Childhood-onset type 1 diabetes and subsequent adult psychiatric disorders: a nationwide cohort and genome-wide Mendelian randomization study.

Childhood-onset type 1 diabetes (T1D) is associated with substantial psychiatric morbidity in later life, but it remains unknown whether these associations are due to common underlying biological mechanisms or the impacts of living with the condition and its treatment. Here, using Czech national register data, we identified children with T1D aged ≤14 years between 1994 and 2007 and estimated the risk of psychiatric disorders up to 24 years later. We found that children diagnosed with T1D had an elevated risk of developing substance use, mood, anxiety and personality disorders, and behavioral syndromes. Conversely, we found that children with T1D had a lower risk of developing psychotic disorders. In Mendelian randomization analysis, we found an association with schizophrenia, which, however, did not persist following multiple testing adjustment. The combined observational and Mendelian randomization evidence suggests that T1D diagnosis in childhood predisposes to far-reaching, extensive psychiatric morbidity, which is unlikely to be explicable by common underlying biological mechanisms. The findings of this study highlight that monitoring and addressing the mental health needs of children with T1D is imperative, whereas glucose dysregulation and/or inflammation implicated in schizophrenia pathogenesis warrants future research.

Adjusting for incomplete baseline covariates in randomized controlled trials: a cross-world imputation framework.

In randomized controlled trials, adjusting for baseline covariates is commonly used to improve the precision of treatment effect estimation. However, covariates often have missing values. Recently, Zhao and Ding studied two simple strategies, the single imputation method and missingness-indicator method (MIM), to handle missing covariates and showed that both methods can provide an efficiency gain compared to not adjusting for covariates. To better understand and compare these two strategies, we propose and investigate a novel theoretical imputation framework termed cross-world imputation (CWI). This framework includes both single imputation and MIM as special cases, facilitating the comparison of their efficiency. Through the lens of CWI, we show that MIM implicitly searches for the optimal CWI values and thus achieves optimal efficiency. We also derive conditions under which the single imputation method, by searching for the optimal single imputation values, can achieve the same efficiency as the MIM. We illustrate our findings through simulation studies and a real data analysis based on the Childhood Adenotonsillectomy Trial. We conclude by discussing the practical implications of our findings.

Data-Driven Implementation Strategy to Optimise Clinician Behaviour Change at Scale in Complex Clinical Environments: A Multicentre Emergency Care Study.

AIM: To develop an evidence-driven, behaviour change focused strategy to maximise implementation and uptake of HIRAID (History including Infection risk, Red flags, Assessment, Interventions, Diagnostics, communication and reassessment) in 30 Australian rural, regional and metropolitan emergency departments. DESIGN: An embedded, mixed-methods study. METHODS: This study is the first phase of a step-wedge cluster randomised control trial of HIRAID involving over 1300 emergency nurses. Concurrent quantitative and qualitative data were collected via an electronic survey sent to all nurses to identify preliminary barriers and enablers to HIRAID implementation. The survey was informed by the Theoretical Domains Framework, which is a synthesis of behavioural change theories that applies the science of intervention implementation in health care to effect change. Quantitative data were analysed using descriptive statistics and qualitative data with inductive content analysis. Data were then integrated to generate barriers and enablers to HIRAID implementation which were mapped to the Theoretical Domains Framework. Corresponding intervention functions and Behaviour Change techniques were selected and an overarching implementation strategy was developed through stakeholder consultation and application of the APEASE criteria (Affordability, Practicability, Effectiveness and cost-effectiveness, Acceptability, Side-effects/safety and Equity). RESULTS: Six barriers to HIRAID implementation were identified by 670 respondents (response rate ~58%) representing all 30 sites: (i) lack of knowledge about HIRAID; (ii) high workload, (iii) lack of belief anything would change; (iv) not suitable for workplace; (v), uncertainty about what to do and (vi) lack of support or time for education. The three enablers were as follows: (i) willingness to learn and adopt something new; (ii) recognition of the need for something new and (iii) wanting to do what is best for patient care. The 10 corresponding domains were mapped to seven intervention functions, 21 behaviour change techniques and 45 mechanisms. The major components of the implementation strategy were a scaffolded education programme, clinical support and environmental modifications. CONCLUSIONS: A systematic process guided by the behaviour change wheel resulted in the generation of a multifaceted implementation strategy to implement HIRAID across rural, regional and metropolitan emergency departments. Implementation fidelity, reach and impact now require evaluation. IMPACT: HIRAID emergency nursing assessment framework reduced clinical deterioration relating to emergency care and improved self-confidence and documentation in emergency departments in pilot studies. Successful implementation of any intervention in the emergency department is notoriously difficult due to workload unpredictability, the undifferentiated nature of patients and high staff turnover. Key barriers and enablers were identified, and a successful implementation strategy was developed. This study uses theoretical frameworks to identify barriers and enablers to develop a data-driven, behavioural-focused implementation strategy to optimise the uptake of HIRAID in geographically diverse emergency departments which can be used to inform future implementation efforts involving emergency nurses. REPORTING METHOD: The CROSS reporting method (Supporting Information S3) was used to adhere to EQUATOR guidelines. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution. TRIAL REGISTRATION: Australian New Zealand; Clinical Trials Registry (ANZCTR) number: ACTRN12621001456842, registered 25/10/2021.

