Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples.

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

Characteristic of clinical trials related to traumatic brain injury registered on ClinicalTrials.gov over the past two decades (2004-2023).

Objective: The aim of this report is to provide a comprehensive overview of clinical trials and protocols related to traumatic brain injury over the past two decades. Methods: We collected information on clinical trials related to traumatic brain injury (TBI) from the ClinicalTrials.gov database, identified key categorical variables, and assessed their characteristics. Results: A total of 367 TBI-related trials were identified for analysis. All identified trials were interventional clinical trials. Most trials were small-scale, with 75.2% enrolling 1-100 participants, and only about 20% were funded by industry or the National Institutes of Health (NIH). In most trials, participants were gender-neutral (96.5%), and the primary age group was adults and older adults (56.9%). Of all identified TBI trials, 78.2% were randomized, and 69.4% were blinded. Additionally, the primary purpose of 297 trials (80.9%) was treatment, with drug therapy as the most common intervention. A total of 153 trials (41.7%) were completed; however, only 58 trials submitted results to the registry. Furthermore, 81 trials (22.1%) were discontinued early, primarily due to recruitment problems. Clinical trials started between 2004 and 2013 reported a higher proportion of results compared with those started between 2014 and 2023 (35.1% vs. 11.1%, p < 0.001). In addition, between 2014 and 2023, there was an increase in trials for diagnostic purposes (2.4% vs. 6.5%, p < 0.001). Conclusion: Based on the data collected from the ClinicalTrials.gov, our study reveals that most clinical trials related to TBI focus on drug-related treatments, underreporting remains a significant concern, and greater emphasis should be placed on improving the publication and dissemination of clinical trial results.

The Danish National Health Survey 2023: study design and participant characteristics.

AIM: To describe the design of the Danish National Health Survey (DNHS) 2023, participants' demographic characteristics and differences in demographic and selected health-related characteristics between respondents invited by web-mode and paper-mode. METHODS: A sample of 25,000 residents in Denmark aged 16 years or above was invited to participate in the DNHS 2023 using a mixed-mode approach (web/paper mode). Web-mode invited were additionally invited to participate in an accelerometer study. The self-administered questionnaire included 83 questions about health, health behaviour and morbidity. Descriptive statistics were used to describe characteristics associated with response and invitation mode. RESULTS: The response proportion was 40.8%. Non-response was more frequent among men, individuals of the youngest age groups, individuals with non-Western backgrounds, unmarried and individuals from densely populated areas. The response proportion was higher among web-mode invited (42.0%) than paper-mode invited (22.6%). Paper-mode invited respondents were more often women, aged 80 years or older, and widowed compared with web-mode invited respondents. CONCLUSIONS: The DNHS 2023 is a national health survey including adult residents in Denmark. Non-response was more pronounced among some subgroups; however, calibrated weights were calculated to minimise non-response bias. The survey is essential for public health surveillance and can be used in health planning and policy development. Furthermore, the data from the survey can be used for research on the population's health and health behaviour. For future waves of the DNHS, it should be considered whether resources should be used to invite people unsubscribed from digital-post due to the low response proportion.

The association between study design and antidepressant effects in psychedelic-assisted therapy: A meta-analysis.

