTIs), pneumonia, and liver abscesses. Community-acquired liver abscesses caused by hypervirulent strains  ofK. pneumoniae have become increasingly common among persons without underlying hepatobiliary disease, particularly in Asia’s Pacific Rim. One potential explanation for these geographic differences in the incidence of disease is a higher rate of intestinal carriage ofK. pneumoniae of the K1 serotype among persons living in this region. In the previously mentioned Korean study, among the 21.1% of healthy adults who had fecal carriage ofK. pneumoniae, 23% were carriers of serotype K12. Interestingly, the rates of carriage of the K1 serotype were 5.6% among adults older than 25 years of age and 0% among those 16–25 years of age (P=0.007), and the prevalence of the K1 serotype was higher among isolates from ethnic Koreans residing in Korea than among those from persons residing in other countries (24.1% versus 5.6%). These findings suggest that environmental factors, such as diet, may play a role in the epidemiologic differences observed with regard to this pathogen2.The most commonly identified community-associated infections caused byrmpA gene-containing plasmid has been associated with this phenotype throughrmpA-mediated increases in capsule production. Explanations for the increased virulence of these strains include resistance to complement and neutrophil-mediated bactericidal activity3. Liver abscesses caused by these particular serotypes are associated with an increased risk of hematogenous dissemination to other sites  and with relatively high rates of morbidity and mortality (4–8%). Evaluation for hepatic abscess should be considered in persons presenting withK. pneumoniae bloodstream infection, endophthalmitis, or central nervous system infection without another explanation, particularly among persons with epidemiologic risk factors . Extended-spectrum beta-lactamases (ESBLs) and AmpC beta-lactamases are fortunately not common among these strains but have been reported5.In the laboratory, these hypervirulent strains are phenotypically characterized by hypermucoviscosity often defined by a positive “string test” in which a viscous string of more than 5 mm in length forms when bacterial colonies on an agar plate are stretched by an inoculation loop. Acquisition of anK. pneumoniae is a relatively infrequent cause of community-acquired infections, it is a common cause of healthcare-associated infections. In fact,Klebsiella species  were the third most common pathogens reported among all cases of central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), ventilator-associated pneumonia, and surgical site infection reported to the National Healthcare Safety Network (NHSN) of the Centers for Disease Control and Prevention (CDC) between 2011 and 2014, representing 7.7% of all reported pathogens6. Over the past few years, several outbreaks of infection caused by multidrug-resistant strains ofK. pneumoniae and other Enterobacteriaceae associated with the use of contaminated duodenoscopes have been reported. These outbreaks have been attributed at least in part to the complex design of duodenoscopes that renders them more difficult to adequately clean and disinfect as compared with endoscopes with simpler designs10. Although these duodenoscope-related infections have largely been associated with carbapenem-resistantK. pneumoniae (CRKP) and other carbapenem-resistant Enterobacteriaceae (CRE), these infections may represent just the tip of the iceberg of duodenoscope-related infections as infections caused by organisms with less notable resistance patterns may be less likely to trigger further investigation of a possible device-associated infection.AlthoughK. pneumoniae infection among persons with current or recent healthcare exposures appears to be due at least in part to increased rates and/or bacterial burdens of gastrointestinal carriage of the organism, which has been identified as a risk factor for subsequentK. pneumoniae infection. For example, in a prospective cohort study of 498 patients, rates of carriage ofK. pneumoniae, as detected by rectal and throat samples collected shortly after admission to the intensive care unit (ICU), were approximately 6% among patients admitted directly from the community and 19% among patients with recent healthcare contacts11. In that study,K. pneumoniae colonization was found to be a significant risk factor for subsequentK. pneumoniae infection while in the ICU, and 16% of carriers versus 3% of non-carriers developed infection and approximately half ofK. pneumoniae infections came from the patients’ own microbiota. Similarly, another study