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Birth-death models are stochastic processes describing speciation and extinction through time and across taxa, and are widely used in biology for inference of evolutionary timescales. Previous research has highlighted how the expected trees under the constant-rate birth-death (crBD) model tend to differ from empirical trees, for example with respect to the amount of phylogenetic imbalance. However, our understanding of how trees differ between the crBD model and the signal in empirical data remains incomplete. In this Point of View, we aim to expose the degree to which the crBD model differs from empirically inferred phylogenies and test the limits of the model in practice. Using a wide range of topology indices to compare crBD expectations against a comprehensive dataset of 1189 empirically estimated trees, we confirm that crBD model trees frequently differ topologically compared with empirical trees. To place this in the context of standard practice in the field, we conducted a meta-analysis for a subset of the empirical studies. When comparing studies that used Bayesian methods and crBD priors with those that used other non-crBD priors and non-Bayesian methods (i.e., maximum likelihood methods), we do not find any significant differences in tree topology inferences. To scrutinize this finding for the case of highly imbalanced trees, we selected the 100 trees with the greatest imbalance from our dataset, simulated sequence data for these tree topologies under various evolutionary rates, and re-inferred the trees under maximum likelihood and using the crBD model in a Bayesian setting. We find that when the substitution rate is low, the crBD prior results in overly balanced trees, but the tendency is negligible when substitution rates are sufficiently high. Overall, our findings demonstrate the general robustness of crBD priors across a broad range of phylogenetic inference scenarios, but also highlights that empirically observed phylogenetic imbalance is highly

Despite the escalating burden of antimicrobial resistance (AMR), the global response has not sufficiently matched the scale and scope of the issue, especially in low- and middle-income countries (LMICs). While many countries have adopted national action plans to combat AMR, their implementation has lagged due to resource constraints, dysfunctional multisectoral coordination mechanisms and, importantly, an under-recognized lack of technical capacity to adapt evidence-based AMR mitigation interventions to local contexts. AMR interventions should be tailored, context-specific, cost-effective and sustainable. The implementation and subsequent scale-up of these interventions require multidisciplinary intervention-implementation research (IIR). IIR involves both quantitative and qualitative approaches, occurs across a three-phase continuum (proof of concept, proof of implementation and informing scale-up), and across four context domains (inner setting, outer setting, stakeholders and the implementation process). We describe the theoretical underpinnings of implementation research (IR), its various components, and how to construct different IR strategies to facilitate sustainable uptake of AMR interventions. Additionally, we provide real-world examples of AMR strategies and interventions to demonstrate these principles in practice. IR provides a practical framework to implement evidence-based and sustainable AMR mitigation interventions., Despite the escalating burden of antimicrobial resistance (AMR), the global response has not sufficiently matched the scale and scope of the issue, especially in low- and middle-income countries (LMICs). While many countries have adopted national action plans to combat AMR, their implementation has lagged due to resource constraints, dysfunctional multisectoral coordination mechanisms and, importantly, an under-recognized lack of technical capacity to adapt evidence-based AMR mitigation interventions to local contexts. AMR interventions should be tailored, context-specific, cost-effective and sustainable. The implementation and subsequent scale-up of these interventions require multidisciplinary intervention-implementation research (IIR). IIR involves both quantitative and qualitative approaches, occurs across a three-phase continuum (proof of concept, proof of implementation and informing scale-up), and across four context domains (inner setting, outer setting, stakeholders and the implementation process). We describe the theoretical underpinnings of implementation research (IR), its various components, and how to construct different IR strategies to facilitate sustainable uptake of AMR interventions. Additionally, we provide real-world examples of AMR strategies and interventions to demonstrate these principles in practice. IR provides a practical framework to implement evidence-based and sustainable AMR mitigation interventions.

Evidence suggests that a certain degree of clustering and narrowing of research trajectories is occurring, both on the individual and disease levels. Mechanisms of this process include biases in funding, a lack of coordination among funders, the significant funding role of for-profit actors, and lobbying by special interest groups. The implication is that fewer individuals might control the direction of research and certain diseases could garner a disproportionate amount of attention and resources, which could be an epistemic threat to medical progress. In this perspective article, we highlight the scale of the issue, mechanisms underlying this process, and their effects on medical progress. The article also explores potential solutions to counteract an excessive narrowing and clustering, highlighting the importance of individual researchers, patients, research organizations, and funders in ensuring that a sufficiently-diverse set of medical research trajectories are being pursued.

INTRODUCTION: In order to fulfill the enormous potential of digital health in the healthcare sector, digital health must become an integrated part of medical education. We aimed to investigate which knowledge, skills and attitudes should be included in a digital health curriculum for medical students through a scoping review and Delphi method study.METHODS: We conducted a scoping review of the literature on digital health relevant for medical education. Key topics were split into three sub-categories: knowledge (facts, concepts, and information), skills (ability to carry out tasks) and attitudes (ways of thinking or feeling). Thereafter, we used a modified Delphi method where experts rated digital health topics over two rounds based on whether topics should be included in the curriculum for medical students on a scale from 1 (strongly disagree) to 5 (strongly agree). A predefined cut-off of ≥4 was used to identify topics that were critical to include in a digital health curriculum for medical students.RESULTS: The scoping review resulted in a total of 113 included articles, with 65 relevant topics extracted and included in the questionnaire. The topics were rated by 18 experts, all of which completed both questionnaire rounds. A total of 40 (62%) topics across all three sub-categories met the predefined rating cut-off value of ≥4.CONCLUSION: An expert panel identified 40 important digital health topics within knowledge, skills, and attitudes for medical students to be taught. These can help guide medical educators in the development of future digital health curricula.

Introduction: In order to fulfill the enormous potential of digital health in the healthcare sector, digital health must become an integrated part of medical education. We aimed to investigate which knowledge, skills and attitudes should be included in a digital health curriculum for medical students through a scoping review and Delphi method study. