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Deep Learning-based Modelling of Complex Hypertensive Multi-Organ Damage with Uncertainty Quantification from Simple Clinical Measures
Hypertension is a leading risk factor for a number of diseases and can cause severe damage to the vital organs such as the brain and heart. However, the level of hypertension itself does not necessarily reflect the full extent of underlying end-organ changes, which may hinder the development of effective treatment strategies. While recent research has demonstrated that these end-organ changes can be measured with deep phenotyping, its clinical translation may not be feasible. In this study, we propose a state-of-art deep learning approach that can quantify multi-organ (e.g., heart, brain, vasculature) phenotypical changes due to persistent hypertension from simple and popular clinical measures such as electrocardiogram (ECG), routinely acquired clinical data (age, BMI, diastolic and systolic blood pressures), and cardiac short axis (SAX) images from the UK Biobank, one of the largest open-access biomedical databases. Our proposed approach captures the intricate patterns of hypertensive disease state without resorting to the complex measures, which is hard to obtain in practical settings. It generates a numeric score between 0 and 1 of multi-organ damage, as well as provides an estimate of the overall uncertainty. The performance of our models is evaluated in different experimental settings and compared against the reference model. The results consistently demonstrate that the proposed approach can effectively model the multi-organ phenotypical changes from simple clinical measures with high performance (best-performing model MAE=0.108, MSE=0.019, variance=0.0005), and underscores its feasibility for potential clinical use.
Self-monitoring blood pressure in pregnancy: evaluation of women's experiences of the BUMP trials.
BACKGROUND: The COVID-19 pandemic accelerated the adoption of remote care, or telemedicine, in many clinical areas including maternity care. One component of remote care, the use of self-monitoring of blood pressure in pregnancy, could form a key component in post-pandemic care pathways. The BUMP trials evaluated a self-monitoring of blood pressure intervention in addition to usual care, testing whether it improved detection or control of hypertension for pregnant people at risk of hypertension or with hypertension during pregnancy. This paper reports the qualitative evaluation which aimed to understand how the intervention worked, the perspectives of participants in the trials, and, crucially, those who declined to participate. METHODS: The BUMP trials were conducted between November 2018 and May 2020. Thirty-nine in-depth qualitative interviews were carried out with a diverse sample of pregnant women invited to participate in the BUMP trials across five maternity units in England. RESULTS: Self-monitoring of blood pressure in the BUMP trials was reassuring, acceptable, and convenient and sometimes alerted women to raised BP. While empowering, taking a series of self-monitored readings also introduced uncertainty and new responsibility. Some declined to participate due to a range of concerns. In the intervention arm, the performance of the BUMP intervention may have been impacted by women's selective or delayed reporting of raised readings and repeated testing in pursuit of normal BP readings. In the usual care arm, more women were already self-monitoring their blood pressure than expected. CONCLUSIONS: The BUMP trials did not find that among pregnant individuals at higher risk of preeclampsia, blood pressure self-monitoring with telemonitoring led to significantly earlier clinic-based detection of hypertension nor improved management of blood pressure. The findings from this study help us understand the role that self-monitoring of blood pressure can play in maternity care pathways. As maternity services consider the balance between face-to-face and remote consultations in the aftermath of the COVID-19 pandemic, these findings contribute to the evidence base needed to identify optimal, effective, and equitable approaches to self-monitoring of blood pressure.
Strategies to improve the implementation of preventive care in primary care: a systematic review and meta-analysis.
