Automated virtual reality therapies are being developed to increase access to psychological interventions. We assessed the experience with one such therapy of patients diagnosed with psychosis, including satisfaction, side effects, and positive experiences of access to the technology. We tested whether side effects affected therapy.

In a clinical trial 122 patients diagnosed with psychosis completed baseline measures of psychiatric symptoms, received gameChange VR therapy, and then completed a satisfaction questionnaire, the Oxford-VR Side Effects Checklist, and outcome measures.

79 (65.8%) patients were very satisfied with VR therapy, 37 (30.8%) were mostly satisfied, 3 (2.5%) were indifferent/mildly dissatisfied, and 1 (0.8%) person was quite dissatisfied. The most common side effects were: difficulties concentrating because of thinking about what might be happening in the room (n = 17, 14.2%); lasting headache (n = 10, 8.3%); and the headset causing feelings of panic (n = 9, 7.4%). Side effects formed three factors: difficulties concentrating when wearing a headset, feelings of panic using VR, and worries following VR. The occurrence of side effects was not associated with number of VR sessions, therapy outcomes, or psychiatric symptoms. Difficulties concentrating in VR were associated with slightly lower satisfaction. VR therapy provision and engagement made patients feel: proud (n = 99, 81.8%); valued (n = 97, 80.2%); and optimistic (n = 96, 79.3%).

Patients with psychosis were generally very positive towards the VR therapy, valued having the opportunity to try the technology, and experienced few adverse effects. Side effects did not significantly impact VR therapy. Patient experience of VR is likely to facilitate widespread adoption.

Clinically significant weight gain (CSWG) is associated with increased morbidity and mortality. This study describes CSWG and comorbidities observed in patients with bipolar I disorder (BD-I) and schizophrenia (SZ) after initiating select second-generation antipsychotics (SGAs).

Percent change in weight, CSWG (=7% weight increase), and incident comorbidities within 12 months of treatment were assessed among patients initiating oral SGAs of moderate-to-high weight gain risk using medical records/claims (OM1 Real-World Data Cloud; January 2013-February 2020). Oral SGAs included clozapine (SZ), iloperidone (SZ), paliperidone (SZ), olanzapine, olanzapine/fluoxetine (BD-I), quetiapine, and risperidone. Outcomes were stratified by baseline body mass index and reported descriptively.

Among patients with BD-I (N = 9142) and SZ (N = 8174), approximately three-quarters were overweight/obese at baseline. During treatment (mean duration = 30 weeks), average percent weight increase was 3.7% (BD-I) and 3.3% (SZ). Average percent weight increase was highest for underweight/normal weight patients (BD-I = 5.5%; SZ = 4.8%), followed by overweight (BD-I = 3.8%; SZ = 3.4%) and obese patients (BD-I = 2.7%; SZ = 2.3%). Within 3 months of treatment, 12% of all patients experienced CSWG. A total of 11.3% (BD-I) and 14.7% (SZ) of patients developed coronary artery disease, hypertension, dyslipidemia, or type 2 diabetes within 12 months of treatment; development of comorbidities was highest among overweight/obese patients and those with CSWG.

Patients who were underweight/normal weight at baseline had the greatest percent change in weight during treatment. Increased comorbidities were observed within 12 months of treatment, specifically among overweight/obese patients and those with CSWG. The magnitude of weight gain and development of comorbidities were similar for patients with BD-I and SZ.

Alkermes, Inc.

To assess preventability of hospital-onset bacteremia and fungemia (HOB), we developed and evaluated a structured rating guide accounting for intrinsic patient and extrinsic healthcare-related risks.

HOB preventability rating guide was compared against a reference standard expert panel.

A 10-member panel of clinical experts was assembled as the standard of preventability assessment, and 2 physician reviewers applied the rating guide for comparison.

The expert panel independently rated 82 hypothetical HOB scenarios using a 6-point Likert scale collapsed into 3 categories: preventable, uncertain, or not preventable. Consensus was defined as concurrence on the same category among ≥70% experts. Scenarios without consensus were deliberated and followed by a second round of rating.

Two reviewers independently applied the rating guide to adjudicate the same 82 scenarios in 2 rounds, with interim revisions. Interrater reliability was evaluated using the κ (kappa) statistic.

Expert panel consensus criteria were met for 52 scenarios (63%) after 2 rounds.