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation.

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next-generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ~10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease and healthy brain ageing based on ~4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 µm isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.

Efficacy of the Dapivirine Vaginal Ring Accounting for Imperfect Adherence.

Product adherence is critical to obtaining objective estimates of efficacy of pre-exposure prophylactic interventions against HIV-1 infection. With imperfect adherence, intention-to-treat analyses assess the collective effects of complete, sub-optimal and non-adherence, providing a biased and attenuated estimate of the average causal effect of an intervention. Using data from the MTN-020/ASPIRE phase III trial evaluating HIV-1 efficacy of the dapivirine vaginal ring, we conducted per-protocol, and adherence-adjusted causal inference analyses using principal stratification and marginal structural models. We constructed two adherence cut offs of ≥ 0.9 mg (low cutoff) and > 4.0 mg (high cutoff) that represent drug released from the ring over a 28-day period. The HIV-1 efficacy estimate (95% CI) was 30.8% (3.6%, 50.3%) (P = 0.03) from the per-protocol analysis, and 53.6% (16.5%, 74.3%) (P = 0.01) among the highest predicted adherers from principal stratification analyses using the low cutoff. Marginal structural models produced efficacy estimates (95% CIs) ranging from 48.8 (21.8, 66.4) (P = 0.0019) to 56.5% (32.8%, 71.9%) (P = 0.0002). Application of adherence-adjusted causal inference methods are useful in interpreting HIV-1 efficacy in secondary analyses of PrEP clinical trials.

Temperature-Dependent Structural and Optoelectronic Properties of the Layered Perovskite 2-Thiophenemethylammonium Lead Iodide.

Improved knowledge of the influence of temperature upon layered perovskites is essential to enable perovskite-based devices to operate over a broad temperature range and to elucidate the impact of structural changes upon the optoelectronic properties. We examined the Ruddlesden-Popper layered perovskite 2-thiophenemethylammonium lead iodide (ThMA2PbI4) and observed a structural phase transition between a high- and a low-temperature phase at 220 K using temperature-dependent X-ray diffraction, UV-visible absorption, and photoluminescence (PL) spectroscopy. The structural phase transition altered the tilt pattern of the inorganic octahedra layer, modifying the absorption and PL spectra. Further, we found a narrow and intense additional PL peak in the low-temperature phase, which we assigned to radiative emission from a defect-bound exciton state. In both phases we determined the thermal expansion coefficient and found values similar to those of cubic 3D perovskites, i.e., larger than those of typical substrates such as glass. These results demonstrate that the organic spacer plays a critical role in controlling the temperature-dependent structural and optoelectronic properties of layered perovskites and suggests more widely that strain management strategies may be needed to fully utilize layered perovskites in device applications.

The Impact of Stigma and Sexual Identity on PrEP Awareness and Use Among At-Risk Men Who Have Sex With Men in Four U.S. Cities (HPTN 078).

Persistent pre-exposure prophylaxis (PrEP) use reduces the risk of HIV infection, yet uptake lags among those with the greatest need. Sexual identity stigma may be a significant barrier to PrEP awareness and use among high-risk communities. The primary aim of this study was to determine whether sexual identity was related to PrEP awareness and use. This multi-site HIV Prevention Trials Network (HPTN) study (HPTN 078) focuses on men who have sex with men (MSM) (n=335) who were HIV-negative at screening. The majority of participants were non-white (62.1%), younger than 35 (57.9%), single (79.1%), and aware of PrEP, yet had never taken PrEP (52.5%). Participants completed questionnaires including sexual history and identity; lesbian, gay, bisexual, transgender, queer (LGBTQ) community engagement; PrEP awareness and use; and several measures of sexual identity stigma including family and friend stigma, general societal stigma, and anticipated healthcare stigma. Univariate and multinomial logistic regression models helped to determine factors associated with PrEP awareness and use. There were stark disparities in PrEP awareness comparing Black and White participants; 50% of Black participants reported being PrEP unaware vs 11.8% of White participants. In this sample, gay sexual identity (compared to bisexual identity) was associated with increased PrEP awareness (AOR 6.66) and use (AOR 16.9). Additionally, 29% of the association between sexual orientation and PrEP use was mediated through internalized stigma. Given low PrEP uptake among MSM, interventions that address sexual identity stigma may motivate greater PrEP uptake.