of patients hospitalized in ICUs and oncology wards found a prevalence of rectal carriage ofK. pneumoniae of 23%12. Among those identified as carriers, 5.2% subsequently developedK. pneumoniae infection  4.06,P<0.001). Finally, 27% of ICU patients identified as asymptomatic carriers of CRKP through perianal swab specimens collected as part of an active surveillance program subsequently developed CRKP bloodstream infection during their index hospitalization13.The increased incidence ofK. pneumoniae has become an increasingly serious problem over the past 20 years, and there are multiple examples of rapid global dissemination of novel mechanisms of resistance, such as theK. pneumoniae carbapenemase (KPC) and the New Delhi metallo-beta-lactamase (NDM). The problem of antimicrobial resistance is particularly prevalent among healthcare-associatedK. pneumoniae isolates. AmongK. pneumoniae andK. oxytoca isolates from CLABSI and CAUTI cases reported to the NHSN in 2014, rates of resistance ranged from 22.5 to 24.1% for extended-spectrum cephalosporins and 9.5 to 10.9% for carbapenems6. Among these same isolates, rates of multidrug resistance, defined as resistance to at least one drug in at least three of five classes, ranged from 14.6 to 17.2%.Antimicrobial resistance among clinical isolates ofK. pneumoniae has led some to warn of the potential for a return to the pre-antibiotic era and the arrival of a “post-antibiotic era” in which we no longer have antibiotics effective for the treatment of infections caused by relatively common bacterial pathogens14. As one example, a recent report described a patient in Nevada who died in September 2016 from septic shock due to pandrug-resistantK. pneumoniae infection15. The isolate was non-susceptible to all 27 available antimicrobial drugs. This particular case occurred in a region with a relatively low prevalence of CRE. The isolate was subsequently found to carry the NDM gene, suggesting that the organism may have been acquired during the patient’s previous healthcare exposures in India and highlighting the importance of international travel, globalization, and healthcare exposures in the epidemiology of antimicrobial resistance.The growing problem of antimicrobial resistance among gram-negative organisms such asK. pneumoniae, as one of the top three urgent antimicrobial resistance threats16. This report estimated that, in the US each year, there are 7,900 infections and 520 deaths due to carbapenem-resistantKlebsiella species. KPC is the most common mechanism of carbapenem resistance amongK. pneumoniae isolates in the US. As of January 2017, KPC-producing CRE had been reported to the CDC from 48 states in the US17. KPC-producing CRE typically also have genes that confer resistance to several other classes of antimicrobials, resulting in these organisms displaying a multidrug-resistant phenotype. Among CRE isolates reported to the CDC as of January 6, 2017, carbapenemases other than KPC that have been identified include NDM (n=175), oxacillinase-48-type carbapenemase , Verona integron-encoded metallo-beta-lactamase , and imipenemase metallo-beta-lactamase . There are other mechanisms of carbapenem resistance, including hyperproduction of the AmpC beta-lactamase with coexisting porin mutations. In some regions outside the US, non-KPC mechanisms of resistance predominate.In a 2013 report, the CDC identified CRE, the most common of which isK. pneumoniae isolates from five Italian hospitals in 201318. Between 2009 and 2012, colistin resistance was detected in 2.7% ofKlebsiella isolates obtained from patients hospitalized with pneumonia at one of 28 medical centers in the US19. Polymyxin resistance has been reported as an independent predictor of 14-day mortality among patients with KPC-producingK. pneumoniae infections18.The polymyxins—polymyxin E (or colistin) and polymyxin B—serve as drugs of last resort for treatment of infections caused by CRKP and other multidrug-resistant gram-negative pathogens; however, resistance to the polymyxins is a well-described phenomenon and has become increasingly common in some areas, and a rate of 27% was reported among KPC-producingmgrB regulatory gene24. Previous treatment with colistin has been associated with infection due to colistin-resistant KPC-producingK. pneumoniae25; however, the majority of patients with colistin-resistant KPC-K. pneumoniae bloodstream infection in one study had not previously received colistin, indicating that other factors, such as healthcare-associated transmission of resistant strains, likely also play a role. More recently, a plasmid-mediated gene (mcr-1) that confers resistance to