Oxidative stress is implicated in the etiology of schizophrenia, and the antioxidant defense system may be protective in this illness. We examined the major antioxidant glutathione (GSH) in prefrontal brain, and its correlates with clinical and demographic variables, in schizophrenia.

GSH levels were measured in the dorsolateral prefrontal region of 28 patients with chronic schizophrenia using a magnetic resonance spectroscopy sequence specifically adapted for GSH. We examined correlations of GSH levels with age, age at onset of illness, duration of illness, and clinical symptoms.

We found a negative correlation between GSH levels and age at onset (r=-.46, p=.015), and a trend-level positive relationship between GSH and duration of illness (r=.34, p=.076).

Our findings are consistent with a possible compensatory upregulation of the antioxidant defense system with longer duration of illness, and suggests the antioxidant defense system may play a role in schizophrenia.

Mismatch negativity (MMN) is an event-related potential (ERP) component reflecting auditory predictive coding. Repeated standard tones evoke increasing positivity (‘repetition positivity’; RP), reflecting strengthening of the standard's memory trace and the prediction it will recur. Likewise, deviant tones preceded by more standard repetitions evoke greater negativity (‘deviant negativity’; DN), reflecting stronger prediction error signaling. These memory trace effects are also evident in MMN difference wave. Here, we assess group differences and test-retest reliability of these indices in schizophrenia patients (SZ) and healthy controls (HC).

Electroencephalography was recorded twice, 2 weeks apart, from 43 SZ and 30 HC, during a roving standard paradigm. We examined ERPs to the third, eighth, and 33rd standards (RP), immediately subsequent deviants (DN), and the corresponding MMN. Memory trace effects were assessed by comparing amplitudes associated with the three standard repetition trains.

Compared with controls, SZ showed reduced MMNs and DNs, but normal RPs. Both groups showed memory trace effects for RP, MMN, and DN, with a trend for attenuated DNs in SZ. Intraclass correlations obtained via this paradigm indicated good-to-moderate reliabilities for overall MMN, DN and RP, but moderate to poor reliabilities for components associated with short, intermediate, and long standard trains, and poor reliability of their memory trace effects.

MMN deficits in SZ reflected attenuated prediction error signaling (DN), with relatively intact predictive code formation (RP) and memory trace effects. This roving standard MMN paradigm requires additional development/validation to obtain suitable levels of reliability for use in clinical trials.

Elevated levels of pro-inflammatory cytokines are consistently reported in schizophrenia (SZ) and bipolar-I disorder (BD), as well as among individuals who have been exposed to childhood trauma. However, higher levels of inflammatory markers in these disorders are yet to be investigated with respect to levels of exposure to different types of childhood trauma.

Participants were 68 cases with a diagnosis of schizophrenia/schizoaffective disorder (SZ), 69 cases with a diagnosis of psychotic BD and 72 healthy controls (HC). Serum levels of interleukin 6 (IL-6), tumour necrosis factor-α (TNF-α) and C-reactive protein (CRP) were quantified, and childhood trauma exposure was assessed with the Childhood Trauma Questionnaire.

The SZ group had significantly higher levels of IL-6, TNF-α and CRP when compared with the HC group (all p < 0.05, d = 0.41–0.63), as well as higher levels of TNF-α when compared with the BD group (p = 0.014, d = 0.50); there were no differences between the BD and HC groups for any markers. Exposure to sexual abuse was positively associated (standardised β = 0.326, t = 2.459, p = 0.018) with levels of CRP in the SZ group, but there were no significant associations between any form of trauma exposure and cytokine levels in the HC or BD groups.

These results contribute to the evidence for a chronic state of inflammation in SZ but not BD cases. Differential associations between trauma exposure and levels of pro-inflammatory cytokines across the diagnostic categories suggest that trauma may impact biological (stress and immune) systems differently in these patient groups.

To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.

To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.

Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.

Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.

To describe the process by which the 12 community-based primary health care (CBPHC) research teams worked together and fostered cross-jurisdictional collaboration, including collection of common indicators with the goal of using the same measures and data sources.

A pan-Canadian mechanism for common measurement of the impact of primary care innovations across Canada is lacking. The Canadian Institutes for Health Research and its partners funded 12 teams to conduct research and collaborate on development of a set of commonly collected indicators.