Different study designs of psychedelic trials may impact the blinding and expectance, leading to biased treatment effects. This study aimed to examine the association between antidepressant efficacy and study designs in psychedelic trials. Six databases were systematically searched. Eligible trials were required to investigate the efficacy of psychedelics (psilocybin, lysergic acid diethylamide [LSD], 3,4-Methylenedioxymethamphetamine [MDMA], and ayahuasca) in adult patients with depressive symptoms. We only considered oral psychedelic-assisted therapy without concomitant use of antidepressants. The primary outcome was the change in depressive symptoms. There were five study designs of psychedelic trials, including non-active-drug-as-placebo, active-drug-as-placebo, waitlist-as-control, fixed-order, and pre-post designs. In non-active-drug -as-placebo design, psilocybin (k = 4, Hedges' g [g] = 0.87, 95 % confidence intervals[CIs] = 0.58 to 1.16) and MDMA (k = 2, g = 0.65, 95%CIs = 0.26 to 1.05) were associated with large and medium effect sizes, respectively. In active-drug-as-placebo design, both psilocybin (k = 2, g = 0.71, 95%CIs = -0.01 to 1.43) and MDMA (k = 3, g = 0.53, 95%CIs = -0.23 to 1.28) were not statistically significant. In pre-post single-arm (k = 3, g = 2.51, 95%CIs = 1.00 to 4.02) and waitlist-as-control (k = 1, g = 2.88, 95%CIs = 1.75 to 4.00) designs, psilocybin showed a large effect size of antidepressant effect. Ayahuasca also showed a large effect size in both pre-post (k = 2, g = 1.88, 95%CIs = 1.18 to 2.57) and non-active-drug-as-placebo (k = 1, g = 1.60, 95%CIs = 0.84 to 2.36) designs. LSD was associated with a significant antidepressant effect only in non-active-drug-as-placebo design (k = 1, g = 1.49, 95%CIs = 0.80 to 2.17) but not in active-drug-as-placebo design (k = 1, g = 0.44, 95%CIs = -0.90 to 1.78). The antidepressant effects of psychedelics may be overestimated in studies with pre-post single-arm, non-active-drugs-as placebo, and waitlist-control designs. Restricted sample size, difficulty with establishing blinding for participants, and over expectancy limit the estimation of the antidepressant effect of psychedelic-assisted therapy.

Heterogeneity of animal experiments and how to deal with it.

Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable.

Machine learning-based prediction of early neurological deterioration after intravenous thrombolysis for stroke: insights from a large multicenter study.

Background: This investigation seeks to ascertain the efficacy of various machine learning models in forecasting early neurological deterioration (END) following thrombolysis in patients with acute ischemic stroke (AIS). Methods: Employing data from the Shenyang Stroke Emergency Map database, this multicenter study compiled information on 7,570 AIS patients from 29 comprehensive hospitals who received thrombolytic therapy between January 2019 and December 2021. An independent testing cohort was constituted from 2,046 patients at the First People's Hospital of Shenyang. The dataset incorporated 15 pertinent clinical and therapeutic variables. The principal outcome assessed was the occurrence of END post-thrombolysis. Model development was executed using an 80/20 split for training and internal validation, employing classifiers like logistic regression with lasso regularization (lasso regression), support vector machine (SVM), random forest (RF), gradient-boosted decision tree (GBDT), and multi-layer perceptron (MLP). The model with the highest area under the curve (AUC) was utilized to delineate feature significance. Results: Baseline characteristics showed variability in END incidence between the training (n = 7,570; END incidence 22%) and external validation cohorts (n = 2,046; END incidence 10%; p < 0.001). Notably, all machine learning models demonstrated superior AUC values compared to the reference model, indicating their enhanced predictive capacity. The lasso regression model achieved the highest AUC at 0.829 (95% CI: 0.799-0.86; p < 0.001), closely followed by the MLP model with an AUC of 0.828 (95% CI: 0.799-0.858; p < 0.001). The SVM, RF, and GBDT models also showed commendable AUCs of 0.753, 0.797, and 0.774, respectively. Decision curve analysis revealed that the SVM and MLP models demonstrated a high net benefit. Feature importance analysis emphasized "Onset To Needle Time" and "Admission NIHSS Score" as significant predictors. Conclusion: Our research establishes the MLP and lasso regression as robust tools for predicting early neurological deterioration in acute ischemic stroke patients following thrombolysis. Their superior predictive accuracy, compared to traditional models, highlights the significant potential of machine learning approaches in refining prognosis and enhancing clinical decisions in stroke care management. This advancement paves the way for more tailored therapeutic strategies, ultimately aiming to improve patient outcomes in clinical practice.

