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The subthalamic nucleus and internal pallidum are main target sites for deep brain stimulation in Parkinson’s disease. Multiple trials that investigated subthalamic versus pallidal stimulation were unable to settle on a definitive optimal target between the two. One reason could be that the effect is mediated via a common functional network. To test this hypothesis, we calculated connectivity profiles seeding from deep brain stimulation electrodes in 94 patients that underwent subthalamic and 28 patients with pallidal treatment based on a normative connectome atlas calculated from 1000 healthy subjects. In each cohort, we calculated connectivity profiles that were associated with optimal clinical improvements. The two maps showed striking similarity and were able to cross-predict outcomes in the respective other cohort (R = 0.37 at P < 0.001; R = 0.34 at P = 0.032). Next, we calculated an agreement map, which retained regions common to both target sites. Crucially, this map was able to explain an additional amount of variance in clinical improvements of either cohort when compared to the maps calculated on each cohort alone. Finally, we tested profiles and predictive utility of connectivity maps calculated from different motor symptom subscores with a specific focus on bradykinesia and rigidity. While our study is based on retrospective data and indirect connectivity metrics, it may deliver empirical data to support the hypothesis of a largely overlapping network associated with effective deep brain stimulation in Parkinson’s disease irrespective of the specific target.

Patient-centred outcomes are increasingly recognised as crucial measures of healthcare quality. Days alive and at home up to 30 days after surgery (DAH30 ) is a validated and readily obtainable patient-centred outcome measure that integrates much of the peri-operative patient journey. However, the minimal difference in DAH30 that is clinically important to patients is unknown. We designed and administered a 28-item survey to evaluate the minimal clinically important difference in DAH30 among adult patients undergoing inpatient surgery. Patients were approached pre-operatively or within 2 days postoperatively. We did not study patients undergoing day surgery or nursing home residents. Patients ranked their opinions on the importance of discharge home using a Likert scale (from 1, not important at all to 6, extremely important) and the minimum number of extra days at home that would be meaningful using this scale. We recruited 104 patients; the survey was administered pre-operatively to 45 patients and postoperatively to 59 patients. The mean (SD) age was 53.5 (16.5) years, and 51 (49%) patients were male. Patients underwent a broad range of surgery of mainly intermediate (55%) to major (33%) severity. The median minimal clinically important difference for DAH30 was 3 days; this was consistent across a broad range of scenarios, including earlier discharge home, complications delaying hospital discharge and the requirement for admission to a rehabilitation unit. Discharge home earlier than anticipated and discharge home rather than to a rehabilitation facility were both rated as important (median score = 5). Empirical data on the minimal clinically important difference for DAH30 may be useful to determine sample size and to guide the non-inferiority margin for future clinical trials.

This study measured the impacts of failure in Crisis and Emergency Risk Communication (CERC) during the outbreak of a contagious Corona viral disease. The study measured the impacts by the number of individuals and hospitals exposed to the virus. The 2015 Middle East Respiratory Syndrome (MERS) outbreak in South Korea was used to investigate the consequences of CERC failure, where the names of hospitals exposed to MERS‐CoV were withheld from the public during the early stage of virus diffusion. Empirical data analyses and simulated model tests were conducted. The findings of analyses and tests show that an early announcement of the hospital names and publicizing the necessary preventive measures could have reduced the rate of infection by approximately 85% and the number of contaminated healthcare facilities by 39% at maximum. This level of reduction is comparable to that of vaccination and of social distancing.

Clinical cancer genomic testing based on next-generation sequencing can help select genotype-matched therapy and provide diagnostic and prognostic information. Pathological tissue from malignant tumors obtained during routine practice are frequently used for genomic testing. This article is aimed to standardize the proper handling of pathological specimens in practice for genomic medicine based on the findings established in "Guidelines on the handling of pathological tissue samples for genomic medicine (in Japanese)" published by The Japanese Society of Pathology (JSP) in 2018. The two-part practical guidelines are based on empirical data analyses; Part 1 describes the standard preanalytic operating procedures for tissue collection, processing, and storage of formalin-fixed paraffin-embedded (FFPE) samples, while Part 2 describes the assessment and selection of FFPE samples appropriate for genomic testing, typically conducted by a pathologist. The guidelines recommend that FFPE sample blocks be used within 3 years from preparation, and the tumor content should be >= 30% (minimum 20%). The empirical data were obtained from clinical studies performed by the JSP in collaboration with leading Japanese cancer genome research projects. The Japanese Ministry of Health, Labour, and Welfare (MHLW) recommended to comply with the JSP practical guidelines in implementing cancer genomic testing under the national health insurance system in over 200 MHLW-designated core and cooperative cancer genome medicine hospitals in Japan.

BACKGROUND: By the beginning of December 2020, some vaccines against COVID-19 already presented efficacy and security, which qualify them to be used in mass vaccination campaigns. Thus, setting up strategies of vaccination became crucial to control the COVID-19 pandemic. METHODS: We use daily COVID-19 reports from Chicago and New York City (NYC) from 01-Mar2020 to 28-Nov-2020 to estimate the parameters of an SEIR-like epidemiological model that accounts for different severity levels. To achieve data adherent predictions, we let the model parameters to be time-dependent. The model is used to forecast different vaccination scenarios, where the campaign starts at different dates, from 01-Oct-2020 to 01-Apr-2021. To generate realistic scenarios, disease control strategies are implemented whenever the number of predicted daily hospitalizations reaches a preset threshold. RESULTS: The model reproduces the empirical data with remarkable accuracy. Delaying the vaccination severely affects the mortality, hospitalization, and recovery projections. In Chicago, the disease spread was under control, reducing the mortality increment as the start of the vaccination was postponed. In NYC, the number of cases was increasing, thus, the estimated model predicted a much larger impact, despite the implementation of contention measures. The earlier the vaccination campaign begins, the larger is its potential impact in reducing the COVID-19 cases, as well as in the hospitalizations and deaths. Moreover, the rate at which cases, hospitalizations and deaths increase with the delay in the vaccination beginning strongly depends on the shape of the incidence of infection in each city.

Drawing on two case studies from large-scale fieldwork carried out on euthanasia in Belgium and assisted suicide in Switzerland, this article focuses on the processes of normalization that structure aid in dying. Normalization takes place through a set of apparatuses only partially derived from current legislation, which underlie the relationships that develop between those requesting aid in dying, healthcare staff, volunteers, and loved ones. The resulting arrangements are specific to each national context, but the empirical data also point to broadly common traits, highlighting new paradigmatic forms of aid in dying in the contemporary era.