polymyxin was discovered. The gene has been identified among Enterobacteriaceae  isolated from animal and human sources. The initial report from China in November 2015 includes isolates obtained as early as 201126. In that investigation, the rates of prevalence of themcr-1 gene were 20.6% amongE. coli isolates obtained from pigs at the time of slaughter, 14.9% amongE. coli isolates obtained from retail chicken and pork, and 1.4% and 0.7% amongE. coli andK. pneumoniae isolates, respectively, from human inpatients. Since that report,mcr-1 has been detected in food animals, food, or humans (or a combination of these) in other Asian countries, Europe, Africa, North America, and South America28. As of March 30, 2017, 14mcr-1-positive isolates, including 12 human and two animal isolates, had been reported from 11 US states29. Investigators have demonstrated successfulin vitro transfer of themcr-1 gene betweenE. coli isolates by conjugation and fromE. coli toE. coli,K. pneumoniae, andPseudomonas aeruginosa by transformation26, raising significant concerns about the possibility of acquisition of this mobile genetic element by organisms that already possess other drug-resistance determinants  resulting in pandrug-resistant bacteria.Resistance to polymyxin is most commonly chromosomally mediated and this is typically due to post-translational modification of bacterial outer-membrane lipopolysaccharide through the addition of cationic groups as a result of mutations in theK. pneumoniae is important for both clinical and epidemiologic purposes. Polymyxin susceptibility testing is challenging for several reasons  and these challenges can lead to unacceptably high error rates when methods such as disk and agar gradient diffusion are used. The Clinical Laboratory Standards Institute/European Committee on Antimicrobial Susceptibility Testing (CLSI/EUCAST) Joint Polymyxin Breakpoints Working Group recently identified broth microdilution as the reference method for testing colistin susceptibility30. No specific statements or recommendations for polymyxin B susceptibility testing were made, but many of the same limitations and challenges as noted for colistin are applicable to polymyxin B as well.Accurate assessment of polymyxin susceptibility among multidrug-resistant strains ofK. pneumoniae have been associated with substantial morbidity, mortality, and cost. The attributable length of hospital stay due to CRE infections has been reported to range from 4 to 21 days, depending on the site of infection31. Reported rates of attributable mortality have ranged from 10 to 70%, again varying substantially among reports and among different sites of infection. A multinational group of investigators recently developed and validated a predictive model of 14-day mortality in patients with monomicrobial bloodstream infection caused by carbapenemase-producing Enterobacteriaceae32. The final model, which exhibited an area under the receiver operating characteristic curve of 0.8  0.73–0.88), included five factors that could be assessed when antimicrobial susceptibility testing results become available: severe sepsis or shock at presentation, Pitt bacteremia score of at least 6, Charlson comorbidity index of at least 2, source of bloodstream infection other than urinary or biliary tract, and inappropriate empiric and early targeted antimicrobial therapy. The cost of a single CRE infection has been estimated to range from $22,484 to $66,031 for hospitals and from $37,778 to $83,512 for society31. Given 9,418 CRE infections in the US per year, the annual costs could be as high as $334 million and $1.59 billion for hospitals and society, respectively, with a loss of up to 12,420 quality-adjusted life years.Infections caused by multidrug-resistant strains of33, but a few topics are worthy of brief discussion here.The optimal antimicrobial treatment of infections caused by CRKP remains to be determined and for any individual patient is likely dependent upon a number of patient-specific  and organism-specific  factors. As noted above, mortality rates for these infections remain unacceptably high with currently available therapy. In addition to antimicrobial agents, other therapeutic interventions such as source control should be used whenever possible in order to maximize the likelihood of a successful outcome. Strategies for, and the challenges and limitations associated with, the use of the currently available antimicrobial agents are thoroughly reviewed in previously published articlesK. pneumoniae isolates demonstrated relatively low-level carbapenem resistance (MIC ≤8–16)34. Retrospective studies that have assessed this