BACKGROUND: Action on smoking, obesity, excess alcohol, and physical inactivity in primary care is effective and cost-effective, but implementation is low. The aim was to examine the effectiveness of strategies to increase the implementation of preventive healthcare in primary care. METHODS: CINAHL, CENTRAL, The Cochrane Database of Systematic Reviews, Dissertations & Theses - Global, Embase, Europe PMC, MEDLINE and PsycINFO were searched from inception through 5 October 2023 with no date of publication or language limits. Randomised trials, non-randomised trials, controlled before-after studies and interrupted time series studies comparing implementation strategies (team changes; changes to the electronic patient registry; facilitated relay of information; continuous quality improvement; clinician education; clinical reminders; financial incentives or multicomponent interventions) to usual care were included. Two reviewers screened studies, extracted data, and assessed bias with an adapted Cochrane risk of bias tool for Effective Practice and Organisation of Care reviews. Meta-analysis was conducted with random-effects models. Narrative synthesis was conducted where meta-analysis was not possible. Outcome measures included process and behavioural outcomes at the closest point to 12 months for each implementation strategy. RESULTS: Eighty-five studies were included comprising of 4,210,946 participants from 3713 clusters in 71 cluster trials, 6748 participants in 5 randomised trials, 5,966,552 participants in 8 interrupted time series, and 176,061 participants in 1 controlled before after study. There was evidence that clinical reminders (OR 3.46; 95% CI 1.72-6.96; I2 = 89.4%), clinician education (OR 1.89; 95% CI 1.46-2.46; I2 = 80.6%), facilitated relay of information (OR 1.95, 95% CI 1.10-3.46, I2 = 88.2%), and multicomponent interventions (OR 3.10; 95% CI 1.60-5.99, I2 = 96.1%) increased processes of care. Multicomponent intervention results were robust to sensitivity analysis. There was no evidence that other implementation strategies affected processes of care or that any of the implementation strategies improved behavioural outcomes. No studies reported on interventions specifically designed for remote consultations. Limitations included high statistical heterogeneity and many studies did not account for clustering. CONCLUSIONS: Multicomponent interventions may be the most effective implementation strategy. There was no evidence that implementation interventions improved behavioural outcomes. TRIAL REGISTRATION: PROSPERO CRD42022350912.
MAIT cells protect against sterile lung injury.
Mucosal-associated invariant T (MAIT) cells, the most abundant unconventional T cells in the lung, can exhibit a wide range of functional responses to different triggers via their T cell receptor (TCR) and/or cytokines. Their role, especially in sterile lung injury, is unknown. Using single-cell RNA sequencing (scRNA-seq), spectral analysis, and adoptive transfer in a bleomycin-induced sterile lung injury, we found that bleomycin activates murine pulmonary MAIT cells and is associated with a protective role against bleomycin-induced lung injury. MAIT cells drive the accumulation of type 1 conventional dendritic cells (cDC1s), limiting tissue damage in a DNGR-1-dependent manner. Human scRNA-seq data revealed that MAIT cells were activated, with increased cDC populations in idiopathic pulmonary fibrosis patients. Thus, MAIT cells enhance defense against sterile lung injury by fostering cDC1-driven anti-fibrotic pathways.
An analysis of controlled human infection studies registered on ClinicalTrials.gov.
OBJECTIVES: Controlled human infection studies (CHIS) involve intentional exposure of human volunteers to infectious agents. A previous systematic review found that adverse event (AE) reporting across CHIS is inconsistent, which makes data aggregation and reuse difficult. We hypothesised that data may be more easily aggregated using a clinical trial registry such as ClinicalTrals.gov, the largest publicly accessible registry of clinical trial data. The objectives of the current analysis were to (1) evaluate the use of ClinicalTrials.gov for CHIS data reporting and (2) compare CHIS clinical trial participant flow and AE reporting in ClinicalTrials.gov with the same data in corresponding published articles. DESIGN: ClinicalTrials.gov records that described a CHIS were included and data were accessed using the Aggregated Analysis of ClinicalTrials.gov application programming interface. These data were compared with results extracted from publications associated with included records' NCT identifiers and compared in groups stratified by sponsor type, cohort size and risk of bias. Results were considered discrepant if the same number was reported unambiguously differently in the clinical trial record and its associated publications. The frequencies of these discrepancies were used to quantify the differences between reporting in ClinicalTrials.gov records and publications of the same results. RESULTS: We screened 5131 ClinicalTrials.gov records for inclusion, reviewed 410 records in full and included 344 records. The overall prevalence of any discrepancy was 40%. Compared with their respective groups, significant discrepancies were observed in publicly funded trials, trials in the third quartile of study size and trials with a high risk of bias in selection of the reported result. Five studies reported a total of five serious AEs in ClinicalTrials.gov records but not in any associated publications. CONCLUSION: We identified an overall prevalence of discrepancy of 40% in CHIS, which is comparable with the prevalence observed in other types of clinical trials. In general, medium-sized, publicly funded trials tended to have more discrepancies in reporting, which may reflect the resources typically available to large, privately funded trials or the relative ease of reporting in smaller trials with fewer overall AEs. These results highlight the need to facilitate clear and consistent reporting in CHIS. PROSPERO REGISTRATION NUMBER: CRD42022330047.