Age-related differences in how the shape of alpha and beta oscillations change during reaction time tasks.

While the shape of cortical oscillations is increasingly recognised to be physiologically and functionally informative, its relevance to the aging motor system has not been established. We therefore examined the shape of alpha and beta band oscillations recorded at rest, as well as during performance of simple and go/no-go reaction time tasks, in 33 young (23.3 ± 2.9 years, 27 females) and 27 older (60.0 ± 5.2 years, 23 females) adults. The shape of individual oscillatory cycles was characterised using a recently developed pipeline involving empirical mode decomposition, before being decomposed into waveform motifs using principal component analysis. This revealed four principal components that were uniquely influenced by task and/or age. These described specific dimensions of shape and tended to be modulated during the reaction phase of each task. Our results suggest that although oscillation shape is task-dependent, the nature of this effect is altered by advancing age, possibly reflecting alterations in cortical activity. These outcomes demonstrate the utility of this approach for understanding the neurophysiological effects of ageing.

Effectiveness of Using Additional HIV Self-Test Kits as an Incentive to Increase HIV Testing Within Assisted Partner Services.

BACKGROUND: Incentives have shown mixed results in increasing HIV testing rates in low-resource settings. We investigated the effectiveness of offering additional self-tests (HIVSTs) as an incentive to increase testing among partners receiving assisted partner services (APS). SETTING: Western Kenya. METHODS: We conducted a single-crossover study nested within a cluster-randomized controlled trial. Twenty-four facilities were randomized 1:1 to (1) control: provider-delivered testing or (2) intervention: offered 1 HIVST or provider-delivered testing for 6 months (pre-implementation), then switched to offering 2 HIVSTs for 6 months (post-implementation). A difference-in-differences approach using generalized linear mixed models, accounting for facility clustering and adjusting for age, sex, and income, was used to estimate the effect of the incentive on HIV testing and first-time testing among partners in APS. RESULTS: March 2021-June 2022, 1127 index clients received APS and named 8155 partners, among whom 2333 reported a prior HIV diagnosis and were excluded from analyses, resulting in 5822 remaining partners: 3646 (62.6%) and 2176 (37.4%) in the pre-implementation and post-implementation periods, respectively. Overall, 944/2176 partners (43%) were offered a second HIVST during post-preimplementation, of whom 34.3% picked up 2 kits, of whom 71.7% reported that the second kit encouraged HIV testing. Comparing partners offered 1 vs. two HIVSTs showed no difference in HIV testing (relative risk: 1.01, 95% confidence interval: 0.951 to 1.07) or HIV testing for the first time (relative risk: 1.23, 95% confidence interval: 0.671 to 2.24). CONCLUSIONS: Offering a second HIVST as an incentive within APS did not significantly impact HIV testing or first-time testing, although those opting for 2 kits reported it incentivized them to test.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights.

OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. MATERIALS AND METHODS: A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. RESULTS: 55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DISCUSSION: Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. CONCLUSION: Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Evolution of Material Properties and Residual Stress with Increasing Number of Passes in Aluminium Structure Printed via Additive Friction Stir Deposition.

Additive friction stir deposition (AFSD) is an emerging solid-state additive manufacturing process with a high deposition rate. Being a non-fusion additive manufacturing (AM) process, it significantly eliminates problems related to melting such as cracking or high residual stresses. Therefore, it is possible to process reactive materials or high-strength alloys with high susceptibility to cracking. Although the residual stresses are lower in this process than with the other AM processes, depending on the deposition path, geometry, and boundary conditions, residual stresses may lead to undesired deformations and deteriorate the dimensional accuracy. Thermal cycling during layer deposition, which also depends on the geometry of the manufactured component, is expected to affect mechanical properties. To this day, the influence of the deposit geometry on the residual stresses and mechanical properties is not well understood, which presents a barrier for industry uptake of this process for large-scale part manufacturing. In this study, a stepped structure with 4, 7, and 10 passes manufactured via AFSD is used to investigate changes in microstructure, residual stress, and mechanical property as a function of the number of passes. The microstructure and defects are assessed using scanning electron microscopy and electron backscatter diffraction. Hardness maps for each step are created. The residual stress distributions at the centreline of each step are acquired via non-destructive neutron diffraction. The valuable insights presented here are essential for the successful utilisation of AFSD in industrial applications.

