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Among patients with schizophrenia (SZ) and bipolar I disorder (BD-I) treated with second-generation antipsychotics (SGAs), clinically-significant weight gain (CSWG) and treatment interruptions (TIs) are challenges that may result in morbidity/mortality.
CSWG and TIs were assessed among patients who initiated oral SGAs of moderate-to-high weight gain risk (no exposure to index SGAs/first-generation antipsychotics for =12 months) using medical records/claims (OM1 Data Cloud; January 2013-February 2020). Outcomes included CSWG (=7% increase in baseline weight) and TIs (switches [to SGAs of low weight gain risk/long-acting injectables] or discontinuations [no SGAs for >30 days]). Descriptive analyses included proportions of patients with CSWG and TIs, and median time to these outcomes.
Approximately three-quarters of patients were overweight/obese at baseline (SZ: N=8,174; BD-I: N=9,142). Within 3 months of SGA initiation, 12% of all patients experienced CSWG. For patients on treatment with index SGAs for >6 months (SZ: 29%; BD-I: 27%), 28% (SZ) and 30% (BD-I) experienced CSWG during follow-up. Median time to CSWG was 14 weeks. CSWG results were numerically similar among patients with SZ and BD-I.
Over 96% of patients had TIs during follow-up (median time of 12 [SZ] and 13 [BD-I] weeks). Among patients with CSWG and subsequent TIs and weight measurements, 74% did not return to baseline weight after interrupting treatment; the remainder returned to baseline weight with median times of 38 (SZ) and 39 (BD-I) weeks. Results suggest that most patients with CSWG do not return to baseline weight after stopping treatment with oral SGAs of moderate-to-high weight gain risk.
Secure forensic mental health services treat patients with high rates of treatment-resistant psychoses. High rates of obesity and medical comorbidities are common. Population-based studies have identified high-risk groups in the event of SARS-CoV-2 infection, including those with problems such as obesity, lung disease and immune-compromising conditions. Structured assessment tools exist to ascertain the risk of adverse outcome in the event of SARS-CoV-2 infection.
To assess risk of adverse outcome in the event of SARS-CoV-2 infection in a complete population of forensic psychiatry patients using structured assessment tools.
All patients of a national forensic mental health service (n = 141) were rated for risk of adverse outcome in the event of SARS-CoV-2 infection, using two structured tools, the COVID-Age tool and the COVID-Risk tool.
We found high rates of relevant physical comorbidities. Mean chronological age was 45.5 years (s.d. = 11.4, median 44.1), mean score on the COVID-Age tool was 59.1 years (s.d. = 19.4, median 58.0), mean difference was 13.6 years (s.d. = 15.6), paired t = 10.9, d.f. = 140, P < 0.001. Three patients (2.1%) were chronologically over 70 years of age, compared with 43 (30.5%) with a COVID-Age over 70 (χ2 = 6.99, d.f. = 1, P = 0.008, Fisher's exact test P = 0.027).
Patients in secure forensic psychiatric services represent a high-risk group for adverse outcomes in the event of SARS-COV-2 infection. Population-based guidance on self-isolation and other precautions based on chronological age may not be sufficient. There is an urgent need for better physical health research and treatment in this group.
The COVID-19 pandemic prompted the development and implementation of hundreds of clinical trials across the USA. The Trial Innovation Network (TIN), funded by the National Center for Advancing Translational Sciences, was an established clinical research network that pivoted to respond to the pandemic.
The TIN’s three Trial Innovation Centers, Recruitment Innovation Center, and 66 Clinical and Translational Science Award Hub institutions, collaborated to adapt to the pandemic’s rapidly changing landscape, playing central roles in the planning and execution of pivotal studies addressing COVID-19. Our objective was to summarize the results of these collaborations and lessons learned.
The TIN provided 29 COVID-related consults between March 2020 and December 2020, including 6 trial participation expressions of interest and 8 community engagement studios from the Recruitment Innovation Center. Key lessons learned from these experiences include the benefits of leveraging an established infrastructure, innovations surrounding remote research activities, data harmonization and central safety reviews, and early community engagement and involvement.