Stop antibiotics when you feel better? Opportunities, challenges and research directions.
Shortening standard antibiotic courses and stopping antibiotics when patients feel better are two ways to reduce exposure to antibiotics in the community, and decrease the risks of antimicrobial resistance and antibiotic side effects. While evidence shows that shorter antibiotic treatments are non-inferior to longer ones for infections that benefit from antibiotics, shorter courses still represent average treatment durations that might be suboptimal for some. In contrast, stopping antibiotics based on improvement or resolution of symptoms might help personalize antibiotic treatment to individual patients and help reduce unnecessary exposure. Yet, many challenges need addressing before we can consider this approach evidence-based and implement it in practice. In this viewpoint article, we set out the main evidence gaps and avenues for future research.
Cognitive and psychiatric symptom trajectories 2-3 years after hospital admission for COVID-19: a longitudinal, prospective cohort study in the UK.
BACKGROUND: COVID-19 is known to be associated with increased risks of cognitive and psychiatric outcomes after the acute phase of disease. We aimed to assess whether these symptoms can emerge or persist more than 1 year after hospitalisation for COVID-19, to identify which early aspects of COVID-19 illness predict longer-term symptoms, and to establish how these symptoms relate to occupational functioning. METHODS: The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study of adults (aged ≥18 years) who were hospitalised with a clinical diagnosis of COVID-19 at participating National Health Service hospitals across the UK. In the C-Fog study, a subset of PHOSP-COVID participants who consented to be recontacted for other research were invited to complete a computerised cognitive assessment and clinical scales between 2 years and 3 years after hospital admission. Participants completed eight cognitive tasks, covering eight cognitive domains, from the Cognitron battery, in addition to the 9-item Patient Health Questionnaire for depression, the Generalised Anxiety Disorder 7-item scale, the Functional Assessment of Chronic Illness Therapy Fatigue Scale, and the 20-item Cognitive Change Index (CCI-20) questionnaire to assess subjective cognitive decline. We evaluated how the absolute risks of symptoms evolved between follow-ups at 6 months, 12 months, and 2-3 years, and whether symptoms at 2-3 years were predicted by earlier aspects of COVID-19 illness. Participants completed an occupation change questionnaire to establish whether their occupation or working status had changed and, if so, why. We assessed which symptoms at 2-3 years were associated with occupation change. People with lived experience were involved in the study. FINDINGS: 2469 PHOSP-COVID participants were invited to participate in the C-Fog study, and 475 participants (191 [40·2%] females and 284 [59·8%] males; mean age 58·26 [SD 11·13] years) who were discharged from one of 83 hospitals provided data at the 2-3-year follow-up. Participants had worse cognitive scores than would be expected on the basis of their sociodemographic characteristics across all cognitive domains tested (average score 0·71 SD below the mean [IQR 0·16-1·04]; p<0·0001). Most participants reported at least mild depression (263 [74·5%] of 353), anxiety (189 [53·5%] of 353), fatigue (220 [62·3%] of 353), or subjective cognitive decline (184 [52·1%] of 353), and more than a fifth reported severe depression (79 [22·4%] of 353), fatigue (87 [24·6%] of 353), or subjective cognitive decline (88 [24·9%] of 353). Depression, anxiety, and fatigue were worse at 2-3 years than at 6 months or 12 months, with evidence of both worsening of existing symptoms and emergence of new symptoms. Symptoms at 2-3 years were not predicted by the severity of acute COVID-19 illness, but were strongly predicted by the degree of recovery at 6 months (explaining 35·0-48·8% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); by a biocognitive profile linking acutely raised D-dimer relative to C-reactive protein with subjective cognitive deficits at 6 months (explaining 7·0-17·2% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); and by anxiety, depression, fatigue, and subjective cognitive deficit at 6 months. Objective cognitive deficits at 2-3 years were not predicted by any of the factors tested, except for cognitive deficits at 6 months, explaining 10·6% of their variance. 95 of 353 participants (26·9% [95% CI 22·6-31·8]) reported occupational change, with poor health being the most common reason for this change. Occupation change was strongly and specifically associated with objective cognitive deficits (odds ratio [OR] 1·51 [95% CI 1·04-2·22] for every SD decrease in overall cognitive score) and subjective cognitive decline (OR 1·54 [1·21-1·98] for every point increase in CCI-20). INTERPRETATION: Psychiatric and cognitive symptoms appear to increase over the first 2-3 years post-hospitalisation due to both worsening of symptoms already present at 6 months and emergence of new symptoms. New symptoms occur mostly in people with other symptoms already present at 6 months. Early identification and management of symptoms might therefore be an effective strategy to prevent later onset of a complex syndrome. Occupation change is common and associated mainly with objective and subjective cognitive deficits. Interventions to promote cognitive recovery or to prevent cognitive decline are therefore needed to limit the functional and economic impacts of COVID-19. FUNDING: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Wolfson Foundation, MQ Mental Health Research, MRC-UK Research and Innovation, and National Institute for Health and Care Research.