Effectiveness of HIV self-testing when offered within assisted partner services in Western Kenya (APS-HIVST Study): a cluster randomized controlled trial.

INTRODUCTION: Assisted partner services (APS) is an effective strategy for increasing HIV testing, new diagnosis, and linkage to care among sexual partners of people living with HIV (PLWH). APS can be resource intensive as it requires community tracing to locate each partner named and offer them testing. There is limited evidence for the effectiveness of offering HIV self-testing (HIVST) as an option for partner testing within APS. METHODS: We conducted a cluster randomized controlled trial comparing provider-delivered HIV testing (Standard APS) versus offering partners the option of provider-delivered testing or HIVST (APS+HIVST) at 24 health facilities in Western Kenya. Facilities were randomized 1:1 and we conducted intent-to-treat analyses using Poisson generalized linear mixed models to estimate intervention impact on HIV testing, new HIV diagnoses, and linkage to care. All models accounted for clustering at the clinic level and new diagnoses and linkage models were adjusted for individual-level age, sex, and income a priori. RESULTS: From March to December 2021, 755 index clients received APS and named 5054 unique partners. Among these, 1408 partners reporting a prior HIV diagnosis were not eligible for HIV testing and were excluded from analyses. Of the remaining 3646 partners, 96.9% were successfully contacted for APS and tested for HIV: 2111 (97.9%) of 2157 in the APS+HIVST arm and 1422 (95.5%) of 1489 in the Standard APS arm. In the APS+HIVST arm, 84.6% (1785/2111) tested via HIVST and 15.4% (326/2111) received provider-delivered testing. Overall, 16.7% of the 3533 who tested were newly diagnosed with HIV (APS+HIVST = 357/2111 [16.9%]; Standard APS = 232/1422 [16.3%]). Of the 589 partners who were newly diagnosed, 90.7% were linked to care (APS+HIVST = 309/357 [86.6%]; Standard APS = 225/232 [97.0%]). There were no significant differences between the two arms in HIV testing (relative risk [RR]: 1.02, 95% CI: 0.96-1.10), new HIV diagnoses (adjusted RR [aRR]: 1.03, 95% CI: 0.76-1.39) or linkage to care (aRR: 0.88, 95% CI: 0.74-1.06). CONCLUSIONS: There were no differences between APS+HIVST and Standard APS, demonstrating that integrating HIVST into APS continues to be an effective strategy for identifying PLWH by successfully reaching and HIV testing >95% of elicited partners, newly diagnosing with HIV one in six of those tested, >90% of whom were linked to care. CLINICAL TRIAL NUMBER: NCT04774835.

Absenteeism and Health Behavior Trends Associated With Acute Respiratory Illness Before and During the COVID-19 Pandemic in a Community Household Cohort, King County, Washington.

Introduction: Longitudinal data on how acute respiratory illness (ARI) affects behavior, namely school or work participation, and nonpharmaceutical intervention (NPI) usage before and during the COVID-19 pandemic is limited. The authors assessed how ARIs and specific symptoms affected school, work, and health-related behaviors over time. Methods: From November 2019 to June 2021, participating households with children in King County, Washington, were remotely monitored for ARI symptoms weekly. Following ARIs, participants reported illness-related effects on school, work, and NPI use. Using logistic regression with generalized estimating equations, the authors examined associations between symptoms and behaviors. Results: Of 1,861 participants, 581 (31%) from 293 households reported 884 ARIs and completed one-week follow-up surveys. Compared with the prepandemic period, during the period of the pandemic pre-COVID-19 vaccine, ARI-related school (56% vs 10%, p<0.001) absenteeism decreased and masking increased (3% vs 28%, p<0.001). After vaccine authorization in December 2020, more ARIs resulted in masking (3% vs 48%, p<0.001), avoiding contact with non-household members (26% vs 58%, p<0.001), and staying home (37% vs 69%, p<0.001) compared with the prepandemic period. Constitutional symptoms such as fever were associated with work disruptions (OR=1.91; 95% CI=1.06, 3.43), staying home (OR=1.55; 95% CI=1.06, 2.27), and decreased contact with non-household members (OR=1.58; 95% CI=1.05, 2.36). Conclusions: This remote household study permitted uninterrupted tracking of behavioral changes in families with children before and during the COVID-19 pandemic, identifying increased use of some NPIs when ill but no additional illness-associated work or school disruptions.