Expert opinion on design and endpoints for studies on catheter ablation of atrial fibrillation.

INTRODUCTION: Catheter ablation of atrial fibrillation (AF) is frequently studied in randomized trials, observational and registry studies. The aim of this expert opinion is to provide guidance for clinicians and industry regarding the development of future clinical studies on catheter ablation of AF, implement lessons learned from previous studies, and promote a higher degree of consistency across studies. BACKGROUND: Studies on catheter ablation of AF may benefit from well-described definitions of endpoints and consistent methodology and documentation of outcomes related to efficacy, safety and cost-effectiveness. The availably of new, innovative technologies warrants further consideration about their application and impact on study design and the choice of endpoints. Moreover, recent insights gained from AF ablation studies suggest a reconsideration of some methodological aspects. METHODS: A panel of clinical experts on catheter ablation of AF and designing and conducting clinical studies developed an expert opinion on the design and endpoints for studies on catheter ablation of AF. Discussions within the expert panel with the aim to reach consensus on predefined topics were based on outcomes reported in the literature and experiences from recent clinical trials. RESULTS: A comprehensive set of recommendations is presented. Key elements include the documentation of clinical AF, medication during the study, repeated ablations and their effect on endpoint assessments, postablation blanking and the choice of rhythm-related and other endpoints. CONCLUSION: This expert opinion provides guidance and promotes consistency regarding design of AF catheter ablation studies and identified aspects requiring further research to optimize study design and methodology. CONDENSED ABSTRACT: Recent insights from studies on catheter ablation of atrial fibrillation (AF) and the availability of new innovative technologies warrant reconsideration of methodological aspects related to study design and the choice and assessment of endpoints. This expert opinion, developed by clinical experts on catheter ablation of AF provides a comprehensive set of recommendations related to these methodological aspects. The aim of this expert opinion is to provide guidance for clinicians and industry regarding the development of clinical studies, implement lessons learned from previous studies, and promote a higher degree of consistency across studies.

Prepared for the polycrisis? The need for complexity science and systems thinking to address global and national evidence gaps.

The Sustainable Development Goals are far off track. The convergence of global threats such as climate change, conflict and the lasting effects of the COVID-19 pandemic-among others-call for better data and research evidence that can account for the complex interactions between these threats. In the time of polycrisis, global and national-level data and research evidence must address complexity. Viewed through the lens of 'systemic risk', there is a need for data and research evidence that is sufficiently representative of the multiple interdependencies of global threats. Instead, current global published literature seems to be dominated by correlational, descriptive studies that are unable to account for complex interactions. The literature is geographically limited and rarely from countries facing severe polycrisis threats. As a result, country guidance fails to treat these threats interdependently. Applied systems thinking can offer more diverse research methods that are able to generate complex evidence. This is achievable through more participatory processes that will assist stakeholders in defining system boundaries and behaviours. Additionally, applied systems thinking can draw on known methods for hypothesising, modelling, visualising and testing complex system properties over time. Application is much needed for generating evidence at the global level and within national-level policy processes and structures.

The impact of a nurse's dual role on implementing an effectiveness study.

BACKGROUND: Reorganizing the Approach to Diabetes through the Application of Registries (RADAR) improved diabetes care and outcomes for First Nations people in Alberta, Canada. The nurse involved in the implementation of RADAR performed two roles in this model of care: research nurse and care coordinator. AIM: To describe the research nurse's dual role in the implementation and evaluation of RADAR. DISCUSSION: The research nurse not only documented and collected data in hard-to-reach communities as part of effective research, she also provided remote care coordination to support community healthcare providers using a culturally tailored registry to facilitate population-level care. This dual role required many qualities of nursing leadership and transformation. CONCLUSION: The research nurse's two roles contributed to the success of the intervention and were critical to the successful implementation of the model, creating valuable real-world evidence across diverse populations and settings. IMPLICATIONS: for practice Nurses are well placed to perform research duties alongside engagement and implementation activities. This can enhance the effectiveness and evaluation of healthcare interventions, particularly in community-based interventions within First Nations communities.