Health impact and economic evaluation of expanded program on immunization in China from 1974 to 2024: a modelling study
Background: The Expanded Program on Immunization (EPI), initiated by the WHO in 1974, is a cornerstone of global public health. Today, China’s EPI covers over one-sixth of the world’s population and encompasses eight routine vaccines with high coverage rates. Methods: This study aimed to estimate health and economic impacts of China’s EPI against eight pathogens: measles, pertussis, hepatitis B, tuberculosis, hepatitis A, Japanese encephalitis, meningitis A, and poliomyelitis in 1974-2024. Health and economic outcomes were determined using mathematical models between a counterfactual scenario without vaccination and the current vaccination scenario, based on both calendar year and birth cohort approaches. Findings: We estimated that China’s EPI averted 703.02 million cases (95% credible interval: 699.51-722.80) and 2.48 million deaths (2.14-2.97) in 1974-2024 based on the calendar year approach, equivalent to a reduction of 160.22 million DALYs (145.05-196.99). Using the birth cohort approach, we predicted 707.41 million cases (703.93-727.03) and 7.01 million deaths (6.95-7.87) averted over the lifetime, resulting in a reduction of 279.02 million DALYs (265.78-316.12). From a societal perspective, the aggregated costs were USD 124.06 billion (120.49- 127.49), while the benefits amounted to USD 2417.85 billion (2359.38- 2710.35). China’s EPI yielded an aggregate benefit-cost ratio of 19.48 (18.82-22.08) from the societal perspective and 8.02 (7.64-8.80) from the provider’s perspective. Interpretation: China’s EPI has demonstrated remarkable health and economic achievements, contributing to worldwide EPI success over the past 50 years. Further investment in EPI is warranted to sustain coverage and expand vaccine inclusion in China and globally. Funding: Natural Science Foundation of Beijing Municipality.
General practice antibiotic prescriptions attributable to respiratory syncytial virus by age and antibiotic class: an ecological analysis of the English population.
BACKGROUND: Respiratory syncytial virus (RSV) may contribute to a substantial volume of antibiotic prescriptions in primary care. However, data on the type of antibiotics prescribed for such infections are only available for children <5 years in the UK. Understanding the contribution of RSV to antibiotic prescribing would facilitate predicting the impact of RSV preventative measures on antibiotic use and resistance. The objective of this study was to estimate the proportion of antibiotic prescriptions in English general practice attributable to RSV by age and antibiotic class. METHODS: Generalized additive models examined associations between weekly counts of general practice antibiotic prescriptions and laboratory-confirmed respiratory infections from 2015 to 2018, adjusting for temperature, practice holidays and remaining seasonal confounders. We used general practice records from the Clinical Practice Research Datalink and microbiology tests for RSV, influenza, rhinovirus, adenovirus, parainfluenza, human metapneumovirus, Mycoplasma pneumoniae and Streptococcus pneumoniae from England's Second Generation Surveillance System. RESULTS: An estimated 2.1% of antibiotics were attributable to RSV, equating to an average of 640 000 prescriptions annually. Of these, adults ≥75 years contributed to the greatest volume, with an annual average of 149 078 (95% credible interval: 93 733-206 045). Infants 6-23 months had the highest average annual rate at 6580 prescriptions per 100 000 individuals (95% credible interval: 4522-8651). Most RSV-attributable antibiotic prescriptions were penicillins, macrolides or tetracyclines. Adults ≥65 years had a wider range of antibiotic classes associated with RSV compared with younger age groups. CONCLUSIONS: Interventions to reduce the burden of RSV, particularly in older adults, could complement current strategies to reduce antibiotic use in England.