Robust analysis of stepped wedge trials using composite likelihood models.

Stepped wedge trials (SWTs) are a type of cluster randomized trial that involve repeated measures on clusters and design-induced confounding between time and treatment. Although mixed models are commonly used to analyze SWTs, they are susceptible to misspecification particularly for cluster-longitudinal designs such as SWTs. Mixed model estimation leverages both "horizontal" or within-cluster information and "vertical" or between-cluster information. To use horizontal information in a mixed model, both the mean model and correlation structure must be correctly specified or accounted for, since time is confounded with treatment and measurements are likely correlated within clusters. Alternative non-parametric methods have been proposed that use only vertical information; these are more robust because between-cluster comparisons in a SWT preserve randomization, but these non-parametric methods are not very efficient. We propose a composite likelihood method that focuses on vertical information, but has the flexibility to recover efficiency by using additional horizontal information. We compare the properties and performance of various methods, using simulations based on COVID-19 data and a demonstration of application to the LIRE trial. We found that a vertical composite likelihood model that leverages baseline data is more robust than traditional methods, and more efficient than methods that use only vertical information. We hope that these results demonstrate the potential value of model-based vertical methods for SWTs with a large number of clusters, and that these new tools are useful to researchers who are concerned about misspecification of traditional models.

Lung Metastasectomy: Where Do We Stand? Results from an Italian Multicentric Prospective Database.

Background/Objectives: The surgical resection of pulmonary metastases is considered a therapeutic option in selected cases. In light of this, we present the results from a national multicenter prospective registry of lung metastasectomy. Methods: This retrospective analysis involves data collected prospectively and consecutively in a national multicentric Italian database, including patients who underwent lung metastasectomy. The primary endpoints were the analysis of morbidity and overall survival (OS), with secondary endpoints focusing on the analysis of potential risk factors affecting both morbidity and OS. Results: A total 470 lung procedures were performed (4 pneumonectomies, 46 lobectomies/bilobectomies, 13 segmentectomies and 407 wedge resections) on 461 patients (258 men and 203 women, mean age of 63.1 years). The majority of patients had metastases from colorectal cancer (45.8%). In most cases (63.6%), patients had only one lung metastasis. A minimally invasive approach was chosen in 143 cases (30.4%). The mean operative time was 118 min, with no reported deaths. Morbidity most frequently consisted of prolonged air leaking and bleeding, but no re-intervention was required. Statistical analysis revealed that morbidity was significantly affected by operative time and pulmonary comorbidities, while OS was significantly affected by disease-free interval (DFI) > 24 months (p = 0.005), epithelial histology (p = 0.001) and colorectal histology (p = 0.004) during univariate analysis. No significant correlation was found between OS and age, gender, surgical approach, surgical extent, surgical device, the number of resected metastases, lesion diameter, the site of lesions and nodal involvement. Multivariate analysis of OS confirmed that only epithelial histology and DFI were risk-factors, with p-values of 0.041 and 0.031, respectively. Conclusions: Lung metastasectomy appears to be a safe procedure, with acceptable morbidity, even with a minimally invasive approach. However, it remains a local treatment of a systemic disease. Therefore, careful attention should be paid to selecting patients who could truly benefit from surgical intervention.

Evaluation of a novel university-based testing platform to increase access to SARS-CoV-2 testing during the COVID-19 pandemic in a cohort study.