Routinely collected data have been increasingly used to assess long-term opioid therapy (LTOT) patterns, with very little guidance on how to measure LTOT from these data sources. We conducted a systematic review of studies published between January 2000 and July 2019 to catalogue LTOT definitions, the rationale for definitions and LTOT rates in observational research using routinely collected data in nonsurgical settings. We screened 4056 abstracts, 210 full-text manuscripts and included 128 studies, mostly from the United States (81%) and published between 2015 and 2019 (69%). We identified 78 definitions of LTOT, commonly operationalised as 90 days of use within a year (23%). Studies often used multiple criteria to derive definitions (60%), mostly based on measures of duration, such as supply days/days of use (66%), episode length (21%) or prescription fills within specified time periods (12%). Definitions were based on previous publications (63%), clinical judgment (16%) or empirical data (3%); 10% of studies applied more than one definition. LTOT definition was not provided with enough details for replication in 14 studies and 38 studies did not specify the opioids evaluated. Rates of LTOT within study populations ranged from 0.2% to 57% according to study design and definition used. We observed a substantial rise in the last 5 years in studies evaluating LTOT with large variability in the definitions used and poor reporting of the rationale and implementation of definitions. This variation impacts on research reproducibility, comparability of findings and the development of strategies aiming to curb therapy that is not guideline-recommended.

Modelling is a well-established concept for understanding the typical shape and pattern of age-specific fertility. The distribution of India’s age-specific fertility rate (ASFR) is unimodal and positively skewed and is distinct from the ASFR of the developed countries. The existing models (P-K model, Gompertz model, Skew-normal model and G-P model considered here) that were developed, based on the experiences of the developed countries, failed to fit the single-year age-specific fertility pattern for India as a whole and for the six selected states. Our study has proposed four flexible models, to capture the diverse age pattern of fertility, observed in the Indian states. The proposed models were compared in three ways; among themselves, with the original models and with the popular Hadwiger model. The parameters of these proposed models were estimated through the Non-Linear Least Squares Method. To find the model with best fit, we used the corrected version of Akaike’s Information Criterion (AICc). Optimization of the four original models was successfully done. When the model was fitted to the empirical data of the 4th round of the National Family Health Survey conducted in 2015–2016, the results of this study showed that all the four proposed models outperform their corresponding original models and the Hadwiger model. When comparison among the proposed models was done, the Modified Gompertz Model provided the best fit for India, Uttar Pradesh and Gujarat. Whereas, the Modified P-K model gave the best fit for West Bengal, Tripura and Karnataka. The Modified G-P model is the most suitable model for Punjab. Although our proposed models illustrated the fitting of ASFR for India as a whole and the selected six states only, it provides an important tool for the policymakers and the government authorities to project fertility rates and to understand the fertility transitions in India and various other states.

Purpose of review To provide an update of recent studies describing the effects of transcranial direct current stimulation (tDCS) on patients with schizophrenia, with particular focus on auditory verbal hallucinations (AVH), cognitive deficits, and negative symptoms. Recent findings As a low-cost, easy-to-use neuromodulation technique, tDCS may have clinical implications for those suffering from treatment-persistent AVH, negative symptoms, and cognitive symptoms in schizophrenia. Over the past decade, tDCS has shown no effects for negative symptoms, except when used at a high frequency of sessions, and inconclusive results for AVH and cognitive symptoms. The treatment has little to no adverse effects. Summary The studies reviewed here support the need for further investigation and empirical data regarding the use of tDCS. The underlying mechanisms of tDCS as well as the most effective stimulation parameters must be better understood. Findings support the need for increased duration and frequency of tDCS sessions. One of the next steps is the investigation of effects of concomitant nonpharmacological treatments with tDCS.

Background Condition-specific quality of life (QoL) instruments are more representative of the priorities of people with lived experience. As such, the development of the first and only bipolar disorder (BD) specific measurement instrument, the Quality of Life in Bipolar Disorder (QoL.BD) questionnaire, marked an important step forward for the literature. The present systematic review aims to characterise applications of the QoL.BD in the BD literature and review empirical findings obtained from studies using this measure. Methods A systematic search identified 37 peer-reviewed publications which reported original empirical data using the QoL.BD in a BD population. No restrictions were placed on language/study type. Results Adaptations to the QoL.BD displayed appropriate psychometric properties. Although clinical trials were typically underpowered, promising effect sizes for a number of treatment modalities were reported. QoL.BD scores were moderately correlated with depressive symptoms; a number of candidate predictors were identified. Limitations Due to resource limitations, the present review used one database (Google Scholar), and a single author reviewed articles for eligibility. On balance the risks of missing relevant studies were deemed minimal. Conclusion A sizeable, international body of evidence now exists regarding the measurement, presentation, and treatment of condition-specific aspects of QoL in BD. Key avenues for future research include large scale, randomized control clinical trials using the QoL.BD as a primary outcome, and granular exploration of potential correlates of QoL.BD domain scores. Finally, longer follow-up periods are required to inform understanding of the dynamic relationship between clinical variables and condition-specific aspects of QoL in BD.

Objective The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI—resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist. Methods We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital-specific CXR generation rates and reporting rates and pathology distribution. Using this, we simulated the standard worklist processing “first-in, first-out” (FIFO) and compared it with a worklist prioritization based on urgency. Examination prioritization was performed by the AI, classifying eight different pathological findings ranked in descending order of urgency: pneumothorax, pleural effusion, infiltrate, congestion, atelectasis, cardiomegaly, mass, and foreign object. Furthermore, we introduced an upper limit for the maximum waiting time, after which the highest urgency is assigned to the examination. Results The average RTAT for all critical findings was significantly reduced in all prioritization simulations compared to the FIFO simulation (e.g., pneumothorax: 35.6 min vs. 80.1 min; p p p Conclusion Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO. Key Points • Development of a realistic clinical workflow simulator based on empirical data from a hospital allowed precise assessment of smart worklist prioritization using artificial intelligence. • Employing a smart worklist prioritization without a threshold for maximum waiting time runs the risk of false negative predictions of the artificial intelligence greatly increasing the report turnaround time. • Use of a state-of-the-art convolution neural network can reduce the average report turnaround time almost to the upper limit of a perfect classification algorithm (e.g., pneumothorax: 35.6 min vs. 30.4 min).

SUMMARY Super-spreading events in an outbreak can change the nature of an epidemic. Therefore, it is useful for public health teams to determine if an ongoing outbreak has any contribution from such events, which may be amenable to interventions. We estimated the basic reproductive number (R0) and the dispersion factor (k) from empirical data on clusters of epidemiologically-linked COVID-19 cases in Hong Kong, Japan and Singapore. This allowed us to infer the presence or absence of super-spreading events during the early phase of these outbreaks. The relatively large values of k implied that large cluster sizes, compatible with super-spreading, were unlikely.

Multiple studies have shown that pharmacologic treatments for attention-deficit hyperactivity disorder (ADHD), especially stimulants, are generally effective. There is yet a paucity of empirical data, however, for some common clinical conditions overlooked in the ADHD treatment guidelines. Some examples include: in cases of first line treatment failure, it is unclear whether switching from one type of stimulant to another is beneficial. In cases of comorbid ADHD and severe aggressive/disruptive behavior in children, it is unclear whether the best first-line treatment is stimulants or atypical antipsychotics like risperidone. In cases of ADHD with comorbid anxiety disorders, there is no clear evidence regarding optimal treatment. The objectives of this article are to review these issues and propose possible answers for such clinical dilemmas.

