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A survey of academic medical-center hospital epidemiologists indicated substantial deviation from Centers for Disease Control and Prevention guidance regarding healthcare providers (HCPs) recovering from coronavirus disease 2019 (COVID-19) returning to work. Many hospitals continue to operate under contingency status and have HCPs return to work earlier than recommended.
Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.
In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.
Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.
Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.
Three-dimensional (3D) food printing is a rapidly emerging technology offering unprecedented potential for customised food design and personalised nutrition. Here, we evaluate the technological advances in extrusion-based 3D food printing and its possibilities to promote healthy and sustainable eating. We consider the challenges in implementing the technology in real-world applications. We propose viable applications for 3D food printing in health care, health promotion and food waste upcycling. Finally, we outline future work on 3D food printing in food safety, acceptability and economics, ethics and regulations.
Unsustainable hunting threatens biodiversity in the tropics through the removal of key seed-dispersing frugivorous primates. Traditionally, hunting in the Amazon Basin was managed through hunter territoriality, with the threat of social sanctions for overexploitation. We examined hunter territoriality and differential prey selection as alternative hypotheses to central-place foraging. Territoriality occurred beyond common hunting grounds, which were on major rivers and immediately surrounding the community. Hunters displayed selectivity in prey choice, with 50% of hunters not hunting primates. The combination of hunter territoriality and differential prey selection means that over 22% of the hunted area of the Sucusari river basin could be considered primate refuge. Of the remaining hunted area, 16% was hunted relatively little by primate hunters. We suggest that the combination of territoriality and selection against primates creates refuges, mitigating the effects of sustained hunting pressure and contributing to the conservation of these species.
Delayed cerebral ischemia (DCI) is a complication of aneurysmal subarachnoid hemorrhage (aSAH) and is associated with significant morbidity and mortality. There is little high-quality evidence available to guide the management of DCI. The Canadian Neurosurgery Research Collaborative (CNRC) is comprised of resident physicians who are positioned to capture national, multi-site data. The objective of this study was to evaluate practice patterns of Canadian physicians regarding the management of aSAH and DCI.
We performed a cross-sectional survey of Canadian neurosurgeons, intensivists, and neurologists who manage aSAH. A 19-question electronic survey (Survey Monkey) was developed and validated by the CNRC following a DCI-related literature review (PubMed, Embase). The survey was distributed to members of the Canadian Neurosurgical Society and to Canadian members of the Neurocritical Care Society. Responses were analyzed using quantitative and qualitative methods.
The response rate was 129/340 (38%). Agreement among respondents was limited to the need for intensive care unit admission, use of clinical and radiographic monitoring, and prophylaxis for the prevention of DCI. Several inconsistencies were identified. Indications for starting hyperdynamic therapy varied. There was discrepancy in the proportion of patients who felt to require IV milrinone, IA vasodilators, or physical angioplasty for treatment of DCI. Most respondents reported their facility does not utilize a standardized definition for DCI.
DCI is an important clinical entity for which no homogeneity and standardization exists in management among Canadian practitioners. The CNRC calls for the development of national standards in the definition, identification, and treatment of DCI.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System. Monoclonal antibody implementation success factors included engagement with local medical providers, therapy batch preparation, placing the infusion center in proximity to emergency services, and creating procedures resilient to EUA changes. Infusion process challenges included confirming patient severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, strained staff, scheduling, and pharmacy coordination. Infusion sites are effective when integrated into pre-existing pandemic response ecosystems and can be implemented with limited staff and physical resources.
The COVID-19 pandemic has shone a spotlight on how health outcomes are unequally distributed among different population groups, with disadvantaged communities and individuals being disproportionality affected in terms of infection, morbidity and mortality, as well as vaccine access. Recently, there has been considerable debate about how social disadvantage and inequality intersect with developmental processes to result in a heightened susceptibility to environmental stressors, economic shocks and large-scale health emergencies. We argue that DOHaD Society members can make important contributions to addressing issues of inequality and improving community resilience in response to COVID-19. In order to do so, it is beneficial to engage with and adopt a social justice framework. We detail how DOHaD can align its research and policy recommendations with a social justice perspective to ensure that we contribute to improving the health of present and future generations in an equitable and socially just way.
To assess the mental health of pregnant women, with reference to anxiety, depression and obsessive-compulsive (OC) symptoms, during the COVID-19 pandemic.
A cross-sectional survey was conducted in Ireland during the third wave of the pandemic between February and March 2021. Psychiatric, social and obstetric information was collected from pregnant women in a Dublin maternity hospital, alongside self-reported measures of mental health status.