Our experience highlighted the benefits and challenges of a multi-institutional approach to clinical research during a pandemic.
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.
The approach taken to support individuals during the coronavirus disease 2019 (COVID-19) pandemic needs to take into account the requirements of people with intellectual disabilities and/or autism, who represent a major vulnerable group, with higher rates of co-occurring health conditions and a greater risk of dying prematurely. To date, little evidence on COVID-related concerns have been produced and no report has provided structured feedback from the point of view of people with intellectual disabilities and/or autism or of their family/carers.
To provide systemised evidence-based information of the priority concerns for people with intellectual disabilities and/or autism regarding the COVID-19 pandemic.
Senior representatives of major UK-based professional and service-user representative organisations with a stake in the care of people with intellectual disabilities and/or autism were contacted to provide a list of concerns across three domains: ‘mental health and challenging behaviour’, ‘physical health and epilepsy’ and ‘social circumstances and support’. The feedback was developed into statements on frequently reported priorities. These statements were then rated independently by expert clinicians. A video-conference meeting to reconcile outliers and to generate a consensus statement list was held.
Thirty-two organisations were contacted, of which 26 (81%) replied. From the respondent's data, 30 draft consensus statements were generated. Following expert clinician review, there was initially strong consensus for seven statements (23%), increasing to 27 statements (90%) following video conferencing.
These recommendations highlight the expectations of people with intellectual disabilities and/or autism in the current pandemic. This could support policymakers and professionals’ deliver and evidence person-centred care.
When a poorly conducting drop that is surrounded by a more conducting exterior fluid is subjected to an electric field, the drop can deform into an oblate shape at low field strengths. Such drops become unstable at high field strengths and display two types of dynamics, dimpling and equatorial streaming, the physics of which is currently not understood. If the drop is more viscous, dimples form and grow at the poles of the drop and eventually the discocyte-shaped drop breaks up to form a torus. If the exterior fluid is more viscous, the drop deforms into a lens and sheds rings from the equator that subsequently break into a number of smaller droplets. A theoretical explanation as to why dimple- and lens-shaped drops occur, and the mechanisms for the onset of these instabilities, are provided by determining steady-state solutions by simulation and inferring their stability from bifurcation analysis. For large drop viscosities, electric shear stress is shown to play a dominant role and to result in dimpling. For small drop viscosities, equatorial normal stresses (electric, hydrodynamic and capillary) become unbounded and lead to the lens shape.
Background: Hospital-onset bacteremia and fungemia (HOB) may be a preventable hospital-acquired condition and a potential healthcare quality measure. We developed and evaluated a tool to assess the preventability of HOB and compared it to a more traditional consensus panel approach. Methods: A 10-member healthcare epidemiology expert panel independently rated the preventability of 82 hypothetical HOB case scenarios using a 6-point Likert scale (range, 1= “Definitively or Almost Certainly Preventable” to 6= “Definitely or Almost Certainly Not Preventable”). Ratings on the 6-point scale were collapsed into 3 categories: Preventable (1–2), Uncertain (3–4), or Not preventable (5–6). Consensus was defined as concurrence on the same category among ≥70% expert raters. Cases without consensus were deliberated via teleconference, web-based discussion, and a second round of rating. The proportion meeting consensus, overall and by predefined HOB source attribution, was calculated. A structured HOB preventability rating tool was developed to explicitly account for patient intrinsic and extrinsic healthcare-related risks (Fig. 1). Two additional physician reviewers independently applied this tool to adjudicate the same 82 case scenarios. The tool was iteratively revised based on reviewer feedback followed by repeat independent tool-based adjudication. Interrater reliability was evaluated using the Kappa statistic. Proportion of cases where tool-based preventability category matched expert consensus was calculated. Results: After expert panel round 1, consensus criteria were met for 29 cases (35%), which increased to 52 (63%) after round 2. Expert consensus was achieved more frequently for respiratory or surgical site infections than urinary tract and central-line–associated bloodstream infections (Fig. 2a). Most likely to be rated preventable were vascular catheter infections (64%) and contaminants (100%). For tool-based adjudication, following 2 rounds of rating with interim tool revisions, agreement between the 2 reviewers was 84% for cases overall (κ, 0.76; 95% CI, 0.64–0.88]), and 87% for the 52 cases with expert consensus (κ, 0.79; 95% CI, 0.65–0.94). Among cases with expert consensus, tool-based rating matched expert consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewer 1 and reviewer 2, respectively. The proportion of cases rated “uncertain“ was lower among tool-based adjudicated cases with reviewer agreement (15 of 69) than among cases with expert consensus (23 of 52) (Fig. 2b). Conclusions: Healthcare epidemiology experts hold varying perspectives on HOB preventability. Structured tool-based preventability rating had high interreviewer reliability, matched expert consensus in most cases, and rated fewer cases with uncertain preventability compared to expert consensus. This tool is a step toward standardized assessment of preventability in future HOB evaluations.