strategy among patients infected with CRKP with high-level carbapenem resistance have generally not demonstrated additional benefit36. These MIC-dependent differences in clinical outcomes are supported byin vitro testing that has demonstrated synergy between bactericidal activity of polymyxin B plus meropenem against KPC-2-producingK. pneumoniae isolates with meropenem MICs of not more than 16 μg/mL37. Similarly, exposure to this combination of agents produced morphological changes in bacterial isolates that decreased as the meropenem MIC increased. The pharmacodynamic effects of combination therapy decreased as the meropenem MIC increased to more than 16 μg/mL. Thus, combinations of a polymyxin plus optimized dosing of a carbapenem appear to be most likely of benefit for treatment of infections caused by CRKP strains with relatively low-level carbapenem resistance .Some but not all retrospective studies have found an association between combination therapy and lower mortality as compared with treatment with single-drug treatment regimens. One of the more common combination therapy regimens is that of a polymyxin plus an optimized dosing regimen of a carbapenem . Some observational studies have reported better outcomes among patients who received polymyxin-carbapenem combination therapy, particularly in patients or settings (or both) in whichIn vitro or animal models using both immunocompetent and neutropenic mice (or both) have demonstrated enhanced efficacy of dual carbapenem regimens  as compared with a single carbapenem (doripenem) against at least some isolates of KPC- and NDM-producingK. pneumoniae39. This strategy appears to be most likely effective for treatment of infections caused by organisms with relatively low carbapenem MICs  and may be less effective in immunocompromised hosts40. Human clinical data are limited, but at least two small case series of three patients each with high-level CRKP bacteremia or UTI have reported successful treatment using the combination of ertapenem plus either doripenem or meropenem42.Dual carbapenem therapy refers to the use of ertapenem, which is the carbapenem with the highest affinity for carbapenemase enzymes, in addition to a carbapenem that has lower affinity for the enzyme  so that ertapenem preferentially consumes the carbapenemase, allowing a larger proportion of the other carbapenem to remain intact and to exert its antimicrobial effect on the infecting organism.fT>MIC) for at least 40% of the dosing interval. Treatment regimens using higher doses and prolonged infusion of carbapenems  have achieved thisfT>MIC goal and have been successful in the treatment of infections due to other gram-negative organisms with relatively low-level carbapenem resistance MIC (<16 µg/mL), includingP. aeruginosa. However, at least onein vitro pharmacodynamic model was not reliably able to reach afT>MIC of at least 40% for KPC-producingK. pneumoniae isolates with MICs of 8 µg/mL and did not achieve afT>MIC of at least 40% for any isolates with an MIC of 16 µg/mL due to rapid hydrolysis of meropenem43.The two previously described treatment strategies both involve the use of optimized dosing of a carbapenem . This refers to administering the drug in doses and frequencies that are most likely to allow the free drug concentration to exceed the MIC of the infecting organism 47. There are currently no data from randomized controlled trials of the use of ceftazidime-avibactam for the treatment of CRKP, but available data from case series suggest that ceftazidime-avibactam may offer a useful therapeutic option for some patients with CRKP infections49. Temkin and colleagues described the use of ceftazidime-avibactam for the treatment of 36 patients with CRE infection (34 of which were caused by CRKP) and two patients with carbapenem-resistantP. aeruginosa48. Among those 38 patients, 28 (74%) experienced clinical or microbiological cure or both. Shields and colleagues described their experience using ceftazidime-avibactam to treat 37 patients with CRE infection, 84% of which wereK. pneumoniae with 90% of those harboring aKPCbla gene49. Clinical success was achieved in 59% of the patients. Microbiologic failure occurred in 27% of the patients and development of ceftazidime-avibactam resistance  was detected in three 3(30%) of 10 cases within 10–19 days of ceftazidime-avibactam exposure. In subsequent investigations, emergence of mutations inKPC-3bla was detected among the three isolates that had acquired ceftazidime-avibactam resistance. The resulting variant enzymes were demonstrated to result in resistance to ceftazidime-avibactam; however, these variant