Of 392 women responding, 23.7% had anxiety, scoring >9 for GAD-7 (7-item generalised anxiety disorder), 20.4% had depression, scoring >9 for PHQ-9 (9-item depression screening tool: Patient health questionnaire) and 10.3% had obsessive-compulsive disorder (OCD), scoring >13 for Yale–Brown obsessive-compulsive scale symptom checklist (Y-BOCS). Amongst self-reported OCD symptoms, there was a preponderance for obsessions rather than compulsions. Of 392 women, 36.2% described their mental health as worse during the pandemic, most frequently describing symptoms of anxiety and sleep disturbance. When analysed against test scores, self-reported worsening of mental health was significantly associated with higher scores on the GAD-7, PHQ-9 and Y-BOCS scales. The three scores were positively interrelated. Poor mental health scores were associated with self-reported strain in relationship with the baby’s father, and current or previous history of mental illness.
This study found high levels of depression, anxiety and OC symptoms amongst pregnant women during COVID-19. This highlights the vulnerability of this group to mental illness and the importance of enhanced screening and support during pandemics.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
An accurate estimate of the average number of hand hygiene opportunities per patient hour (HHO rate) is required to implement group electronic hand hygiene monitoring systems (GEHHMSs). We sought to identify predictors of HHOs to validate and implement a GEHHMS across a network of critical care units.
Multicenter, observational study (10 hospitals) followed by quality improvement intervention involving 24 critical care units across 12 hospitals in Ontario, Canada.
Critical care patient beds were randomized to receive 1 hour of continuous direct observation to determine the HHO rate. A Poisson regression model determined unit-level predictors of HHOs. Estimates of average HHO rates across different types of critical care units were derived and used to implement and evaluate use of GEHHMS.
During 2,812 hours of observation, we identified 25,417 HHOs. There was significant variability in HHO rate across critical care units. Time of day, day of the week, unit acuity, patient acuity, patient population and use of transmission-based precautions were significantly associated with HHO rate. Using unit-specific estimates of average HHO rate, aggregate HH adherence was 30.0% (1,084,329 of 3,614,908) at baseline with GEHHMS and improved to 38.5% (740,660 of 1,921,656) within 2 months of continuous feedback to units (P < .0001).
Unit-specific estimates based on known predictors of HHO rate enabled broad implementation of GEHHMS. Further longitudinal quality improvement efforts using this system are required to assess the impact of GEHHMS on both HH adherence and clinical outcomes within critically ill patient populations.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
Colleges and universities around the world engaged diverse strategies during the COVID-19 pandemic. Baylor University, a community of ˜22,700 individuals, was 1 of the institutions which resumed and sustained operations. The key strategy was establishment of multidisciplinary teams to develop mitigation strategies and priority areas for action. This population-based team approach along with implementation of a “Swiss Cheese” risk mitigation model allowed small clusters to be rapidly addressed through testing, surveillance, tracing, isolation, and quarantine. These efforts were supported by health protocols including face coverings, social distancing, and compliance monitoring. As a result, activities were sustained from August 1 to December 8, 2020. There were 62,970 COVID-19 tests conducted with 1435 people testing positive for a positivity rate of 2.28%. A total of 1670 COVID-19 cases were identified with 235 self-reports. The mean number of tests per week was 3500 with approximately 80 of these positive (11/d). More than 60 student tracers were trained with over 120 personnel available to contact trace, at a ratio of 1 per 400 university members. The successes and lessons learned provide a framework and pathway for similar institutions to mitigate the ongoing impacts of COVID-19 and sustain operations during a global pandemic.
This chapter comprises the following sections: names, taxonomy, subspecies and distribution, descriptive notes, habitat, movements and home range, activity patterns, feeding ecology, reproduction and growth, behavior, parasites and diseases, status in the wild, and status in captivity.
Restless legs syndrome (RLS) is a neurological disorder characterized by an urge to move and uncomfortable sensations. Genetic studies have identified polymorphisms in up to 19 risk loci, including MEIS1 and BTBD9. Rodents deficient in either homolog show RLS-like phenotypes. However, whether MEIS1 and BTBD9 interact in vivo is unclear. Here, with C. elegans, we observed that the hyperactive egg-laying behavior caused by loss of BTBD9 homolog was counteracted by knockdown of MEIS1 homolog. This was further investigated in mutant mice with Btbd9, Meis1, or both knocked out. The double knockout mice showed an earlier onset of the motor deficit in a wheel running test but did not have increased sensitivity to heat stimuli as observed in single knock outs. Meis1 protein level was not influenced by Btbd9 deficiency, and Btbd9 transcription was not affected by Meis1 haploinsufficiency. Our results demonstrate that MEIS1 and BTBD9 do not regulate each other.