Background: In 2018, the Maryland Department of Health, in collaboration with the University of Maryland and Johns Hopkins University, created the Statewide Prevention and Reduction of Clostridioides difficile (SPARC) collaborative to reduce C. difficile as specified in Healthy People 2020. Methods: The SPARC collaborative recruited hospitals contributing most cases to statewide C. difficile standardized infection ratio (SIR), according to data reported to the National Healthcare Safety Network (NHSN). SPARC developed intervention bundles around 4 domains: infection prevention, environmental cleaning, and diagnostic and antimicrobial stewardship. Each facility completed a self-assessment followed by an on-site, day-long, peer-to-peer (P2P) evaluation with 8–12 SPARC subject matter experts (SMEs) representing each domain. The SMEs met with hospital executive leadership and then led 4 domain-based group discussions with relevant hospital team leaders. To identify policy and practice gaps, SMEs visited hospital inpatient units for informal interviews with frontline staff. In a closing session, SPARC SMEs, hospital executives, and team leaders reconvened to discuss preliminary findings. This included review of covert observation data (hand hygiene, personal protective equipment compliance, environmental cleaning) obtained by SPARC team 1–2 weeks prior. Final SPARC P2P written recommendations guided development of customized interventions at each hospital. SPARC provided continuous support (follow up phone calls, educational webinars, technical support, didactic training for antimicrobial stewardship pharmacists) to enhance facility-specific implementation. For every quarter, we categorized C. difficile NHSN data for each Maryland hospital into “SPARC” or “non-SPARC” based on participation status. Using negative binomial mixed models, we analyzed difference-in-difference of pre- and postincidence rate ratios (IRRs) for SPARC and non-SPARC hospitals, which allowed estimation of change attributable to SPARC participation independent of other time-varying factors. Results: Overall, 13 of 48 (27%) hospitals in Maryland participated in the intervention. The baseline SIR for all Maryland hospitals was 0.92, and the post-SPARC SIR was 0.67. The SPARC hospitals had a greater reduction in hospital-onset C. difficile incidence; 8.6 and 4.3 events per 10,000 patient days for baseline and most recent quarter, respectively. For non-SPARC hospitals, these hospital-onset C. difficile incidences were 5.1 preintervention and 4.3 postintervention. We found a statistically significant difference-in-difference between SPARC and non-SPARC hospital C. difficile reduction rates (ratio of IRR, 0.63; 95% CI, 0.44−0.89; P = .01). Conclusions: The Maryland SPARC collaborative, a public health-academic partnership, was associated with a 25% reduction in the Maryland C. difficile SIR. Hospitals participating in SPARC demonstrated significantly reduced C. difficile incidences to match that of high-performing hospitals in Maryland.
Clinical trial participation among US Hispanics remains low, despite a significant effort by research institutions nationwide. ResearchMatch, a national online platform, has matched 113,372 individuals interested in participating in research with studies conducted by 8778 researchers. To increase accessibility to Spanish speakers, we translated the ResearchMatch platform into Spanish by implementing tenets of health literacy and respecting linguistic and cultural diversity across the US Hispanic population. We describe this multiphase process, preliminary results, and lessons learned.