enzymes had reduced carbapenamase activity50. Meropenem MICs were reduced by at least 4-fold from baseline with restoration of meropenem susceptibility in two of the three isolates. Other identified mechanisms of resistance to ceftazidime-avibactam among KPC-producing Enterobacteriaceae include production of large amounts of AmpC beta-lactamase51, suggesting that ceftazidime-avibactam may not be active against organisms with this particular combination of beta-lactamases, and mutations in outer-membrane porins 52.Ceftazidime-avibactam was approved by the US Food and Drug Administration (FDA) in 2015 for treatment of complicated UTI, including pyelonephritis and, in combination with metronidazole, complicated intra-abdominal infections. Avibactam is a new non-beta-lactam beta-lactamase inhibitor that has activity against class A and C beta-lactamases, including ESBLs, AmpC, and KPC. It is not active against class B metallo-beta-lactamases, such as NDMin vitro activity against multidrug-resistant strains ofK. pneumoniae are now in development. These include combinations of existing beta-lactam drugs with new carbapenemase inhibitors and novel drugs within existing drug classes .K. pneumoniae and other gram-negative organisms is urgently needed.Until very recently, the pipeline of new drugs for the treatment of multidrug-resistant gram-negative pathogens had been described as “dry”. However, a number of new drugs withK. pneumoniae infections, prevention of transmission and subsequent infection with these organisms is critical. In November 2015, the CDC updated their recommendations for CRE prevention and control in acute care hospitals and long-term care facilities that provide skilled nursing or rehabilitation services53. The recommendations reflect the complex, multifactorial epidemiology of CRE transmission in healthcare facilities and include guidance related to surveillance , basic infection prevention strategies , antimicrobial stewardship, education of healthcare personnel, and communication within and between healthcare facilities. Additional recommendations have been provided to specifically address and mitigate the previously described risk of transmission of pathogens, includingK. pneumoniae, through the use of duodenoscopes54.Given the limited treatment options available for, and the morbidity and mortality associated with, multidrug-resistantK. pneumoniae have ranged from 5.4 to 67%57. Investigators have also assessed the frequency at which healthcare workers become contaminated withKlebsiella while providing care to patients colonized or infected with these organisms. Overall rates of contamination of gowns or gloves (or both) of 10.4 to 16.9% have been reported56, but further evaluation is needed to identify specific activities as well as patient- and organism-specific characteristics that may be associated with higher rates of contamination.The recommendation to ensure strict adherence to basic infection prevention practices such as environmental cleaning, hand hygiene, and contact precautions is supported by a number of studies conducted in the healthcare environment. For example, rates of environmental contamination in hospital rooms housing patients colonized or infected withP<0.01)58. The difference between groups was no longer statistically significant at 6 weeks (58.5% versus 33.3%). While such a strategy has the potential to be useful for CRKP-colonized patients during a period of particularly high risk for invasive infection, the results of these data do not seem to support routine use of this strategy given its less-than-reliable efficacy (nearly 40% remained culture-positive at 2 weeks), the potential risk for promoting the development of resistance to polymyxin, which remains an important drug for the treatment of CRKP infections, and the lack of data on the clinical impact of such treatment. Prevention of CRKP infections among carriers of the organism is an area in great need of further research.Most recommended prevention strategies are focused on preventing transmission of CRKP from colonized and infected patients to others. The relatively high rate of subsequent CRE infection among those who are asymptomatic carriers of CRE highlights the current lack of and need for effective interventions to prevent progression to active infection among persons who are carriers. At least one small study has evaluated the effect of a selective digestive decontamination  on rates of rectal culture positivity among hospital patients with gastrointestinal carriage of CRKP. In this randomized, controlled, double-blind trial, investigators found that significantly more patients in the active treatment arm had negative rectal cultures at 2 weeks (61.1% versus 16.1%, OR 0.13,