A working group representing the 12 teams was established. They undertook an iterative process to consider existing primary care indicators identified from the literature and by stakeholders. Indicators were agreed upon with the intention of addressing three objectives across the 12 teams: (1) describing the impact of improving access to CBPHC; (2) examining the impact of alternative models of chronic disease prevention and management in CBPHC; and (3) describing the structures and context that influence the implementation, delivery, cost, and potential for scale-up of CBPHC innovations.

Nineteen common indicators within the core dimensions of primary care were identified: access, comprehensiveness, coordination, effectiveness, and equity. We also agreed to collect data on health care costs and utilization within each team. Data sources include surveys, health administrative data, interviews, focus groups, and case studies. Collaboration across these teams sets the foundation for a unique opportunity for new knowledge generation, over and above any knowledge developed by any one team. Keys to success are each team’s willingness to engage and commitment to working across teams, funding to support this collaboration, and distributed leadership across the working group. Reaching consensus on collection of common indicators is challenging but achievable.

To integrate electronic clinical decision support tools into clinical practice and to evaluate the impact on indwelling urinary catheter (IUC) use and catheter-associated urinary tract infections (CAUTIs).

This 4-phase observational study included all inpatients at a multicampus, academic medical center between 2011 and 2015.

Phase 1 comprised best practices training and standardization of electronic documentation. Phase 2 comprised real-time electronic tracking of IUC duration. In phase 3, a triggered alert reminded clinicians of IUC duration. In phase 4, a new IUC order (1) introduced automated order expiration and (2) required consideration of alternatives and selection of an appropriate indication.

Overall, 2,121 CAUTIs, 179,070 new catheters, 643,055 catheter days, and 2,186 reinsertions occurred in 3·85 million hospitalized patient days during the study period. The CAUTI rate per 10,000 patient days decreased incrementally in each phase from 9·06 in phase 1 to 1·65 in phase 4 (relative risk [RR], 0·182; 95% confidence interval [CI], 0·153–0·216; P<·001). New catheters per 1,000 patient days declined from 53·4 in phase 1 to 39·5 in phase 4 (RR, 0·740; 95% CI, 0·730; P<·001), and catheter days per 1,000 patient days decreased from 194·5 in phase 1 to 140·7 in phase 4 (RR, 0·723; 95% CI, 0·719–0·728; P<·001). The reinsertion rate declined from 3·66% in phase 1 to 3·25% in phase 4 (RR, 0·894; 95% CI, 0·834–0·959; P=·0017).

The phased introduction of decision support tools was associated with progressive declines in new catheters, total catheter days, and CAUTIs. Clinical decision support tools offer a viable and scalable intervention to target hospital-wide IUC use and hold promise for other quality improvement initiatives.

Existing studies have not investigated the effectiveness of one long-acting injectable antipsychotic (LAI) versus another in preventing hospitalizations among patients with bipolar disorder (BD). This study was conducted to compare all-cause inpatient healthcare utilization and associated costs among BD patients who initiated LAIs.

This retrospective cohort analysis used the Truven Health Analytics MarketScan® Commercial and Medicaid claims database. Bipolar patients >18 years with at least one claim for one of the following LAIs were identified between 1 January 2013 and 30 June 2014 (identification period): aripiprazole, haloperidol, paliperidone, and risperidone. The first day of initiating an LAI was considered the index date. Logistic regression and generalized linear regression models were conducted to estimate risk of inpatient hospitalization and associated costs during the 1-year follow up.

A total of 1,540 BD patients initiated an LAI: 14.5 percent aripiprazole, 16.3 percent risperidone, 21.0 percent haloperidol, and 48.1 percent paliperidone. With the aripiprazole cohort as the reference group, the odds of having any inpatient hospitalizations were significantly higher in haloperidol [Odds Ratio, OR (95 percent Confidence Interval, CI): 1.49 (1.01 - 2.19)] and risperidone [1.78 (1.19 - 2.66)] cohorts. The paliperidone cohort also had a higher risk of having a hospitalization than aripiprazole, but the difference was not statistically significant (p>.05). Among LAI initiators having any inpatient hospitalizations, the adjusted mean all-cause inpatient costs were lowest in the aripiprazole cohort (USD26,002), followed by risperidone (USD27,937), haloperidol (USD30,411), and paliperidone (USD33,240). However, the cost difference was not statistically significant.