Translation of the ResearchMatch site consisted of several activities including: (1) improving the English language site’s reading level, removing jargon, and using plain language; (2) obtaining a professional Spanish translation of the site and incorporating iterative revisions by a panel of bilingual community members from diverse Hispanic backgrounds; (3) technical development and launch; and (4) initial promotion.
The Spanish language version was launched in August 2018, after 11 months of development. Community input improved the initial translation, and early registration and use by researchers demonstrate the utility of Spanish ResearchMatch in engaging Hispanics. Over 12,500 volunteers in ResearchMatch self-identify as Hispanic (8.5%). From August 2018 to March 2020, 162 volunteers registered through the Spanish language version of ResearchMatch, and over 500 new and existing volunteers have registered a preference to receive messages about studies in Spanish.
By applying the principles of health literacy and cultural competence, we developed a Spanish language translation of ResearchMatch. Our multiphase approach to translation included key principles of community engagement that should prove informative to other multilingual web-based platforms.
Lack of participation in clinical trials (CTs) is a major barrier for the evaluation of new pharmaceuticals and devices. Here we report the results of the analysis of a dataset from ResearchMatch, an online clinical registry, using supervised machine learning approaches and a deep learning approach to discover characteristics of individuals more likely to show an interest in participating in CTs.
We trained six supervised machine learning classifiers (Logistic Regression (LR), Decision Tree (DT), Gaussian Naïve Bayes (GNB), K-Nearest Neighbor Classifier (KNC), Adaboost Classifier (ABC) and a Random Forest Classifier (RFC)), as well as a deep learning method, Convolutional Neural Network (CNN), using a dataset of 841,377 instances and 20 features, including demographic data, geographic constraints, medical conditions and ResearchMatch visit history. Our outcome variable consisted of responses showing specific participant interest when presented with specific clinical trial opportunity invitations (‘yes’ or ‘no’). Furthermore, we created four subsets from this dataset based on top self-reported medical conditions and gender, which were separately analysed.
The deep learning model outperformed the machine learning classifiers, achieving an area under the curve (AUC) of 0.8105.
The results show sufficient evidence that there are meaningful correlations amongst predictor variables and outcome variable in the datasets analysed using the supervised machine learning classifiers. These approaches show promise in identifying individuals who may be more likely to participate when offered an opportunity for a clinical trial.
Perioperative medicine describes the practice of patient-centred, multidisciplinary, and integrated medical care of patients from the moment of contemplation of surgery until full recovery (Grocott & Mythen, 2015). This encompasses the three stages of surgical care: preoperative, intraoperative, and postoperative.
This definition covers a wide range of patients with many different conditions, ranging from a low-risk, young, healthy person undergoing minor surgery in an ambulatory care setting to a high-risk older person with multiple co-morbidities undergoing major and complex surgery.
A classic example of microbiome function is its role in nutrient assimilation in both plants and animals, but other less obvious roles are becoming more apparent, particularly in terms of driving infectious and non-infectious disease outcomes and influencing host behaviour. However, numerous biotic and abiotic factors influence the composition of these communities, and host microbiomes can be susceptible to environmental change. How microbial communities will be altered by, and mitigate, the rapid environmental change we can expect in the next few decades remain to be seen. That said, given the enormous range of functional diversity conferred by microbes, there is currently something of a revolution in microbial bioengineering and biotechnology in order to address real-world problems including human and wildlife disease and crop and biofuel production. All of these concepts are explored in further detail throughout the book.
This is the second volume of a series of mainly expository articles on the arithmetic theory of automorphic forms. It forms a sequel to On the Stabilization of the Trace Formula published in 2011. The books are intended primarily for two groups of readers: those interested in the structure of automorphic forms on reductive groups over number fields, and specifically in qualitative information on multiplicities of automorphic representations; and those interested in the classification of I-adic representations of Galois groups of number fields. Langlands' conjectures elaborate on the notion that these two problems overlap considerably. These volumes present convincing evidence supporting this, clearly and succinctly enough that readers can pass with minimal effort between the two points of view. Over a decade's worth of progress toward the stabilization of the Arthur-Selberg trace formula, culminating in Ngo Bau Chau's proof of the Fundamental Lemma, makes this series timely.