Background: Research has demonstrated a strong link between trauma, posttraumatic stress disorder (PTSD) and substance use disorders (SUDs) in general and cannabis use disorders in particular. Yet, few studies have examined the impact of cannabis use on treatment outcomes for individuals with co-occurring PTSD and SUDs. Methods: Participants were 136 individuals who received cognitive-behavioral therapies for co-occurring PTSD and SUD. Multivariate regressions were utilized to examine the associations between baseline cannabis use and end-of-treatment outcomes. Multilevel linear growth models were fit to the data to examine the cross-lagged associations between weekly cannabis use and weekly PTSD symptom severity and primary substance use during treatment. Results: There were no significant positive nor negative associations between baseline cannabis use and end-of-treatment PTSD symptom severity and days of primary substance use. Cross-lagged models revealed that as cannabis use increased, subsequent primary substance use decreased and vice versa. Moreover, results revealed a crossover lagged effect, whereby higher cannabis use was associated with greater PTSD symptom severity early in treatment, but lower weekly PTSD symptom severity later in treatment. Conclusion: Cannabis use was not associated with adverse outcomes in end-of-treatment PTSD and primary substance use, suggesting independent pathways of change. The theoretical and clinical implications of the reciprocal associations between weekly cannabis use and subsequent PTSD and primary substance use symptoms during treatment are discussed. Decades of research have demonstrated a strong link between trauma, PTSD and Substance Use Disorders (SUDs) in general ,2,3,4 anCannabis is often used concurrently with other substances, with individuals who used cannabis in the previous six months being more likely than those who do not use cannabis to smoke cigarettes (33.9% vs. 61.9%), engage in hazardous alcohol use (8.89% vs. 11.54%) and other drug use 4.1% vs. 23.8%) [.8% [23].Given the widespread utilization of cannabis among those with PTSD, paired with reductions in the perception of the harmfulness of cannabis, investigations have now begun to explore whether the utilization of cannabis prior to, during or after treatment is associated with beneficial or adverse treatment outcomes among those with co-occurring psychiatric and other substance use disorders. Several studies suggest that cannabis use is associated with PTSD symptom reduction and improved coping ,27. In aThe benefits of cannabis use with respect to other drugs of abuse are less clear. Several studies have reported no association between cannabis use and adverse treatment outcomes among opioid- and cocaine-dependent patients ,34,35,36However, other studies suggest that cannabis use either before entering or after being discharged from treatment may be associated with adverse treatment outcomes among opioid and cocaine-dependent patients ,39,40. FDespite mixed findings, the majority of studies reported were conducted with predominantly young, male, Caucasian or veteran samples receiving primarily medication-assisted treatments; thus, it remains unclear whether the findings are generalizable to other subgroups of populations. Moreover, none of the studies to date have examined the impact of cannabis use on treatment outcomes in a dually-diagnosed sample with co-occurring PTSD and substance use disorders. Additionally, very few studies have examined the effect of cannabis use on PTSD or primary substance use severity during treatment. The present study thus sought to extend prior findings by examining whether cannabis use at baseline and weekly during treatment had an impact on in-treatment and end-of-treatment PTSD symptom severity and primary substance use among a treatment-seeking dually-diagnosed population. Given the extant literature on the link between cannabis use and PTSD symptoms, we hypothesized that baseline and in-treatment cannabis use would be significantly associated with in-treatment and end-of-treatment PTSD symptom severity. Given the mixed findings in the literature on the impact of cannabis use on other substance use outcomes and the limited data on the effects of weekly cannabis use on in-treatment SUD symptomatology, we examined these associations in an exploratory fashion.n = 9), since our primary question pertained to the impact of cannabis use on other primary substance use disorders. Of the 136 participants included in this analysis (out of 179), 32 