Objective:To assess the quantity and focus of recent empirical research regarding the effect of micronutrient supplementation on live birth outcomes in low-risk pregnancies from high-income countries.Design:A systematic quantitative literature review.Setting:Low-risk pregnancies in World Bank-classified high-income countries, 2019.Results:Using carefully selected search criteria, a total of 2475 publications were identified, of which seventeen papers met the inclusion criteria for this review. Data contributing to nine of the studies were sourced from four cohorts; research originated from ten countries. These cohorts exhibited a large number of participants, stable data and a low probability of bias. The most recent empirical data offered by these studies was 2011; the most historical was 1980. In total, fifty-five categorical outcome/supplement combinations were examined; 67·3 % reported no evidence of micronutrient supplementation influencing selected outcomes.Conclusions:A coordinated, cohesive and uniform empirical approach to future studies is required to determine what constitutes appropriate, effective and safe micronutrient supplementation in contemporary cohorts from high-income countries, and how this might influence pregnancy outcomes.

Theoretical models are typically developed through a deductive process where a researcher formulates a system of dynamic equations from hypothesized mechanisms. Recent advances in algorithmic methods can discover dynamic models inductively– directly from data. Most previous research has tested these methods by rediscovering models from synthetic data generated by the already known model. Here we apply Sparse Identification of Nonlinear Dynamics (SINDy) to discover mechanistic equations for disease dynamics from case notification data for measles, chickenpox, and rubella. The discovered models provide a good qualitative fit to the observed dynamics for all three diseases, However, the SINDy chickenpox model appears to overfit the empirical data, and recovering qualitatively correct rubella dynamics requires using power spectral density in the goodness-of-fit criterion. When SINDy uses a library of second-order functions, the discovered models tend to include mass action incidence and a seasonally varying transmission rate–a common feature of existing epidemiological models for childhood infectious diseases. We also find that the SINDy measles model is capable of out-of-sample prediction of a dynamical regime shift in measles case notification data. These results demonstrate the potential for algorithmic model discovery to enrich scientific understanding by providing a complementary approach to developing theoretical models.

Nolan, D, Lynch, AE, and Egan, B. Self-reported prevalence, magnitude, and methods of rapid weight loss in male and female competitive powerlifters. J Strength Cond Res 36(2): 405-410, 2022-Rapid weight loss (RWL) is common practice in weight category sports, but no empirical data exist documenting the weight-making practices of competitive strength athletes. This study investigated the self-reported prevalence, magnitude, and methods of RWL used by male and female powerlifters when preparing for competition. Competitive powerlifters (n = 321; M/F, 194/127) completed an anonymous online questionnaire previously validated for assessment of methods of RWL. Respondents were categorized by their federation's respective antidoping policy, weigh-in procedure, and degree of assistive equipment allowed, in addition to their use or not of RWL. Subgroup analyses were performed on the largest category of respondents (n = 200, M/F, 117/83; ≤2-hour weigh-in, drug-tested, "raw") based on sex, weight category, and competitive status. Prevalence of RWL was 85.8%, with an average RWL of 3.0 ± 1.9% body mass and an RWL score of 25.1 ± 7.4. Neither sex nor weight category influenced the RWL score, but in male athletes, a lower RWL score (22.7 ± 6.3) was reported in athletes in the lowest tertile of the Wilks score (p = 0.015). Frequencies of "always use" were reported as 54.0% for fluid restriction and 49.0% for water loading. Coaches (37.5%) and online resources (35.0%) were "very influential" on RWL practices in these athletes, while doctors (85.5%) and dieticians (63.0%) were reported to be "not influential." The prevalence of RWL is high in competitive powerlifting, and the methods used are akin to other weight category sports, but the reported RWL scores are lower than reported in combat sports with longer recovery periods after weigh-in.

Biosimilar medicines have shown similarity with the originator biologic and offer a similar clinical outcome generally at a lower cost. This paper identifies benefits of off-patent biologics and biosimilars, and illustrates these benefits with empirical data from Europe. We provide a narrative review of published literature on values and benefits of biosimilars in Europe. The results describe cost savings as the key driver stemming from the lower price of biosimilars, than that of originator products, and from price competition between biosimilar(s), originator, and next-generation products. Cost savings may then translate into a number of other associated benefits. The lower price of biosimilars and similar effectiveness to the originator biologics improve cost effectiveness, implying that reimbursement can be granted or extended to other patient groups, or that the biologic therapy can be moved to an earlier line of treatment. Cost savings from biosimilars can be used to increase patient access to therapy or to increase the number of healthcare professionals. Finally, competition between off-patent biologics and biosimilars may stimulate an innovation in the formulation and development of next-generation biologics. Our paper illustrates that the benefit of off-patent biologics and biosimilars is not restricted to cost savings, but that these medicines may contribute to an expansion of medical treatment options for patients, hence concomitantly contributing to the long-term sustainability of the healthcare system. This review provides a broader view for clinical and economic decision makers and healthcare professionals on the added benefits of off-patent biologics and their use in clinical practice. ispartof: BIODRUGS vol:34 issue:2 pages:159-170 ispartof: location:New Zealand status: published

With the increasing prevalence of technology, the internet is often the first step for potential pet owners searching for an adoptable dog. However, best practices for the online portrayal of shelter and foster dogs remain unclear. Different online photo backgrounds appearing on adoption websites for shelter dogs may impact adoption speed by influencing viewer interest. Online clicking behaviour on pet profiles and human-directed sociability, broadly defined, has been previously linked to increased adoption likelihood. Therefore, the objective of this study was to determine the relationship between photo backgrounds of shelter dogs and online clicking as well as perceived human-directed sociability. In a virtual experiment, 680 participants were asked to rank the sociability and friendliness of four different adoptable dogs on a scale from 0–10. The photo background of each dog was digitally altered and randomly assigned to four experimental background conditions: 1) outdoor, 2) home indoor, 3) in-kennel, and 4) plain coloured. As a proxy for adoption interest, a link to the dog’s adoption profile was presented on each slide and the clicking behaviour of participants on this link was recorded. Mixed logistic regression and Poisson models revealed that background did not affect participants’ link-clicking behaviour (chisq = 3.55, df = 3, p = .314) nor perceptions of sociability (statistic = 6.19, df = 3, p = .103). Across all backgrounds, only 4.74% of presented slides culminated in participant link-clicking. Sociability scores also did not predict link clicking. Assessment of participant-related factors and dog ID revealed that link-clicking and sociability scores of photographs were influenced by differences between dogs themselves and unaffected by participants’ awareness of study hypotheses. We conclude that artificial background types did not affect participant responses. The results demonstrate the importance of empirical data in making marketing decisions in animal shelters. Understanding which aspects of online marketing materials impact viewer interest will provide guidance for both animal shelter personnel and foster families to improve the speed of adoption of the animals in their care.