A pilot protocol for surveillance of infection and antibiotic prescribing in primary healthcare across the globe: Antibiotic Prescribing in Primary Healthcare Point Prevalence Survey (APC-PPS)
Little data is available from the primary healthcare setting in low- and middle-income countries to describe the burden of clinical infections and antibiotic prescribing proportions for those infections. The AWaRe Antibiotic Book provides a framework for assessing antibiotic prescribing in primary healthcare but requires understanding both frequency of clinical infections and their antibiotic prescribing proportions. The Antibiotic Prescribing in Primary Healthcare Point Prevalence Survey (APC-PPS) project is a series of point prevalence surveys conducted at primary healthcare facilities in LMICs to capture the frequency of consultation for different clinical infections and diagnoses and the frequency and type of antibiotic prescribing associated with these infections in primary healthcare facilities. This study aims to assess the feasibility of using a PPS methodology to collect data on clinical presentation and antibiotic prescribing in primary healthcare settings. The data collected are necessary to be able to summarise relative rates of presentation of different clinical infections and antibiotic prescribing practices to inform global estimates of antibiotic use and inform the development of surveillance methods and representative sampling frames. Each site will conduct 6-8 point prevalence surveys over the course of 12 months. Completely anonymous data on age, sex, relevant comorbidities, infection symptoms and diagnoses and antibiotic prescription are collected for patients of all ages with acute infection symptoms (up to 14 days of symptoms) who present to the facility on the day of the survey. No identifiable data will be collected from individuals. Data is collected via ODK Collect and stored in a secure ODK Cloud server hosted by City St. George’s, University of London. Sites will be active between early 2023- end 2024, with regular interim data analysis scheduled and final data analysis planned by mid 2025. All required local and national ethical and regulatory approvals will be obtained prior to sites starting.
Umbrella review of economic evaluations of interventions for the prevention and management of healthcare-associated infections in adult hospital patients.
INTRODUCTION: Healthcare-associated infections result in worse outcomes for patients and greater financial burden. An estimated 4.8 million HCAIs occurred in hospitals across Europe in 2022-23. Sixty-four percent of antibiotic-resistant infections in Europe are associated with healthcare. It is therefore vital to identify cost-effective interventions. Our objective was to summarise the cost-effectiveness evidence of interventions addressing HCAIs in hospitals. METHODS: An umbrella review was conducted to identify evidence on the cost-effectiveness of antimicrobial stewardship, infection prevention and control, and microbiology and diagnostic stewardship interventions for the prevention and clinical management of HCAIs in adult hospital patients. Medline, Embase and EconLit databases were searched. A qualitative synthesis was undertaken. RESULTS: Twenty-four systematic reviews met the inclusion criteria, with 101 separate analyses extracted and grouped into 10 intervention and 14 infection/organism categories, across various countries and settings. Most evidence focussed on screening followed by contact precautions, isolation and/or decolonisation, with selective screening most cost-effective. Most IPC bundles were cost-effective, although interventions were heterogeneous. The evidence base was sparse for the remaining intervention categories, with more research required. The limited evidence suggests standalone environmental cleaning, hand hygiene, diagnostics, surveillance, ABS, and decolonisation interventions were mostly cost-effective. The cost-effectiveness of standalone personal protective equipment, and education and training interventions was mixed. Most interventions focussed on methicillin-resistant Staphylococcus aureus and other Gram-positive infections, with more research needed on Gram-negative infections. The comparator was unclear in many extracted analyses. CONCLUSIONS: Cost-effective interventions to address HCAIs in hospitals exist, although more evidence is needed for most interventions.
Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.
One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.
Clinical metagenomics: ethical issues
Metagenomics is increasingly used for diagnosis in hospital settings. It is useful particularly in cases of unknown aetiology, where novel or difficult-to-diagnose pathogens are suspected, and/or following unexplained disease outbreaks. In this paper, we present three use cases that draw on existing reports: one involving a patient in intensive care with encephalitis of unknown aetiology; a second case with likely infection with drug-resistant Klebsiella pneumoniae and an incidental finding of unknown relevance; and a third case situated in an unexplained outbreak of acute hepatitis in children, with severe outcomes due to co-infection. We examine each case in turn, highlighting ethical questions arising in relation to clinical issues including: disclosure to patients of untreatable disease, cost-effectiveness, the value of resistance testing, sensitivity and specificity, uncertain or unexpected findings, patient consent and data sharing. We conclude by proposing recommendations for further research and developing particular pieces of guidance to improve clinical uses of metagenomics for diagnosis.