participants used cannabis in the seven days prior to baseline and were included in the cannabis use group. The mean age of cannabis users was 41.63 years (SD = 9.38); approximately 66% were male; and average years of education were 13.08 (SD = 1.08). Nonusers had a mean age of 44 years old (SD = 9.18); approximately 42% were males; and they completed 13.28 years of education (SD = 2.52), on average. There were no significant differences in age , race/ethnicity distributions , level of education  and level of employment  between the cannabis users and nonusers. The cannabis user group was composed of significantly more males than nonusers  and was more likely to have a cocaine use disorder than nonusers . Nonusers were more like to have an alcohol use disorder compared to cannabis users . See Data for these analyses were derived from two recently-completed clinical trials that tested combined  and integrated cognitive-behavioral treatments for co-occurring PTSD and substance use disorders. Trial 1 compared Seeking Safety + Sertraline (SS + S) to Seeking Safety + Placebo   is a manTrial 2: Concurrent treatment with Prolonged Exposure (COPE) is a 12-week intervention that integrates the empirically-supported models of prolonged exposure for PTSD  and RPT Demographics: In both trials: age, sex, race/ethnicity, education, marital status, employment pattern and income were collected during the baseline interview.Psychiatric and alcohol/substance use disorder diagnoses: In both trials, the Structured Clinical Interview for DSM-IV for Axis I Disorders (SCID-I)  was admiPTSD symptom severity: In both trials, the Clinician-Administered PTSD Scale (CAPS)  was usedSubstance use: In Trial 1, The Timeline Follow-Back (TLFB)  was usedIn Trial 2, primary SUD diagnosis was based on a number of dependence criteria from the SCID-I. The Addiction Severity Index-Lite (ASI-Lite) ,54, a seIn both trials, the Substance Use Inventory (SUI)  was usedt-tests for continuous variables were used to compare cannabis users and nonusers on baseline sociodemographic variables. Bivariate correlations were utilized to assess the associations between baseline frequency of cannabis use, age, end-of-treatment PTSD symptom severity and days of primary substance use. A series of multivariate regression analyses was conducted to determine whether frequency of marijuana use at baseline predicted end-of-treatment response on two dimensions (PTSD symptom severity (as measured by the CAPS) and days of primary substance use (as measured by ASI and TLFB)). End-of-treatment PTSD symptom severity and days of primary substance use were regressed independently on the frequency of marijuana use while controlling for baseline scores of either PTSD symptom severity or days of primary substance use, gender and age. All analyses were run using bootstrap sampling (1000 bootstrap draws) in order to reduce the chances of a confirmation of null findings due to Type I error related to sample size.Chi-square tests for categorical variables and independent sample Several models were specified in a generalized multilevel framework using Stata Version 14  to examia, while the information to the right of the plus sign represents our second dependent variable, cannabis use, which is denoted by the subscript b. To model the impact of lagged variables , the variables were lagged by one time point, which is seen in the above equation by the subscript j − 1. Given that both cannabis use and primary substance use were lagged in the model, time itself was centered at Week 2 of treatment so that the predicted intercept  for each variable would be meaningful.In this equation, the information to the left of the bolded plus sign represents our first dependent variable, primary substance use, which is denoted by the subscript When we were examining the impact of lagged weekly cannabis and primary substance use on PTSD symptoms, we were unable to model all of the variables as outcomes simultaneously, as we did for primary substance use and cannabis use, because of the difference in scales of the substance use variables and the PTSD symptom severity . TherefoGiven that both primary substance use and cannabis use were significantly right skewed and there was evidence of overdispersion, a negative binomial family distribution and a log link function were used for all models in which substance use was the outcome. When PTSD symptom severity was the outcome, a normal distribution was specified. For both models, the unadjusted model controlled only for time, while sex and age (mean centered) were included as covariates in adjusted models. To present the most parsimonious