OBJECTIVE: We aimed to evaluate the feasibility and utility of an unsupervised testing mechanism, in which participants pick up a swab kit, self-test (unsupervised) and return the kit to an on-campus drop box, as compared with supervised self-testing at staffed locations. DESIGN: University SARS-CoV-2 testing cohort. SETTING: Husky Coronavirus Testing provided voluntary SARS-CoV-2 testing at a university in Seattle, USA. OUTCOME MEASURES: We computed descriptive statistics to describe the characteristics of the study sample. Adjusted logistic regression implemented via generalised estimating equations was used to estimate the odds of a self-swab being conducted through unsupervised versus supervised testing mechanisms by participant characteristics, including year of study enrolment, pre-Omicron versus post-Omicron time period, age, sex, race, ethnicity, affiliation and symptom status. RESULTS: From September 2021 to July 2022, we received 92 499 supervised and 26 800 unsupervised self-swabs. Among swabs received by the laboratory, the overall error rate for supervised versus unsupervised swabs was 0.3% vs 4%, although this declined to 2% for unsupervised swabs by the spring of the academic year. Results were returned for 92 407 supervised (5% positive) and 25 836 unsupervised (4%) swabs from 26 359 participants. The majority were students (79%), 61% were female and most identified as white (49%) or Asian (34%). The use of unsupervised testing increased during the Omicron wave when testing demand was high and stayed constant in spring 2022 even when testing demand fell. We estimated the odds of using unsupervised versus supervised testing to be significantly greater among those <25 years of age (p<0.001), for Hispanic versus non-Hispanic individuals (OR 1.2, 95% CI 1.0 to 1.3, p=0.01) and lower among individuals symptomatic versus asymptomatic or presymptomatic (0.9, 95% CI 0.8 to 0.9, p<0.001). CONCLUSIONS: Unsupervised swab collection permitted increased testing when demand was high, allowed for access to a broader proportion of the university community and was not associated with a substantial increase in testing errors.

Cost-Effectiveness and Budget Impact Analysis of the Implementation of Differentiated Service Delivery Models for HIV Treatment in Mozambique: a Modelling Study.

INTRODUCTION: In 2018, the Mozambique Ministry of Health launched guidelines for implementing differentiated service delivery models (DSDMs) to optimize HIV service delivery, improve retention in care, and ultimately reduce HIV-associated mortality. The models were fast-track, 3-month antiretrovirals dispensing, community antiretroviral therapy groups, adherence clubs, family approach and three one-stop shop models: adolescent-friendly health services, maternal and child health, and tuberculosis. We conducted a cost-effectiveness analysis and budget impact analysis to compare these models to conventional services. METHODS: We constructed a decision tree model based on the percentage of enrolment in each model and the probability of the outcome (12-month retention in treatment) for each year of the study period-three for the cost-effectiveness analysis (2019-2021) and three for the budget impact analysis (2022-2024). Costs for these analyses were primarily estimated per client-year from the health system perspective. A secondary cost-effectiveness analysis was conducted from the societal perspective. Budget impact analysis costs included antiretrovirals, laboratory tests and service provision interactions. Cost-effectiveness analysis additionally included start-up, training and clients' opportunity costs. Effectiveness was estimated using an uncontrolled interrupted time series analysis comparing the outcome before and after the implementation of the differentiated models. A one-way sensitivity analysis was conducted to identify drivers of uncertainty. RESULTS: After implementation of the DSDMs, there was a mean increase of 14.9 percentage points (95% CI: 12.2, 17.8) in 12-month retention, from 47.6% (95% CI, 44.9-50.2) to 62.5% (95% CI, 60.9-64.1). The mean cost difference comparing DSDMs and conventional care was US$ -6 million (173,391,277 vs. 179,461,668) and -32.5 million (394,705,618 vs. 433,232,289) from the health system and the societal perspective, respectively. Therefore, DSDMs dominated conventional care. Results were most sensitive to conventional care interaction costs in the one-way sensitivity analysis. For a population of 1.5 million, the base-case 3-year financial costs associated with the DSDMs was US$550 million, compared with US$564 million for conventional care. CONCLUSIONS: DSDMs were less expensive and more effective in retaining clients 12 months after antiretroviral therapy initiation and were estimated to save approximately US$14 million for the health system from 2022 to 2024.

Fatigue Crack Growth Rates and Crack Tip Opening Loads in CT Specimens Made of SDSS and Manufactured Using WAAM.

Additive manufacturing offers greater flexibility in the design and fabrication of structural components with complex shapes. However, the use of additively manufactured parts for load-bearing structural applications, specifically involving cyclic loading, requires a thorough investigation of material fatigue properties. These properties can be affected by many factors, including residual stresses and crack tip shielding mechanisms, which can be very different from those of conventionally manufactured materials. This research focuses on super duplex stainless steels (SDSSs) fabricated with wire arc additive manufacturing (WAAM) and investigates their fatigue crack growth rates and the net effect of crack tip shielding mechanisms. Using the compliance-based method, we measured crack tip opening loads in compact tension (CT) specimens with cracks propagating longitudinally and transversely to the WAAM deposition direction. It was found that fatigue crack growth rates were very similar in both directions when correlated by the effective stress intensity factor range. However, the differences in crack tip opening loads explain a quite significant influence of the deposition direction on the fatigue life.