After 2 rounds, guide-based rating matched expert panel consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewers 1 and 2, respectively. Agreement rates between the 2 reviewers were 84% overall (κ, 0.76; 95% confidence interval [CI], 0.64–0.88]) and 87% (κ, 0.79; 95% CI, 0.65–0.94) for the 52 scenarios with expert consensus.

Preventability ratings of HOB scenarios by 2 reviewers using a rating guide matched expert consensus in most cases with moderately high interreviewer reliability. Although diversity of expert opinions and uncertainty of preventability merit further exploration, this is a step toward standardized assessment of HOB preventability.

The process of identifying and connecting with clinical trial study teams can be challenging and difficult for members of the public. The national volunteer community registry, ResearchMatch, and the public clinical trials search tool, Trials Today, work in tandem to bridge this connection by providing a streamlined process for potential participants to identify clinical trials which may be of interest.

Building on the existing infrastructure of ResearchMatch and Trials Today, we created a mechanism by which the public can request that their basic contact information (e.g., email/phone) be securely shared with any actively recruiting clinical trial, including trials with no existing relationship with ResearchMatch.

Within the first 2 years of use (July 2019–July 2021), ResearchMatch Volunteers sent 12,251 requests to study teams. On average, 20% of these requests were accepted by the study teams.

The utilization of this tool indicates that there is active interest among members of the public to independently contact study teams about trials of interest. Additionally, research teams unaffiliated with ResearchMatch are willing to at minimum accept contact information. This allows ResearchMatch to successfully serve as a medium, connecting members of the public with actively recruiting trials.

To improve maternal health outcomes, increased diversity is needed among pregnant people in research studies and community surveillance. To expand the pool, we sought to develop a network encompassing academic and community obstetrics clinics. Typical challenges in developing a network include site identification, contracting, onboarding sites, staff engagement, participant recruitment, funding, and institutional review board approvals. While not insurmountable, these challenges became magnified as we built a research network during a global pandemic. Our objective is to describe the framework utilized to resolve pandemic-related issues.

We developed a framework for site-specific adaptation of the generalized study protocol. Twice monthly video meetings were held between the lead academic sites to identify local challenges and to generate ideas for solutions. We identified site and participant recruitment challenges and then implemented solutions tailored to the local workflow. These solutions included the use of an electronic consent and videoconferences with local clinic leadership and staff. The processes for network development and maintenance changed to address issues related to the COVID-19 pandemic. However, aspects of the sample processing/storage and data collection elements were held constant between sites.

Adapting our consenting approach enabled maintaining study enrollment during the pandemic. The pandemic amplified issues related to contracting, onboarding, and IRB approval. Maintaining continuity in sample management and clinical data collection allowed for pooling of information between sites.

Adaptability is key to maintaining network sites. Rapidly changing guidelines for beginning and continuing research during the pandemic required frequent intra- and inter-institutional communication to navigate.

Whole-genome sequencing (WGS) shotgun metagenomics (metagenomics) attempts to sequence the entire genetic content straight from the sample. Diagnostic advantages lie in the ability to detect unsuspected, uncultivatable, or very slow-growing organisms.

To evaluate the clinical and economic effects of using WGS and metagenomics for outbreak management in a large metropolitan hospital.

Cost-effectiveness study.

Intensive care unit and burn unit of large metropolitan hospital.

Simulated intensive care unit and burn unit patients.

We built a complex simulation model to estimate pathogen transmission, associated hospital costs, and quality-adjusted life years (QALYs) during a 32-month outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB). Model parameters were determined using microbiology surveillance data, genome sequencing results, hospital admission databases, and local clinical knowledge. The model was calibrated to the actual pathogen spread within the intensive care unit and burn unit (scenario 1) and compared with early use of WGS (scenario 2) and early use of WGS and metagenomics (scenario 3) to determine their respective cost-effectiveness. Sensitivity analyses were performed to address model uncertainty.

On average compared with scenario 1, scenario 2 resulted in 14 fewer patients with CRAB, 59 additional QALYs, and $75,099 cost savings. Scenario 3, compared with scenario 1, resulted in 18 fewer patients with CRAB, 74 additional QALYs, and $93,822 in hospital cost savings. The likelihoods that scenario 2 and scenario 3 were cost-effective were 57% and 60%, respectively.

The use of WGS and metagenomics in infection control processes were predicted to produce favorable economic and clinical outcomes.