Dry heat decontamination has been shown to effectively inactivate viruses without compromising the integrity of delicate personal protective equipment (PPE), allowing safe reuse and helping to alleviate shortages of PPE that have arisen due to COVID-19. Unfortunately, current thermal decontamination guidelines rely on empirical data which are often sparse, limited to a specific virus, and unable to provide fundamental insight into the underlying inactivation reaction. In this work, we experimentally quantified dry heat decontamination of SARS-CoV-2 on disposable masks and validated a model that treats the inactivation reaction as thermal degradation of macromolecules. Furthermore, upon nondimensionalization, all of the experimental data collapse onto a unified curve, revealing that the thermally driven decontamination process exhibits self-similar behavior. Our results show that heating surgical masks to 70 °C for 5 minutes inactivates over 99.9% of SARS-CoV-2. We also characterized the chemical and physical properties of disposable masks after heat treatment and did not observe degradation. The model presented in this work enables extrapolation of results beyond specific temperatures to provide guidelines for safe PPE decontamination. The modeling framework and self-similar behavior are expected to extend to most viruses—including yet-unencountered novel viruses—while accounting for a range of environmental conditions., Graphical abstract

Background There is limited empirical data quantifying the utility of genetic testing for families of children with autism spectrum disorder (ASD) or related neurodevelopmental disorders (NDD). We assessed the utility of clinical chromosomal microarray analysis (CMA), defined by diagnostic yield and parental empowerment, in population‐based sample of parents of affected children; and explored child, family, and health services factors predictive of empowerment. Methods Participants were families of children undergoing diagnostic assessments, between 2016 and 2019. Diagnostic yield of CMA in affected children was determined. Parental empowerment was measured through adapted version of the Genetics Counseling Outcome Scale‐24. Parents completed questionnaires to capture child, family, and health service factors. Results The diagnostic yield of CMA was 2.8% for pathogenic variants. Parental empowerment was significantly correlated with family functioning and aspects of perceived family‐centeredness of care. The model accounted for 49.8% of the variation in parental empowerment, F (10,37) = 3.67, p = 0.002. After accounting for other predictors, parental perception of the provision of general information remained significantly associated with empowerment. Conclusion The informational needs of families play an important role in their empowerment during genetic testing. Meeting these needs and monitoring empowerment can aid genomic technologies integration in personalized healthcare for ASD/NDD.

The first-line physicians’ practice in Kisangani city in Democratic Republic of Congo: Towards a typology. Background: In the Democratic Republic of the Congo (DRC), for a number of years, there has been a spontaneous and growing phenomenon of physicians operating at the front line of the health system, while this role is traditionally devolved to nurse-practitioners. This phenomenon does not align with the current health policy. Aim: The aim of this paper is to develop and discuss the main types of frontline physicians in the city of Kisangani. Setting: We conducted a descriptive cross-sectional study in two urban districts in the city of Kisangani. Methods: The study population consisted of all first-line health facilities that employed at least one physician. The construction of a typology of first-line physicians consisted of three stages: identification and definition of relevant dimensions of analysis; grouping cases based on empirical data; and analysis of significant relationships and establishment of the typology itself. Results: An involvement of physicians in healthcare delivery at the first line was observed in 60% of all first line facilities in the two urban districts. Two main types of first-line physicians were identified: firstly, and by large the most prevalent one (96% of cases), the ‘hospital-like physician’, and secondly, the much less frequent type of the ‘supervision physician’. Conclusion: The involvement of physicians in first line healthcare is today a growing phenomenon in the DRC, especially in urban areas. The most dominant expression of this phenomenon is a transposition of the hospital-based physician model to the first line healthcare services, which thereby jeopardizing the specificity of first line healthcare.

Transmission of Hepatitis C (HCV) continues via sharing of injection equipment between people who inject drugs (PWID). Network-based modelling studies have produced conflicting results about whether random treatment is preferable to targeting treatment at PWID with multiple partners. We hypothesise that differences in the modelled injecting network structure produce this heterogeneity. The study aimed to test how changing network structure affects HCV transmission and treatment effects. We created three dynamic injecting network structures connecting 689 PWID (UK-net, AUS-net and USA-net) based on published empirical data. We modelled HCV in the networks and at 5 years compared prevalence of HCV 1) with no treatment, 2) with randomly targeted treatment and 3) with treatment targeted at PWID with the most injecting partnerships (degree-based treatment). HCV prevalence at 5 years without treatment differed significantly between the three networks (UK-net (42.8%) vs. AUS-net (38.2%), p < 0.0001 and vs. USA-net (54.0%), p < 0.0001). In the treatment scenarios UK-net and AUS-net showed a benefit of degree-based treatment with a 5-year prevalence of 1.0% vs. 9.6% p < 0.0001 and 0.15% vs. 0.44%, p < 0.0001. USA-net showed no significant difference (29.3% vs. 29.2%, p = 0.0681). Degree-based treatment was optimised with low prevalence, moderate treatment coverage conditions whereas random treatment was optimised in low treatment coverage, high prevalence conditions. In conclusion, injecting network structure determines the transmission rate of HCV and the most efficient treatment strategy. In real-world injecting network structures, the benefit of targeting HCV treatment at individuals with multiple injecting partnerships may have been underestimated.

Despite the widespread belief that donor organ availability varies around holidays and seasons, there is little empirical data supporting this long-held belief. Variations in donor heart availability may be of interest to patients and clinicians. The UNOS/OPTN registry was queried for all heart donations from October 1987 through March 2017. Daily heart donation rates were modeled nationally using Poisson regression including splines for year and day of the year. Seasonality was assessed using a likelihood ratio test for the spine terms for day of the year. The holiday effect was assessed using conditional logistic regression. Seasonal plots suggest a significant, although modest, increase in organ availability during the summer months, except for region 1. The regions with the highest amplitude were region 7 (peak: June 21, amplitude: 16.63%) and region 6 (peak: July 5, amplitude: 11.29%). There was no significant difference in the odds of heart donation when comparing holidays vs. non-holidays using national data (odds ratio [95% CI]: 1.01 [0.98, 1.03], P = 0.560) or any regional subsets. There was no observable correlation between donor heart availability and holidays. However, a significant seasonality effect was observed with higher donation rates occurring during warmer months.

Background Since phase III trials for the most prominent vaccines excluded immunocompromised or immunosuppressed patients, data on safety and efficacy of SARS‐CoV‐2 vaccines for recipients of solid organ transplantations are scarce. Aims Our study offers a synthesis of expert opinions aligned with available data addressing key questions of the clinical management of SARS‐CoV‐2 vaccinations for transplant patients. Method An online research was performed retrieving available recommendations by national and international transplantation organizations and state institutions on SARS‐CoV2 vaccination management for transplant recipients. Results Eleven key statements were identified from recommendations by 18 national and international societies, and consensus for the individual statements was evaluated by means of the Society Recommendation Consensus score. The highest consensus level (SRC A) was found for prioritized access to vaccination for transplant patients despite anticipation of a weakened immune response. All currently authorized vaccines can be considered safe for transplant patients (SRC A). The handling of immunosuppressive medication, the timely management of vaccines, and other aspects were aligned with available expert opinions. Conclusion Expert consensus can be determined for crucial aspects of the implementation of SARS‐CoV‐2 vaccination programs. We hereby offer a tool for immediate decision‐making until empirical data becomes available.

