Among those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used.

In a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model.

Strongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use.

Network analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.

We identify a set of essential recent advances in climate change research with high policy relevance, across natural and social sciences: (1) looming inevitability and implications of overshooting the 1.5°C warming limit, (2) urgent need for a rapid and managed fossil fuel phase-out, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future contribution of natural carbon sinks, (5) intertwinedness of the crises of biodiversity loss and climate change, (6) compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems.

The Intergovernmental Panel on Climate Change Assessment Reports provides the scientific foundation for international climate negotiations and constitutes an unmatched resource for researchers. However, the assessment cycles take multiple years. As a contribution to cross- and interdisciplinary understanding of climate change across diverse research communities, we have streamlined an annual process to identify and synthesize significant research advances. We collected input from experts on various fields using an online questionnaire and prioritized a set of 10 key research insights with high policy relevance. This year, we focus on: (1) the looming overshoot of the 1.5°C warming limit, (2) the urgency of fossil fuel phase-out, (3) challenges to scale-up carbon dioxide removal, (4) uncertainties regarding future natural carbon sinks, (5) the need for joint governance of biodiversity loss and climate change, (6) advances in understanding compound events, (7) accelerated mountain glacier loss, (8) human immobility amidst climate risks, (9) adaptation justice, and (10) just transitions in food systems. We present a succinct account of these insights, reflect on their policy implications, and offer an integrated set of policy-relevant messages. This science synthesis and science communication effort is also the basis for a policy report contributing to elevate climate science every year in time for the United Nations Climate Change Conference.

We highlight recent and policy-relevant advances in climate change research – with input from more than 200 experts.

Brain in Hand (BIH) is a UK-based digital self-support system for managing anxiety and social functioning.

To identify the impact of BIH on the psychological and social functioning of adults with autism.

Adults with diagnosed or suspected DSM-5 (level 1) autism, identified by seven NHS autism services in England and Wales, were recruited for a 12-week prospective mixed-methods cohort study. The primary quantitative outcome measures were the Health of the Nation Outcome Scales for People with Learning Disabilities (HONOS-LD) and the Hospital Anxiety and Depression Scale (HADS). Fisher's exact test explored sociodemographic associations. Paired t-test was utilised for pre–post analysis of overall effectiveness of BIH. Multivariable linear regression models, univariable pre–post analysis, Wilcoxon signed-rank test, logistic regression analysis, Bonferroni correction and normative analysis were used to give confidence in changes identified. A thematic analysis of semi-structured exist interviews following Braun and Clarke's six-step process of 10% of participants who completed the study was undertaken.

Sixty-six of 99 participants completed the study. There was significant reduction in mean HONOS-LD scores, with 0.65 s.d. decrease in those who used BIH for 12 weeks. Significant positive changes were identified in HONOS-LD subdomains of ‘self-injurious behaviours’, ‘memory and orientation’, ‘communication problems in understanding’, ‘occupation and activities’ and ‘problems with relationship’. A significant reduction in the anxiety, but not depression, component of the HADS scores was identified. Thematic analysis showed high confidence in BIH.

BIH improved anxiety and other clinical, social and functioning outcomes of adults with autism.

Medication nonadherence is a public health concern and can impact clinical trial data quality. Traditional compliance collection (pill counts, diaries) can be unreliable in central nervous system trials. As such, strategies such as adherence technologies may play a key role in trial outcomes. AiCure, a computer vision-assisted dosing mobile application (app), collects dosing data and connects patients to sites for dosing support. Phone-based computer vision algorithms confirm dosing and transfer videos for artificial intelligence and human review. Boehringer Ingelheim is partnering with AiCure on pilot trials using AiCure adherence data to improve patient retention and clinical trial data quality. Here we report initial findings.

This pilot used data from two Phase II trials on the efficacy and safety of BI 409306 in people with schizophrenia (NCT03351244) or Attenuated Psychosis Syndrome (NCT03230097). The AiCure mobile app alerted participants to dosing protocols. The dose event was visually confirmed, providing sites a real-time view of adherence and allowing for targeted outreach and intervention. Adherence data from the first 2 weeks generated quantitative, machine-learning models to predict the individual adherence over the trial. Predictive modeling explored different monitoring periods (7-, 10-, and 14-day) and adherence cutoff points (0.8, 0.7, 0.6).