model, the final model presented includes only significant predictors.r = 0.84, p < 0.01). There were no significant correlations between baseline days of cannabis use and end-of-treatment PTSD symptom severity or days of primary substance use.t = 1.04, p = 0.30) or end-of-treatment days of primary substance use , indicating that cannabis use was not associated with either positive or negative response at end-of-treatment in either domain. Neither gender, nor age accounted for a significant amount of variance in end-of-treatment PTSD symptom severity or days of primary substance use (p > 0.05). Only baseline PTSD symptom severity accounted for a significant proportion of variance in the end-of-treatment PTSD symptom severity . The overall model fit for predicting end-of-treatment PTSD symptom severity was R2 = 0.14 and for end-of-treatment days of primary substance use was R2 = 0.04.Multivariate regressions with bootstrapping further revealed that baseline days of cannabis use was not a significant predictor of end of treatment PTSD symptom severity , while there was a trend for a decrease in weekly cannabis use , p = 0.071). There was evidence of a cross-lagged association for both weekly cannabis , p < 0.001) and primary substance use , p = 0.002), both indicating that as one substance increased, the other substance decreased. Lagged PTSD symptom severity was not significantly associated with either weekly primary substance or cannabis use  and none of the lagged predictors  had a significant interaction with time. After adjusting for age and sex, results indicated that both weekly primary substance use , p < 0.001) and weekly cannabis use , p < 0.001) significantly decreased during treatment. Further, the cross-lagged associations between weekly cannabis use and weekly primary substance use were largely unchanged. Specifically, a one-unit increase in lagged weekly cannabis use was associated with 26% lower weekly primary substance use, while a one-unit increase in lagged primary substance use was associated with 14% lower weekly cannabis use.A multilevel linear growth model was fit to the data to examine the cross-lagged associations between weekly cannabis and primary substance use throughout the 12 weeks of treatment. Although both outcomes were run simultaneously, both unadjusted and adjusted model results are displayed in two tables  to increp < 0.001), PTSD symptom severity decreased significantly during treatment. However, neither lagged weekly cannabis, nor primary substance use was associated with weekly PTSD symptom severity . In addition, lagged weekly primary substance use did not interact with time in the prediction of PTSD symptom severity scores (p = 0.902). However, the interaction between lagged weekly cannabis use and time was significant , p = 0.029). After adjusting for covariates, results remained largely unchanged. The interaction between lagged weekly cannabis use and time was explored . Self-report measures of substance use bring inherent biases related to recall and social desirability. Finally, since the study was not originally designed to test the impact of cannabis use on treatment outcomes, these post-hoc subgroup analyses may suffer from selection bias.Despite these limitations, this is one of the first studies to examine the impact of cannabis use in a racially-/ethnically-diverse sample of participants receiving cognitive behavioral therapies for co-occurring PTSD and substance use disorders. In addition to documenting moderate rates of cannabis use among those with other primary substance use disorders, these findings provide evidence in support of a harm reduction perspective in the treatment of addictions with PTSD. First, our findings demonstrated that baseline cannabis use was not associated with end-of-treatment outcomes, suggesting independent pathways of change. Second, cross-lagged predictive models examining the impact of previous week cannabis use on subsequent primary substance use revealed an inverse relationship showing that increasing cannabis use was actually associated with lowering primary substance use. Conversely, increasing primary substance use in the previous week was associated with lowering cannabis use the following week. Moreover, findings revealed a cross-over effect, whereby higher cannabis use was related to higher PTSD symptom severity early in treatment, but lower PTSD symptom severity later in treatment. Taken as a whole, our findings provide more support in the controversy that cannabis use (in non-primary cannabis dependence users) is not necessarily an adverse component to the treatment process for addictions.