The acquisition of translation equivalents is often considered a special component of bilingual children's vocabulary development, as bilinguals have to learn words that share the same meaning across their two languages. This study examined three contrasting accounts for bilingual children's acquisition of translation equivalents relative to singlets (i.e., words that are first labels for a referent): the Avoidance Account whereby translation equivalents are harder to learn, the Preference Account whereby translation equivalents are easier to learn, and the Neutral Account whereby translation equivalents and singlets are learned similarly. To adjudicate between these accounts, Study 1 explored patterns of translation equivalent learning under a novel computational model — the Bilingual Vocabulary Model — which quantifies translation equivalent knowledge as a function of the probability of learning words in each language, and includes a bias parameter that varies the difficulty of learning translation equivalents according to each account. Study 2 tested model-derived predictions against vocabulary data from 200 French–English bilingual children aged 18–33 months. Results showed a close match between the model predictions and bilingual children's patterns of translation equivalent learning. At smaller vocabulary sizes, data matched the Preference Account, while at larger vocabulary sizes they matched the Neutral Account. Our findings show that patterns of translation equivalent learning emerge predictably from the word learning process, and potentially reveal a qualitative shift in translation equivalent learning as bilingual children develop and learn more words.

BACKGROUND/PURPOSE The outbreak of the Coronavirus disease 2019 (COVID-19) has led to unprecedented impact on mental health globally. Recent empirical data however, indicated that suicide rates in many countries remained unchanged or even decreased. Existing studies assessed the overall rates and did not stratify by age-subgroups. METHODS We used an interrupted time-series analysis to model the age-stratified (

OBJECTIVE To report preliminary empirical data on a novel, developmentally appropriate, observational postconcussive symptoms inventory for infants, toddlers, and preschoolers. SETTING Emergency departments of 2 tertiary, urban pediatric hospitals. PARTICIPANTS Ninety-eight children (0-8 years of age; mean age at injury = 33.00, SD = 24.7 months) with mild traumatic brain injury (concussion) divided into younger (0-2 years) and older (3-8 years) age groups. DESIGN Observational study. MAIN MEASURE The Report of Early Childhood Traumatic Injury Observations & Symptoms (REACTIONS) documents 17 postconcussive symptoms representing observable manifestations thereof and was completed by parents in the acute (24-48 hours; n = 65), subacute (7-14 days; n = 78), and/or persistent phase (25-35 days; n = 72) post-mild traumatic brain injury. RESULTS Different patterns of postconcussive symptoms were reported by age group, with behavioral manifestations particularly salient in younger children. More children younger than 2 years had sleep and comfort-seeking symptoms at each of the 3 postinjury time points. CONCLUSION Postconcussive symptoms may manifest differently after mild traumatic brain injury sustained during early childhood. To fully understand and address their presence and evolution, developmentally sound measures such as the REACTIONS inventory are required.

Background Serial screening is critical for restricting spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by facilitating timely identification of infected individuals to interrupt transmission. Variation in sensitivity of different diagnostic tests at different stages of infection has not been well documented. Methods In a longitudinal study of 43 adults newly infected with SARS-CoV-2, all provided daily saliva and nasal swabs for quantitative reverse transcription polymerase chain reaction (RT-qPCR), Quidel SARS Sofia antigen fluorescent immunoassay (FIA), and live virus culture. Results Both RT-qPCR and Quidel SARS Sofia antigen FIA peaked in sensitivity during the period in which live virus was detected in nasal swabs, but sensitivity of RT-qPCR tests rose more rapidly prior to this period. We also found that serial testing multiple times per week increases the sensitivity of antigen tests. Conclusions RT-qPCR tests are more effective than antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (given timely results reporting). All tests showed >98% sensitivity for identifying infected individuals if used at least every 3 days. Daily screening using antigen tests can achieve approximately 90% sensitivity for identifying infected individuals while they are viral culture positive.

Research that is integrated into ongoing clinical activities holds the potential to accelerate the generation of knowledge to improve the health of individuals and populations. Yet integrating research into clinical care presents difficult ethical and regulatory challenges, including how or whether to obtain informed consent. Multiple empirical studies have explored patients' and the public's attitudes toward approaches to consent for pragmatic research. Questions remain, however, about how to use the resulting empirical data in resolving normative and policy debates and what kind of data warrants the most consideration. We recommend prioritizing data about what people consider acceptable with respect to consent for pragmatic research and data about people's informed, rather than initial, preferences on this subject. In addition, we advise caution regarding the weight given to majority viewpoints and identify circumstances when empirical data can be overridden. We argue that empirical data bolster normative arguments that alterations of consent should be the default in pragmatic research; waivers are appropriate only when the pragmatic research would otherwise be impracticable and has sufficiently high social value.

Analyzing the structure and function of the brain from a network perspective has increased considerably over the past two decades, with regional subnetwork analyses becoming prominent in the recent literature. However, despite the fact that the brain, as a complex system of interacting subsystems (i.e., subnetworks), cannot be fully understood by analyzing its constituent parts as independent elements, most studies extract subnetworks from the whole and treat them as independent networks. This approach entails neglecting their interactions with other brain regions and precludes identifying potential compensatory mechanisms outside the analyzed subnetwork. In this study, using simulated and empirical data, we show that the analysis of brain subnetworks within the context of their whole-brain networks, that is, including their interactions with other brain regions, can yield different outcomes when compared to analyzing them as independent networks. We also provide a multivariate mixed-effects modeling framework that allows analyzing subnetworks within the context of their whole-brain networks, and show that it can better disentangle global (whole-brain) and local (subnetwork) differences when compared to standard t-test analyses. T-test analyses may produce misleading results in identifying complex global and local level differences. The provided multivariate model is an extension of a previously developed model for global, system-level hypotheses about the brain. The modified version detailed here provides the same utilities as the original model-quantifying the relationship between phenotypes and brain connectivity, comparing brain networks among groups, predicting brain connectivity from phenotypes, and simulating brain networks-but for local, subnetwork-level hypotheses.

Evidence suggests that trafficked persons in the United States frequently seek health care, yet little is known of their experiences, including reasons for seeking assistance, interactions with professionals, and barriers to obtaining care. To gain a better understanding, a search was conducted for empirical data collected directly from trafficked persons about their US health care experiences, published in peer-reviewed journals within the past 10 years, and in the English language. Four databases were searched and of the 1,605 articles initially identified, 8 met all inclusion criteria. Data from 420 participants demonstrated a wide range of physical and mental health complaints and 50%-98% reported seeking health care services in diverse medical settings during their exploitation. Barriers to care occurred at various levels, and although some are not modifiable, others are amendable by changes in the behaviors of professionals. A trauma-informed, rights-based approach to care would address many of these issues and create feasible treatment plans.