Stunting increases a child's susceptibility to diseases, increases mortality, and is associated over long term with reduced cognitive abilities, educational achievement, and productivity. We aimed to assess the most effective public health nutritional intervention to reduce stunting in Myanmar.
We searched the literature and developed a conceptual framework for interventions known to reduce stunting. We focused on the highest impact and most feasible interventions to reduce stunting in Myanmar, described policies to implement them, and compared their costs and projected effect on stunting using data-based decision trees. We estimated costs from the government perspective and calculated total projected cases of stunting prevented and cost per case prevented (cost-effectiveness). All interventions were compared to projected cases of stunting resulting from the current situation (e.g., no additional interventions).
Three new policy options were identified. Operational feasibility for all three options ranged from medium to high. Compared to the current situation, two were similarly cost-effective, at an additional USD 598 and USD 667 per case of stunting averted. The third option was much less cost-effective, at an additional USD 27,741 per case averted. However, if donor agencies were to expand their support in option three to the entire country, the prevalence of 22.5 percent would be reached by 2025 at an additional USD 667 per case averted.
A policy option involving immediate expansion of the current implementation of proven nutrition-specific interventions is feasible. It would have the highest impact on stunting and would approach the WHO 2025 target.
This paper completes the construction of
-functions for unitary groups. More precisely, in Harris, Li and Skinner [‘
-functions for unitary Shimura varieties. I. Construction of the Eisenstein measure’, Doc. Math.Extra Vol. (2006), 393–464 (electronic)], three of the authors proposed an approach to constructing such
-functions (Part I). Building on more recent results, including the first named author’s construction of Eisenstein measures and
-adic differential operators [Eischen, ‘A
-adic Eisenstein measure for unitary groups’, J. Reine Angew. Math.699 (2015), 111–142; ‘
-adic differential operators on automorphic forms on unitary groups’, Ann. Inst. Fourier (Grenoble)62(1) (2012), 177–243], Part II of the present paper provides the calculations of local
-integrals occurring in the Euler product (including at
). Part III of the present paper develops the formalism needed to pair Eisenstein measures with Hida families in the setting of the doubling method.
The adventures of Sherlock Holmes and John Watson begin at the end of Watson's personal mobility. He has ‘gravitated to London, that great cesspool into which all the loungers and idlers of the Empire are irresistibly drained’, with his health, and his career as a colonial medic, ‘irretrievably ruined’ (Doyle 2006: 14). Watson, curious about his new flatmate's profession, makes a list of his new friend's unique specializations and areas of ignorance – Holmes possesses a precise knowledge of London and the surrounding suburbs and an encyclopaedic catalogue of crime and chemistry, but knows little else (34). Holmes's unconventional occupation is revealed not in some dramatic conversation about a crime, but through his particular beliefs about the brain's ability to store a finite amount of information, like an ‘attic’ belonging to a ‘workman’ (32). Sherlock Holmes, with his carefully stocked ‘brain attic’, is a domestic detective and so his skills are described in domestic terms. The ‘attic’ is immobile; his skills are limited and specialized; and his knowledge of London's geography is not transferrable to another locale. He is so narrowly specialized that we (and even Watson) might say he is provincial.
The irony in calling Sherlock Holmes provincial is that his province, his region or specialty, is London as the Victorian imperial centre. Holmes is an ideal late-Victorian scientist taken to a distinctly un-Victorian extreme of specificity. And yet, this strange, provincial character is central both in imperial space, as London's superdetective, and in the international genre of detective fiction writ large, as a prototype of ‘the great consulting detective’. Holmes's empire over the genre is wide but the character’s abilities as a detective are decidedly narrow.
There is a parallel relationship between how a great detective's skills are described and how the space they inhabit relates to imperial-cultural centres. A Holmes-like detective whose investigative space includes a different type of space or place might choose a different metaphor than ‘brain attic’ to describe their investigative toolkit, as their relationship to their space is different. Adapting a genre's conventions or tropes to local conditions and conventions is a well-studied phenomenon. What is not often discussed, and what is revealed by these subtle changes to Holmes-like detectives, is the politics inherent in this practice.