Advancing collaborative research for health: why does collaboration matter?

The calls for health research to be collaborative are ubiquitous-even as part of a recent World Health Assembly resolution on clinical trials-yet the arguments in support of collaborative research have been taken for granted and are absent in the literature. This article provides three arguments to justify why health research ought to be collaborative and discusses trade-offs to be considered among the ethical values guiding each argument.

How to Conduct Clinical Research in Cardiovascular Imaging: A Primer for Clinical Cardiologists and Researchers. A Statement of the European Association of Cardiovascular Imaging (EACVI) of the ESC.

This statement from the European Association of Cardiovascular Imaging (EACVI) of the ESC aims to address the fundamental principles that guide clinical research in the field of cardiovascular imaging. It provides clinical researchers, cardiology fellows, and Ph.D. students with a condensed, updated, and practical reference document to support them in designing, implementing, and conducting imaging protocols for clinical trials. Although the present article cannot replace formal research training and mentoring, it is recommended reading for any professional interested in becoming acquainted with or participating in clinical trials involving cardiovascular imaging.

Multilevel Longitudinal Functional Principal Component Model.

Sensor devices, such as accelerometers, are widely used for measuring physical activity (PA). These devices provide outputs at fine granularity (e.g., 10-100 Hz or minute-level), which while providing rich data on activity patterns, also pose computational challenges with multilevel densely sampled data, resulting in PA records that are measured continuously across multiple days and visits. On the other hand, a scalar health outcome (e.g., BMI) is usually observed only at the individual or visit level. This leads to a discrepancy in numbers of nested levels between the predictors (PA) and outcomes, raising analytic challenges. To address this issue, we proposed a multilevel longitudinal functional principal component analysis (mLFPCA) model to directly model multilevel functional PA inputs in a longitudinal study, and then implemented a longitudinal functional principal component regression (FPCR) to explore the association between PA and obesity-related health outcomes. Additionally, we conducted a comprehensive simulation study to examine the impact of imbalanced multilevel data on both mLFPCA and FPCR performance and offer guidelines for selecting optimal methods.

The Healthy User Effect in Pharmacoepidemiology.

The healthy user effect is a well-recognized bias in the field of pharmacoepidemiology and can be expected to overstate the effect of a preventive intervention when comparing long term users or "adherers" to non-users. Similar to the healthy worker effect observed in occupational epidemiology, the healthy user effect can be separated into a healthy initiator effect (baseline confounding) and a healthy adherer effect (selection bias). Restriction approaches and new user designs that implicitly condition on the indication and, similar healthy behaviors or health status can often mitigate the healthy initiator effect (confounding) or healthy adherer effect (selection bias) at the start of a study. Addressing the healthy adherer effect due to continued conditioning on adherence over the duration of a study is more challenging as methods to mitigate it require the ability to predict adherence, which is often difficult using databases common in pharmacoepidemiologic research. Here, we describe the healthy user effect, with supporting examples, and describe study design approaches available to pharmacoepidemiologists to mitigate the potential for bias.

Power analyses to inform Duplex Sequencing study designs for MutaMouse liver and bone marrow.