It has been demonstrated that wound dressings provide a protective effect against pressure injuries. However, no method exists to measure either the life or performance of dressings used in prevention; testing dressings in a clinical setting or a research environment has typically been based on measuring its moisture absorption capacity. This article examines the changes that occur in the structural and mechanical properties of a prophylactic dressing based on conditions of use when wound exudate is not present.A clinically relevant method was developed to simulate the loading, friction-inducing shear, and moisture transpiration present in a typical hospitalization where a dressing is applied for prevention. Single-use dressings were tested using this method to evaluate their ability to protect patients from pressure injuries throughout the typical 5 to 7 days of use. Following this aging process, researchers measured the physical, structural, and mechanical changes in prophylactic dressings over time.This innovative method provides guidance for clinicians on dressing use and replacement intervals. For bioengineers, the method generates important empirical data for computer modeling of dressing performance, which can then reveal the consequences of changes in dressing structure and function on sustained tissue loads. It is the authors' hope to generate discussion about the creation of industry-wide standards for testing dressings to improve patient care.

Background A critical adaptation strategy for reducing heat-related health risk under climate change is to establish a heat warning system with a proper threshold that requires evaluation of heat-health relationships using empirical data. Objectives This work presents a new approach to selecting proper health-based thresholds for a heat warning system which are different from thresholds of heat-health relationship. Methods The proposed approach examined heat-health relationships through analyzing 15 years of health records with a modified generalized additive model (GAM), compared risk ratio increments (RRIs) of threshold candidates against a reference, assessed frequency of days above these candidates, and presented results graphically for easy communication. The candidate with the maximum RRI and proper occurring frequency is potentially the best threshold. Three heat indicators, including wet-bulb globe temperature (WBGT), temperature (T), and apparent temperature (AT), as well as three health outcomes, including all-cause mortality, heat-related hospital admissions, and heat-related emergency visits were evaluated. Results Risk ratios for all three health outcomes showed a consistent rising trend with increasing threshold candidates for all three heat indicators among different age and gender groups. WBGT had the most obvious increasing trend of RRIs with the three health outcomes. The maximum RRI was observed in heat-related emergency visits (242%), followed by heat-related hospital admissions (73%), and all-cause mortality (9%). The RRIs assessed for the three health outcomes pointed to the same thresholds, 33.0 °C, 34.0 °C, and 37.5 °C for WBGT, T, and AT, respectively. The number of days above these thresholds and for warning to be issued ranged between 0 and 7 days during 2000–2014. Discussion This study demonstrated a new approach to determining heat-warning thresholds with different heat indicators and health outcomes. The proposed approach provides a straightforward, feasible, and flexible scientific tool that assists the authorities around the world in selecting a proper threshold for a heat warning system., Highlights • This work shows a new approach to select proper thresholds for heat warning systems. • Modified generalized additive model and risk ratio increments (RRIs) were applied. • Threshold of wet-bulb globe temperature (WBGT) at 33.0 °C were identified for Taiwan. • WBGT had the most obvious increasing trend of RRIs among three heat indicators. • The maximum RRI of WBGT was observed in emergency visits (242%).

Although some studies suggest a possible association between food allergy (FA) and depression/psychological distress, empirical data are still scarce. We aimed to examine whether this association exists in a large sample of the Japanese population.This web-based cross-sectional survey included 1000 individuals with self-reported lifetime history of clinical depression (mean age: 41.4 years, 501 men), and the remaining 10,876 subjects served as controls (mean age: 45.1 years, 5691 men). A six-item Kessler scale (K6) test was used to evaluate severe psychological distress. Information on FA was obtained by a self-report checking for 27 specific allergens.Participants with FA, 2 or more, 3 or more, and 4 or more allergens were more common in the depression group than in the control group (odds ratio [OR] = 1.64, 1.75, 2.02, and 2.27, respectively; p 0.001). In the allergen analyses, allergies for shrimp, egg, mackerel, crab, kiwi fruit, milk, banana, and squid (nominal, p 0.05) were more common in the depression group than in the controls. The proportion of individuals who had a K6 test cut-off score ≥ 13 was higher in the FA group than in the non-FA group, in the total sample (OR = 1.32, 1.62, 2.04 and 2.51; 1, 2, 3, and 4 or more allergens, respectively; p 0.001).The identification of FA and depression was based on self-reports.Our data suggest that FA is a risk factor for depression and severe psychological distress, which depends on the number of allergens.

Aims and objectivesTo explore the role that Donor Transplant Co‐ordinators have played and the future potential of Specialist Nurses for Organ Donation (SN‐ODs), within organ donation strategies in the UK and other countries.BackgroundOrgan donation and transplantation rates vary extensively around the world. However, there is a universal shortage of deceased donors, prompting different approaches to increase transplantation rates. Within the UK, the Clinical Lead for Organ Donation and Specialist Nurse in Organ Donation undertake a key role in the implementation of the Organ Donation Strategy. The Human Transplantation (Wales) Act 2015 is a recent development which facilities a deemed (presumed) consent approach to organ donation, the Specialist Nurse in Organ Donation undertakes a major role identifying the potential donor in this situation by confirming the deemed consent status of the donor and supporting bereaved relatives. UK governments in England and Scotland are currently seeking legislative changes to an opt‐out system of organ donation, in line with the Wales change.DesignThis discursive paper explores the role from Donor Transplant Co‐ordinator to Specialist Nurse in Organ Donation (SN‐OD) within organ donation policy in different settings, but with a specific focus on the UK. The paper clarifies the current and future potential of nurses working with bereaved families when requesting authorisation for donation.Implications for nursingThe current scope and future potential of Donor Transplant Co‐ordinator and Specialist Nurse in Organ Donation roles need better recognition. Little empirical data exist about the key role that these nurses play in the organ donation process, especially in relation to gaining authorisation to proceed to donation.ConclusionThere is a need to clarify the role of the Specialist Nurse in Organ Donation and their impact on improving rates of organ donation.

Continuous growth models show great potential for analysing cancer screening data. We recently described such a model for studying breast cancer tumour growth based on modelling tumour size at diagnosis, as a function of screening history, detection mode, and relevant patient characteristics. In this article, we describe how the approach can be extended to jointly model tumour size and number of lymph node metastases at diagnosis. We propose a new class of lymph node spread models which are biologically motivated and describe how they can be extended to incorporate random effects to allow for heterogeneity in underlying rates of spread. Our final model provides a dramatically better fit to empirical data on 1860 incident breast cancer cases than models in current use. We validate our lymph node spread model on an independent data set consisting of 3961 women diagnosed with invasive breast cancer.

Background The psychological distress caused by cancer can remain long after remission. With advanced curative treatments, many pediatric patients continue to have late complications that interfere with neurologic, physical, and social development. Objectives The aim of this article is to analyze nine published articles that focus on adolescent cancer survivors (ACSs) and the incidence and risk factors of post-traumatic stress disorder (PTSD) and post-traumatic stress symptoms (PTSSs). Methods A search of published articles including pediatric and adolescent oncology and PTSD was performed. The search was narrowed to peer-reviewed articles published after 2010 that presented empirical data and were specific to post-trauma or post-traumatic stress. Findings Significant findings for PTSD and PTSSs were reported in ACSs. ACSs suffering from PTSD and PTSSs should be identified and treated appropriately based on age, diagnosis, treatment, and comorbid symptoms.