Initial AiCure assessment identified 43% of participants in NCT03351244 as ≤80% compliant (definition of compliance >80% compliant). Variance in adherence rates between electronic case report forms (eCRF; 78%) and AiCure (26%) data was also observed in the highly compliant/adherent group in NCT03230097. Using the first 2 weeks of adherence data (both studies combined), a participant’s adherence predicted their average adherence for the remainder of the trial. Observation of a participant’s adherence for the latest 4 weeks predicted the probability of premature dropout from the trial. There were further correlations of lower predicted adherence with actual disposition-based dropouts.

The early adherence predictive model (0.6 adherence cutoff) identified 22%, 20%, and 19% of patients for trial NCT03351244 (total n=235) as high-risk patients (low-adherence prediction) across 7-, 10-, and 14-day monitoring periods, respectively. Of those high-risk patients, 81%, 90%, and 96%, respectively, were truly nonadherent based on actual adherence data. The 14-day monitoring period model provided the lowest false omission rate, indicative of a better performing model.

AiCure data provided insights into patient behavior and adherence patterns which would not be available via CRF. Predictive models developed with AiCure adherence data can identify and predict future poor adherers. This creates opportunities to plan interventions and mitigation strategies to improve patient adherence during trials, thereby providing test drugs the best opportunity at proving efficacy.

Boehringer Ingelheim International GmbH (NCT03351244/1289-0049 and NCT03230097/1289-0032)

We summarize what we assess as the past year's most important findings within climate change research: limits to adaptation, vulnerability hotspots, new threats coming from the climate–health nexus, climate (im)mobility and security, sustainable practices for land use and finance, losses and damages, inclusive societal climate decisions and ways to overcome structural barriers to accelerate mitigation and limit global warming to below 2°C.

We synthesize 10 topics within climate research where there have been significant advances or emerging scientific consensus since January 2021. The selection of these insights was based on input from an international open call with broad disciplinary scope. Findings concern: (1) new aspects of soft and hard limits to adaptation; (2) the emergence of regional vulnerability hotspots from climate impacts and human vulnerability; (3) new threats on the climate–health horizon – some involving plants and animals; (4) climate (im)mobility and the need for anticipatory action; (5) security and climate; (6) sustainable land management as a prerequisite to land-based solutions; (7) sustainable finance practices in the private sector and the need for political guidance; (8) the urgent planetary imperative for addressing losses and damages; (9) inclusive societal choices for climate-resilient development and (10) how to overcome barriers to accelerate mitigation and limit global warming to below 2°C.

Science has evidence on barriers to mitigation and how to overcome them to avoid limits to adaptation across multiple fields.

Noninterventional naturalistic studies are an important complement to randomized controlled trials. Aripiprazole once-monthly (AOM) is an atypical antipsychotic in a long-acting injectable formulation.

A pooled analysis of two noninterventional studies was undertaken to validate previous results on AOM effectiveness and safety in a larger population and improve statistical power for preplanned subgroup analyses. We analyzed data from 409 patients with schizophrenia who were treated with AOM and were enrolled in noninterventional studies in Germany (via noninterventional studies registry 15,960 N) and Canada (NCT02131415). Data collected at baseline, 3 and 6 months were analyzed. Among the endpoints were psychopathology (brief psychiatric rating scale [BPRS]) and disease severity (clinical global impression [CGI]).

Mean patient age was 38.9 (SD 14.8) years, and 59.9% were male. BPRS decreased from 48.1 (SD 15.6) at baseline to 36.5 (SD 13.7) at month 6 (p < 0.001). CGI decreased from 4.47 (SD 0.90) at baseline to 3.64 (SD 1.16) at month 6 (p < 0.001). A total of 54.4% were responders (at least 20% reduction) on the BPRS, and 56.5% had a CGI-S-score that was at least 1 level better than baseline. A total of 43.4% were considered responders on both the BPRS and CGI scales. A total of 45.2% were considered in remission. Adverse events were rare and corresponded to the previously known safety profile of AOM.