Our study findings highlight the value of aripiprazole in reducing all-cause inpatient hospitalizations and associated costs among patients with BD during the 1-year follow-up. It is worthwhile to note that bipolar diagnoses were identified from healthcare claims coded for reimbursement purposes, thus misclassification was possible. Future studies are warranted to understand the impact of LAI use in a longer period of time.

Existing evidence on clinical and economic effectiveness of one long-acting injectable antipsychotic (LAI) versus another in successful management of schizophrenia is scarce. The study was conducted to compare all-cause inpatient healthcare utilization and associated costs among Medicaid patients with schizophrenia who initiated LAIs.

This retrospective cohort analysis used the Truven Health Analytics MarketScan® Medicaid claims database. Schizophrenia patients >18 years with at least one claim for one of the following LAI were identified between 1 January 2013 and 30 June 2014 (identification period): aripiprazole, fluphenazine, haloperidol, paliperidone palmitate, and risperidone. The first day of initiating an LAI was considered the index date. Patients were followed for 1 year from index date. Logistic and general linear regression models were used to estimate risk of inpatient hospitalization and associated costs during follow up.

Of the identified Medicaid patients with schizophrenia, 1,672 (36.7 percent) initiated an LAI: 44.0 percent received paliperidone, 26.4 percent haloperidol, 13.8 percent risperidone, 9.2 percent aripiprazole, and 6.6 percent fluphenazine. With the aripiprazole cohort as the reference group, the odds of having any inpatient hospitalizations were significantly higher in haloperidol [Odds Ratio, OR (95 percent Confidence Interval, CI): 1.51 (1.05 - 2.16)] and risperidone [OR (95 percent CI): 1.58 (1.07 - 2.33)] cohorts. Fluphenazine and paliperidone palmitate cohorts also had higher risk of having any inpatient hospitalizations compared with aripiprazole, but the differences were not statistically significant (p>.05). Among LAI initiators with any inpatient hospitalizations, the adjusted mean inpatient costs were lowest in the aripiprazole cohort (USD25,616), followed by haloperidol (USD30,811), paliperidone (USD30,833), risperidone (USD31,584), and fluphenazine (USD37,338), although differences were not statistically significant.

Our study findings highlight the value of aripiprazole in reducing inpatient hospitalizations and associated costs among patients with schizophrenia. However, our study is limited as our results are reflective of a multi-state Medicaid population. Future studies are warranted to confirm the results in non-Medicaid patient populations.

Existing findings on effectiveness of long-acting injectable antipsychotics (LAIs) versus oral antipsychotics in preventing hospitalizations are inconclusive. This study was conducted to compare hospitalization costs between Medicaid patients diagnosed with schizophrenia who initiated a LAI and those who changed from one oral antipsychotic to another.

This retrospective cohort analysis used the Truven Health Analytics MarketScan® Medicaid claims database to study patients ≥18 years with schizophrenia. The two cohorts were: “LAI”, defined as initiating LAI (no prior LAI therapy) between 1 January 2013 and 30 June 2014; and “oral”, defined as changing from one oral antipsychotic to another during the same period. The first day of LAI or the new oral antipsychotic was the index date. A linear regression model was conducted to estimate hospitalization costs.

The final sample included 2,861 (36.7 percent) LAI and 4,926 (63.3 percent) oral users. Compared to oral users, LAI patients were younger (mean (Standard Deviation, SD): 39.9 (13.2) versus 42.7 (13.1); p<.001) and had a lower mean Charlson Comorbidity Index score (mean (SD): 1.1 (1.9) versus 1.7 (2.3); p<.001). Of the 877 LAI initiators and 1,688 oral users who were hospitalized during the 1-year post-index follow-up period, the unadjusted mean hospitalization costs for LAI and oral users were USD32,626 and USD36,048, respectively. After adjusting for patient demographic and clinical characteristics, baseline medication use, and baseline ED or hospitalizations, the adjusted average hospitalization costs were USD1,170 lower in LAI initiators than oral users. None of the unadjusted or adjusted differences were statistically significant.

This real-world study suggests that among hospitalized patients, hospitalization costs are lower in LAI initiators than in oral antipsychotic users, although the difference is not statistically significant. Our study is limited as our results are reflective of a multi-state Medicaid population. Future studies are warranted to confirm the results in non-Medicaid patient populations.