Simulation models from the early COVID-19 pandemic highlighted the urgency of applying non-pharmaceutical interventions (NPIs), but had limited empirical data. Here we use data from 2020-2021 to retrospectively model the impact of NPIs in Ontario, Canada. Our model represents age groups and census divisions in Ontario, and is parameterised with epidemiological, testing, demographic, travel, and mobility data. The model captures how individuals adopt NPIs in response to reported cases. We compare a scenario representing NPIs introduced within Ontario (closures of workplaces/schools, reopening of schools/workplaces with NPIs in place, individual-level NPI adherence) to counterfactual scenarios wherein alternative strategies (e.g. no closures, reliance on individual NPI adherence) are adopted to ascertain the extent to which NPIs reduced cases and deaths. Combined school/workplace closure and individual NPI adoption reduced the number of deaths in the best-case scenario for the case fatality rate (CFR) from 178548 [CI: 171845, 185298] to 3190 [CI: 3095, 3290] in the Spring 2020 wave. In the Fall 2020/Winter 2021 wave, the introduction of NPIs in workplaces/schools reduced the number of deaths from 20183 [CI: 19296, 21057] to 4102 [CI: 4075, 4131]. Deaths were several times higher in the worst-case CFR scenario. Each additional 9−16 (resp. 285−578) individuals who adopted NPIs in the first wave prevented one additional infection (resp., death). Our results show that the adoption of NPIs prevented a public health catastrophe. A less comprehensive approach, employing only closures or individual-level NPI adherence, would have resulted in a large number of cases and deaths.

Objectives The objective of this review was to identify sources of variability in cost-effectiveness analyses of chimeric antigen receptor T-cell (CAR-T) therapies, tisagenlecleucel and axicabtagene ciloleucel, evaluated by health technology assessment (HTA) agencies, focusing on young compared with older patients. Methods HTA evaluations in pediatric acute lymphoblastic leukemia (ALL) and adult diffuse large B-cell lymphoma (DLBCL) were included from Australia, Canada, England, Norway, and the United States. Key clinical evidence, economic approach, and outcomes (costs, quality-adjusted life-years [QALYs] and incremental cost-effectiveness ratios) were summarized. Results Fourteen HTA evaluations were identified (5 ALL, 9 DLBCL [4 tisagenlecleucel, 5 axicabtagene]). Analyses were naive comparisons of prospective single-arm studies for the CAR-Ts with retrospective cohort studies for the comparators. Key clinical evidence and economic model approaches were generally consistent by CAR-T and indication, although outcomes varied. Notably, incremental QALYs varied substantially in ALL (3.67-10.6 QALYs gained), whereas variation in DLBCL was less (1.21-1.97 [tisagenlecleucel], 1.97-3.40 [axicabtagene]). Discounting of costs and outcomes varied, with the highest QALYs generated for tisagenlecleucel in ALL (10.95) associated with the lowest discount rate (1.5%) and vice versa (4.97 QALYs; 5% discount rate). The approach to extrapolation of overall survival data varied, even where the same empirical data were used. Conclusion Modeled, long-term treatment benefit in young patients may be associated with greater uncertainty compared with adults because of potential life-long benefits with cell and gene therapies. This reflects the methodological challenges identified by HTA agencies associated with single-arm, short-term studies.

Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems involving more than a handful of sequences, inference under the maximum-likelihood paradigm integrates heuristic approaches to evaluate only a subset of all potential trees. Consequently, existing methods suffer from the known tradeoff between accuracy and running time. In this proof-of-concept study, we train a machine-learning algorithm over an extensive cohort of empirical data to predict the neighboring trees that increase the likelihood, without actually computing their likelihood. This provides means to safely discard a large set of the search space, thus potentially accelerating heuristic tree searches without losing accuracy. Our analyses suggest that machine learning can guide tree-search methodologies towards the most promising candidate trees., Likelihood optimization in phylogenetic tree reconstruction is computationally intensive, especially as the number of sequences and taxa included increase. Here, Azouri et al. show how an artificial intelligence approach can reduce computational time without losing accuracy of tree inference.

AIM The aim of this study was to describe changes in the anthropometric and motor characteristics of female students attending the University of Warmia and Mazury in Olsztyn between 2000 and 2018. MATERIALS AND METHODS A total of 4046 randomly selected female university students aged 19-21 years (20.1 ± 1.2) were investigated. The students' body mass and height were measured, and their motor abilities were analyzed in 13 tests. Linear and curvilinear functions were fit to empirical data to assess the evaluated traits. RESULTS The results of the long-term study indicate that the body height of female students increased by 3.07 cm between 2000 and 2018. A decrease in the participants' body mass and BMI was noted between 2000 and 2006 (by 0.24 kg and 0.18 kg/m2 per year on average), whereas an increase was observed between 2006 and 2018 (by 0.34 kg and 0.10 kg/m2 per year on average). The tested motor abilities were highly correlated with body mass, BMI and, partially, with body height. The students' motor abilities continued to improve until 2006, after which they declined steadily up to 2018 when the lowest results were noted in motor tests. CONCLUSIONS The body height of the studied population continued to increase over the years, but it increased at a slower rate than body mass and BMI. Lower body mass and BMI values were correlated with improved scores in motor tests, whereas higher values of both parameters were accompanied by a significant decrease in all analyzed motor abilities.

Background: Healthcare chaplains have key roles in providing palliative support to patients and families, and they are well-suited to facilitate advance care planning (ACP). However, empirical data on the roles and responsibilities of chaplains in facilitating ACP are limited. Objectives: To examine the roles of board-certified healthcare chaplains in ACP in various healthcare settings. Methods: A cross-sectional, web-based self-report survey was conducted with 585 board-certified chaplains recruited from 3 major professional chaplains’ organizations in the U.S. The survey data included chaplains’ demographic and professional characteristics, their roles and responsibilities, and responses regarding communication and participation with other healthcare team members in facilitating ACP, including experienced barriers. Results: More participants worked in community hospital settings (42%) and academic medical centers (19.6%) than in any other setting. Over 90% viewed ACP as an important part of their work, 70% helped patients complete advance directives, and 90% helped patients discuss their preferences about end-of-life treatments. Many chaplains were not consistently included in team discussions regarding decision-making, although most chaplains reported that they could always find ways to communicate with their teams. Conclusion: Professional board-certified chaplains regularly engage in facilitating ACP discussions with patients and families in various healthcare settings. There is a need to recognize and provide systematic support for the role of chaplains in facilitating ACP conversations and to integrate chaplains into routine interdisciplinary team and family meetings.

This study offers rare empirical data and insight about the experiences of women who use and sell drugs in China and their participation in the drug economy. Drug selling is traditionally viewed as a male job in China and commonly overlaps with drug use practices. While this largely male-dominated economy has been widely documented, very little is known about the experiences of women. Drawing on interviews with twelve women, this exploratory study aims to shed light on the lives and experiences of women who use and sell drugs in China. Findings indicate that for study participants, entering into the drug selling economy was primarily driven by motives of maintaining their own drug use. Our analysis also shows that participants kept their drug selling within limited social circles. Instead of seeking to make large profits, they often aimed to “help friends” and secure drugs for their own use. Women who sold drugs in our study usually affiliated themselves with their male partners, often purposefully utilizing feminine characteristics and practices to serve gendered roles in drug selling. In doing so, this paper brings to light the gendered nature of drug selling practices and drug market relations in China and more broadly.