Treatment with AOM for patients with schizophrenia appeared effective and safe under real-life conditions.

The burden of healthcare-associated infections (HAIs) is higher in low- and middle-income countries, but HAIs are often missed because surveillance is not conducted. Here, we describe the identification of and response to a cluster of Burkholderia cepacia complex (BCC) bloodstream infections (BSIs) associated with high mortality in a surgical ICU (SICU) that joined an HAI surveillance network.

A 780-bed, tertiary-level, public teaching hospital in northern India.

After detecting a cluster of BCC in the SICU, cases were identified by reviewing laboratory registers and automated identification and susceptibility testing outputs. Sociodemographic details, clinical records, and potential exposure histories were collected, and a self-appraisal of infection prevention and control (IPC) practices using assessment tools from the World Health Organization and the US Centers for Disease Control and Prevention was conducted. Training and feedback were provided to hospital staff. Environmental samples were collected from high-touch surfaces, intravenous medications, saline, and mouthwash.

Between October 2017 and October 2018, 183 BCC BSI cases were identified. Case records were available for 121 case patients. Of these 121 cases, 91 (75%) were male, the median age was 35 years, and 57 (47%) died. IPC scores were low in the areas of technical guidelines, human resources, and monitoring and evaluation. Of the 30 environmental samples, 4 grew BCC. A single source of the outbreak was not identified.

Implementing standardized HAI surveillance in a low-resource setting detected an ongoing Burkholderia cepacia outbreak. The outbreak investigation and use of a multimodal approach reduced incident cases and informed changes in IPC practices.

To determine whether cascade reporting is associated with a change in meropenem and fluoroquinolone consumption.

A quasi-experimental study was conducted using an interrupted time series to compare antimicrobial consumption before and after the implementation of cascade reporting.

A 399-bed, tertiary-care, Veterans’ Affairs medical center.

Antimicrobial consumption data across 8 inpatient units were extracted from the Center for Disease Control and Prevention (CDC) National Health Safety Network (NHSN) antimicrobial use (AU) module from April 2017 through March 2019, reported as antimicrobial days of therapy (DOT) per 1,000 days present (DP).

Cascade reporting is a strategy of reporting antimicrobial susceptibility test results in which secondary agents are only reported if an organism is resistant to primary, narrow-spectrum agents. A multidisciplinary team developed cascade reporting algorithms for gram-negative bacteria based on local antibiogram and infectious diseases practice guidelines, aimed at restricting the use of fluoroquinolones and carbapenems. The algorithms were implemented in March 2018.

Following the implementation of cascade reporting, mean monthly meropenem (P =.005) and piperacillin/tazobactam (P = .002) consumption decreased and cefepime consumption increased (P < .001). Ciprofloxacin consumption decreased by 2.16 DOT per 1,000 DP per month (SE, 0.25; P < .001). Clostridioides difficile rates did not significantly change.

Ciprofloxacin consumption significantly decreased after the implementation of cascade reporting. Mean meropenem consumption decreased after cascade reporting was implemented, but we observed no significant change in the slope of consumption. cascade reporting may be a useful strategy to optimize antimicrobial prescribing.

The effectiveness of mechanical thrombectomy (MT) in elderly stroke patients remains debated. We aimed to describe outcomes and their predictors in a cohort of patients aged ≥ 85 years treated with MT.

Data from consecutive patients aged ≥ 85 years undergoing MT at two stroke centers between January 2016 and November 2019 were reviewed. Admission National Institutes of Health Stroke Scale (NIHSS), pre-stroke, and 3-month modified Rankin scale (mRS) were collected. Successful recanalization was defined as modified thrombolysis in cerebral ischemia score ≥ 2b. Good outcome was defined as mRS 0–3 or equal to pre-stroke mRS at 3 months.