Regulatory genetic toxicology testing is essential for identifying potentially mutagenic hazards. Duplex Sequencing (DS) is an error-corrected next-generation sequencing technology that provides substantial advantages for mutation analysis over conventional mutagenicity assays including: improved accuracy of mutation detection, ability to measure changes in mutation spectrum, and applicability across diverse biological models. To apply DS for regulatory toxicology testing, power analyses are required to determine suitable sample sizes and study designs. In this study, we explored study designs to achieve sufficient power for various effect sizes in chemical mutagenicity assessment. We collected data from MutaMouse bone marrow and liver samples that were analyzed by DS using TwinStrand's Mouse Mutagenesis Panel. Average duplex reads achieved in two separates studies on liver and bone marrow were 8.4 × 108 (± 7.4 × 107) and 9.5 × 108 (± 1.0 × 108), respectively. Baseline mean mutation frequencies (MF) were 4.6 × 10-8 (± 6.7 × 10-9) and 4.6 × 10-8 (± 1.1 × 10-8), with estimated standard deviations for the animal-to-animal random effect of 0.15 and 0.20, for liver and bone marrow, respectively. We conducted simulation analyses based on these empirically derived parameters. We found that a sample size of four animals per group is sufficient to obtain over 80% power to detect a two-fold change in MF relative to baseline. In addition, we estimated the minimal total number of informative duplex bases sequenced with different sample sizes required to retain power for various effect sizes. Our work provides foundational data for establishing suitable study designs for mutagenicity testing using DS.

Generating the Evidence Base for Convalescent Plasma Use for a New Infectious Disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) swept across the world in the waning months of 2019 and emerged as the cause of the coronavirus disease 19 (COVID-19) pandemic in early 2020. The use of convalescent plasma (CP) for prior respiratory pandemics provided a strong biological rationale for the rapid deployment of COVID-19 convalescent plasma (CCP) in early 2020 when no validated treatments or prior immunity existed. CCP is an antiviral agent, with its activity against SARS-CoV-2 stemming from specific antibodies elicited by the virus. Early efforts to investigate the efficacy of CCP in randomized clinical trials (RCTs) that targeted hospitalized patients with COVID-19 did not demonstrate the overall efficacy of CCP despite signals of benefit in certain subgroups, such as those treated earlier in disease. In contrast, studies adhering to the principles of antibody therapy in their study design, choice of patient population, and product qualification, i.e., those that administered high levels of specific antibody during the viral phase of disease in immunocompromised or very early in immunocompetent individuals, demonstrated benefits. In this chapter, we leverage the knowledge gained from clinical studies of CCP for COVID-19 to propose a framework for future studies of CP for a new infectious disease. This framework includes obtaining high-quality CP and designing clinical studies that adhere to the principles of antibody therapy to generate a robust evidence base for using CP.

Best practices for recruitment in veterinary clinical trials.

A successful clinical trial requires participants, but many factors can impede effective study recruitment. To better recruit for quality veterinary clinical trials in client-owned animals that lead to improved evidence-based patient care and outcomes, there is a collective need to share and implement current best practices for recruitment strategies. These strategies should utilize a holistic view of recruitment, encompassing study design and logistics, representative participation, incentives, personnel resources, advertising, and participant retention. Although human clinical trial data and resources can provide guidance, effort also needs to be put into evaluating current practices and opportunities for process improvement that are specific to the conduct of veterinary clinical trials. Considering the power of pets as naturally occurring models of disease and as sentinels, improved conduct of veterinary clinical research has the potential to inform human health outcomes. Continued development of collaborations surrounding best practices and training opportunities in veterinary clinical research will improve the impact of veterinary clinical trials teams, while also promoting workforce development and alternate career paths for veterinary professionals.

Articles Published in Korean Journal of Family Medicine: Impact of COVID-19 on Study Trends.

Background: The Korean Journal of Family Medicine (KJFM), which is an official journal of the Korean Academy of Family Medicine, is an English-text medical journal published since 2009. Although nearly 15 years have passed since the journal was launched, to the best of our knowledge, no study has reviewed articles published in the KJFM. Accordingly, we analyzed articles published in the KJFM for the first time. Methods: Articles published in the KJFM between January 2018 and November 2023 were categorized according to article type. Information about author affiliations, study subjects, research methods, and modes of data collection was then scrutinized. Moreover, we compared the frequencies of subjects, research methods and modes of data collection before, during, and after the coronavirus disease 2019 pandemic. Results: Original article was the most common article type. Approximately 52% of the articles were published by authors affiliated with departments other than family medicine, and 40% were published by family medicine. Approximately 60% and 38% of the articles were published by Korean authors and authors of international affiliations, respectively. Throughout the pandemic periods, research subjects focusing on "diseases & symptoms" have diminished, while "principles of family medicine" have progressively increased. Additionally, the use of cross-sectional study methods has declined. In terms of data collection, the use of "big data," "medical records," and "questionnaires" has decreased, whereas the use of "study results" has increased. Conclusion: KJFM is journal with wide and international participation covering various research subjects and study methods. We believe that our study provides valuable data for the future direction and development of the KJFM.