29 International collaboration to advance research preparedness and response
Pandemic preparedness and research response bring together multiple disciplines and organizations to coordinate action across geographical and specialty boundaries. At their best, these international collaborations provide rapid, robust answers to key scientific questions. But several recent pandemics, notably coronavirus disease 2019 (COVID-19), have revealed less than ideal levels of international collaboration. This chapter discusses factors that limit collaboration and some of the risks of a global research response ecosystem prone to delay and error. Using several case studies as examples, this chapter proposes measures to better prepare and implement international collaborations in future outbreaks, including the strategic allocation of funding to support well-designed, expedited clinical research to answer key clinical and public health questions.
Synthesis of bicyclo[3.1.1]heptanes, meta-substituted arene isosteres, from [3.1.1]propellane.
The use of saturated small-ring bridged hydrocarbons as bioisosteres for aromatic rings has become a popular tactic in drug discovery. Perhaps the best known of such hydrocarbons is bicyclo[1.1.1]pentane, for which the angle between the exit vectors of the bridgehead substituents is identical to that of a para-substituted arene (180°). The development of meta-arene (bio)isosteres is much less explored due to the challenge of identifying an accurate geometric mimic (substituent exit vector angle ~120°, dihedral angle ~0°). To address this, we recently reported straightforward access to bicyclo[3.1.1]heptanes (BCHeps), which exactly meet these geometric properties, via radical ring-opening reactions of [3.1.1]propellane. This required the development of a scalable synthesis of [3.1.1]propellane, as well as the implementation of various ring-opening reactions and derivatizations. Here we describe methodology for a multigram scale synthesis of [3.1.1]propellane in five steps from commercially available ethyl 4-chlorobutanoate, which proceeds in an overall yield of 26-37%. We also describe the functionalization of [3.1.1]propellane to three key classes of BCHep iodides by photocatalyzed-atom transfer radical addition reactions using 456 nm blue light. We further report protocols for the elaboration of these products to other useful derivatives, via iron-catalyzed Kumada coupling with aryl Grignard reagents and conversion of a pivalate ester to a carboxylic acid through hydrolysis/oxidation. The total times required to synthesize [3.1.1]propellane, the BCHep iodides and the BCHep carboxylic acid are ~53, 6-8 and 40 h, respectively, requiring an average level of synthetic chemistry expertise (for example, masters and/or graduate students).
Protocol for the process evaluation for a cluster randomised controlled trial evaluating primary school-based screening and intervention delivery for childhood anxiety problems.
INTRODUCTION: Anxiety problems are prevalent in childhood and, without intervention, can persist into adulthood. Effective evidence-based interventions for childhood anxiety disorders exist, specifically cognitive-behavioural therapy (CBT) in a range of formats. However, only a small proportion of children successfully access and receive treatment. Conducting mental health screening in schools and integrating evidence-based interventions for childhood anxiety problems may be an effective way to ensure support reaches children in need. The Identifying Child Anxiety Through Schools-Identification to Intervention (iCATS i2i) trial involves screening for childhood anxiety problems and offering a brief online parent-led CBT intervention. This paper presents the protocol for the process evaluation of the iCATS i2i trial, which aims to examine the implementation and acceptability of the study procedures, the mechanisms of change and whether any external factors had an impact on procedure engagement or delivery. METHODS AND ANALYSIS: This process evaluation will use both quantitative and qualitative methods to evaluate the implementation and acceptability of and barriers/facilitators to engagement and delivery of the iCATS screening/intervention procedures. Quantitative data sources will include opt-out and completion rates of baseline measures and usage analytics extracted from the online intervention platform. Qualitative interviews will be conducted with children, parents, school staff, iCATS i2i clinicians and researchers delivering study procedures. The Medical Research Council framework for process evaluations will guide study design and analysis. ETHICS AND DISSEMINATION: This study has received ethical approval from the University of Oxford Research Ethics Committee (R66068_RE003). Findings from the study will be disseminated via peer-reviewed publications in academic journals, conferences, digital and social media platforms and stakeholder meetings. TRIAL REGISTRATION: ISRCTN76119074.