Of 151 included patients, successful recanalization was achieved in 74.2%. At 3 months, 44.7% of patients had a good outcome and 39% had died. Any intracranial hemorrhage (ICH) and symptomatic ICH occurred in 20.3% and 3.6%, respectively. Logistic regression analysis identified lower pre-stroke mRS score (adjusted odds ratio [aOR], 0.52; 95% CI, 0.36–0.76), lower admission NIHSS score (aOR, 0.90; 95% CI, 0.83–0.97), successful recanalization (aOR, 3.65; 95% CI, 1.32–10.09), and absence of ICH on follow-up imaging (aOR, 0.42; 95% CI, 0.08–0.75), to be independent predictors of good outcome. Patients with successful recanalization had a higher proportion of good outcome (45.3% vs 34.3%, p = 0.013) and lower mortality at 3 months (35.8% vs 48.6%, p = 0.006) compared to patients with unsuccessful recanalization.

Among patients aged ≥ 85 years, successful recanalization with MT is relatively common and associated with better 3-month outcome and lower mortality than failed recanalization. Attempting to achieve recanalization in elderly patients using MT appears reasonable.

During the Randomized Assessment of Rapid Endovascular Treatment (EVT) of Ischemic Stroke (ESCAPE) trial, patient-level micro-costing data were collected. We report a cost-effectiveness analysis of EVT, using ESCAPE trial data and Markov simulation, from a universal, single-payer system using a societal perspective over a patient’s lifetime.

Primary data collection alongside the ESCAPE trial provided a 3-month trial-specific, non-model, based cost per quality-adjusted life year (QALY). A Markov model utilizing ongoing lifetime costs and life expectancy from the literature was built to simulate the cost per QALY adopting a lifetime horizon. Health states were defined using the modified Rankin Scale (mRS) scores. Uncertainty was explored using scenario analysis and probabilistic sensitivity analysis.

The 3-month trial-based analysis resulted in a cost per QALY of $201,243 of EVT compared to the best standard of care. In the model-based analysis, using a societal perspective and a lifetime horizon, EVT dominated the standard of care; EVT was both more effective and less costly than the standard of care (−$91). When the time horizon was shortened to 1 year, EVT remains cost savings compared to standard of care (∼$15,376 per QALY gained with EVT). However, if the estimate of clinical effectiveness is 4% less than that demonstrated in ESCAPE, EVT is no longer cost savings compared to standard of care.

Results support the adoption of EVT as a treatment option for acute ischemic stroke, as the increase in costs associated with caring for EVT patients was recouped within the first year of stroke, and continued to provide cost savings over a patient’s lifetime.

Clinical Trial Registration: NCT01778335

During the COVID-19 pandemic, the use of telemedicine as a way to reduce COVID-19 infections was noted and consequently deregulated. However, the degree of telemedicine regulation varies from country to country, which may alter the widespread use of telemedicine. This study aimed to clarify the telepsychiatry regulations for each collaborating country/region before and during the COVID-19 pandemic.

We used snowball sampling within a global network of international telepsychiatry experts. Thirty collaborators from 17 different countries/regions responded to a questionnaire on barriers to the use and implementation of telepsychiatric care, including policy factors such as regulations and reimbursement at the end of 2019 and as of May 2020.

Thirteen of 17 regions reported a relaxation of regulations due to the pandemic; consequently, all regions surveyed stated that telepsychiatry was now possible within their public healthcare systems. In some regions, restrictions on prescription medications allowed via telepsychiatry were eased, but in 11 of the 17 regions, there were still restrictions on prescribing medications via telepsychiatry. Lower insurance reimbursement amounts for telepsychiatry consultations v. in-person consultations were reevaluated in four regions, and consequently, in 15 regions telepsychiatry services were reimbursed at the same rate (or higher) than in-person consultations during the COVID-19 pandemic.

Our results confirm that, due to COVID-19, the majority of countries surveyed are altering telemedicine regulations that had previously restricted the spread of telemedicine. These findings provide information that could guide future policy and regulatory decisions, which facilitate greater scale and spread of telepsychiatry globally.