Reflections on the study of empathy in a sample of refugees and migrants from Arabic-speaking countries with diverse experiences of war-related trauma.

Empathic abilities are proposed to affect the trajectory from trauma exposure to psychopathology. Yet, studies addressing the role of empathy in refugees with diverse experiences of war-related trauma are lacking. This may relate to missing recommendations on aspects to consider in the planning and execution of such a study. In the present methodological paper, we hence share our experiences in designing and implementing a study on the interrelations of war-related trauma, post-traumatic stress disorder, and empathy in individuals from Arabic-speaking countries who had entered Germany as refugees or migrants. In specific, we reflect on decisions related to the choice of experimental groups and measures of empathy, and describe unanticipated problems encountered during recruitment, screening and testing. Overall, we recommend applying a multi-method approach (i.e., a combination of questionnaire, behavioral and biological measures) to gain a comprehensive picture of the different facets of empathy. Further, we stress the importance to consider that not only refugees, but also migrants may have experienced war-related trauma. Beyond that, we advise to consult individuals of the study population of interest for the translation of instruments, realization of effective recruitment strategies, and to ensure that the testing procedures are sensitive to participants' past experiences and current needs. We hope that sharing these insights will benefit researchers interested in conducting basic and intervention research aimed at improving the mental health of individuals exposed to war-related trauma.

Long-term retention and positive deviant practices in Uganda's community client-led antiretroviral distribution groups (CCLADs): a mixed-methods study.

BACKGROUND: HIV testing and starting antiretroviral therapy (ART) are pivotal in treating people living with HIV (PLHIV) but sustaining PLHIV on treatment remains challenging. We assessed retention and attrition in community client-led antiretroviral distribution groups (CCLADs) in Uganda and identified positive deviant practices that foster long-term retention. METHODS: Using explanatory mixed methods, we collected longitudinal medical data from 65 health facilities across 12 districts in East Central Uganda. Quantitative phase, from 18 April 2021 to 30 May 2021, employed survival analysis and Cox regression to assess retention and identify attrition risk factors. Qualitative inquiry focused on four districts with high attrition from 11 August 2021 to 20 September 2021, where we identified nine health facilities exhibiting high retention in CCLADs. We purposively selected 50 clients for in-depth interviews (n=22) or focus group discussions (n=28). Using thematic analysis, we identified positive deviant practices. We integrated quantitative and qualitative findings into joint displays. RESULTS: Involving 3055 PLHIV, the study showed retention rates of 97.5% at 6 months, declining to 89.7% at 96 months. Attrition risk factors were lower levels of care (health centre three (adjusted HR (aHR) 2.80, 95% CI 2.00 to 3.65) and health centre four (aHR 3.61, 95% CI 2.35 to 5.54)); being unemployed (aHR 2.21, 95% CI 1.00 to 4.84); enrolment year into CCLAD (aHR 23.93, 95% CI 4.66 to 123.05) and virological failure (aHR 3.41, 95% CI 2.51 to 4.63). Of 22 clients interviewed, 8 were positive deviants. Positive deviants were characterised by prolonged retention in CCLADs, improved clinical outcomes and practised uncommon behaviours that enabled them to find better solutions than their peers. Positive deviant practices included fostering family-like settings, offering financial or self-development advice, and promoting healthy lifestyles. CONCLUSIONS: Findings underscore the importance of addressing factors contributing to attrition and leveraging positive deviant practices to optimise retention and long-term engagement in HIV care.