During the first wave of the Covid-19 pandemic, access to health care was limited, and patients encountered important delays for scheduled appointments and care. Empirical data relying on patients' reports of forgoing health care are scarce. This study investigated Covid-19-related self-reports of forgoing health care in a sample of vulnerable outpatients in Geneva, Switzerland. We collected data from 1167 adult outpatients, including clinically vulnerable patients (with chronic diseases), geriatric patients (involved in a health care network for people aged 60 or older), and socially vulnerable patients (involved in a migrant health program or a mobile outpatient community care center) in June 2020. Data on sociodemographic factors, forgoing health care, and anti-SARS-CoV-2 antibodies were collected. Of the patients, 38.5% reported forgoing health care. Forgoing health care was more frequent for younger patients, women, patients with a low level of education, and patients with a chronic disease (p, Preventive Medicine, 150

The high prevalence of chronic sleep restriction in adolescents underscores the importance of understanding how adolescent sleep is regulated under such conditions. One component of sleep regulation is a homeostatic process: if sleep is restricted, then sleep intensity increases. Our knowledge of this process is primarily informed by total sleep deprivation studies and has been incorporated in mathematical models of human sleep regulation. Several animal studies, however, suggest that adaptation occurs in chronic sleep restriction conditions, showing an attenuated or even decreased homeostatic response. We investigated the homeostatic response of adolescents to different sleep opportunities. Thirty-four participants were allocated to one of three groups with 5, 7.5, or 10 h of sleep opportunity per night for five nights. Each group underwent a protocol of nine nights designed to mimic a school week between two weekends: two baseline nights (10 h sleep opportunity), five condition nights (5, 7.5, or 10 h), and two recovery nights (10 h). Measures of sleep homeostasis (slow-wave activity and slow-wave energy) were calculated from frontal and central EEG derivations and compared to predictions derived from simulations of the homeostatic process of the two-process model of sleep regulation. Only minor differences were found between empirical data and model predictions, indicating that sleep homeostasis is preserved under chronic sleep restriction in adolescents. These findings improve our understanding of effects of repetitive short sleep in adolescents.

Knowledge about the therapeutic potential of medical cannabis has greatly improved over the past decade, with an ever-increasing range of developments in human clinical applications. A growing body of scientific evidence supports the use of medical cannabis products for some therapeutic indications, whilst for others, the evidence base remains disputed. For this narrative review, we incorporate areas where the current evidence base is substantial, such as intractable childhood epilepsy and multiple sclerosis, as well as areas where the evidence is still controversial, such as PTSD and anxiety. We provide a high-level summary of current developments using findings from recent major reviews, as well as real world evidence (RWE), including global database registries and other patient reported outcomes (PROs). On the one hand, our strongest empirical data supports the use of cannabis-based medicinal products (CBMPs) for conditions with relatively small patient numbers. Yet on the other hand, the conditions, where the highest patient numbers present, often have debatable clinical evidence but good RWE, incorporating PROs of 1000s of patients. The discord between PROs and the respective strength of the evidence from randomised controlled trials (RCTs) highlights the urgent need for further research. The scientific literature examining the efficacy of medical cannabis for many conditions is still developing, whilst large numbers of patients globally have been successfully using medical cannabis to treat a broad range of conditions. We conclude on the importance of systematically developing RWE databases to supplement RCTs and to bridge the current evidence gaps.

The authors conducted a review of the literature of cost-effectiveness analyses regarding management of Barrett's esophagus, including screening, surveillance, and treatment strategies. Because of the presence of multiple systematic reviews on this topic, they chose to focus on more recent economic analyses, with an emphasis on comparative modeling because these analyses have been demonstrated to achieve greater validity and impact when there are multiple competing strategies that are clinically reasonable to pursue. The authors identified areas of consensus across studies regarding management strategies and also areas that require additional empirical data.

Prostate cancer is a common cancer among males in the USA and is often treated by intermittent androgen deprivation therapy. This therapy requires a patient to alternate between periods of androgen suppression treatment and no treatment. Prostate-specific antigen levels are used to track relative changes in tumor volume of prostate cancer patients undergoing intermittent androgen deprivation therapy. During this therapy, there is a pause between treatment cycles. Traditionally, continuous ordinary differential equations are used to estimate prostate-specific antigen levels. In this paper, we use dynamic equations to estimate prostate-specific antigen levels and construct a novel time scale model to account for both continuous and discrete time simultaneously. This allows us to account for breaks between treatment cycles. Using empirical data sets of prostate-specific antigen levels, a known bio-marker of prostate cancer, across multiple patients, we fit our model and use least squares to estimate two parameter values. We then compare our model to the data and find a resemblance on treatment intervals similar to our time scale.

This article updates a 2006 review of empirical data concerning whether clinicians can predict whether patients will die by suicide, or whether fatality can be prevented. Based on further empirical data, a negative conclusion remains justified. There is good evidence that treatment programs, using psychotherapy and medication, can reduce suicide attempts. But people who die by suicide are a distinct population from attempters, and those at high risk do not necessarily present for treatment. Research on suicide prevention has not shown that fatalities among patients can be predicted, or that clinical interventions can reduce the risk. The strongest evidence for prevention derives from reducing access to means. Population-based strategies are more effective than high-risk strategies focusing on patients with suicidal ideas or attempts.

INTRODUCTION: Childhood immunization schedules often involve multiple vaccinations per visit. When increased risk of an adverse event is observed after simultaneous (same-day) vaccinations, it can be difficult to ascertain which triggered the adverse event. This methods paper discusses a systematic process to determine which of the simultaneously administered vaccine(s) are most likely to have caused an observed increase in risk of an adverse event. METHODS: We use an example from the literature where excess risk of seizure was observed one day after vaccination, but same-day vaccination patterns made it difficult to discern which vaccine(s) may trigger the adverse event. We illustrate the systematic identification process using a simulation that retained the observed pattern of simultaneous vaccination in an empirical cohort of vaccinated children. We simulated “true” effects for diphtheria-tetanus-acellular pertussis (DTaP) and pneumococcal conjugate (PCV) on risk of seizure the day after vaccination. We varied the independent and interactive effects of vaccines (on the multiplicative scale). After applying the process to simulated data, we evaluated risk of seizure one day after vaccination in the empirical cohort. RESULTS: In all simulations, we were able to determine which vaccines contributed to excess risk. In empirical data, we narrowed the association with seizure from all vaccines in the schedule to three likely candidates, DTaP, PCV, and/or Haemophilus influenzae type B (HiB) (p < 0.01, attributable risk when all 3 were administered together: 5 per 100,000). Disentangling their associations with seizure would require a larger sample or more variation in the combinations administered. When none of these three were administered, no excess risk was observed. CONCLUSION: The process outlined could provide valuable information on the magnitude of potential risk from individual and simultaneous vaccinations. Associations should be further investigated with independent data as well as biologically based, statistically independent hypotheses.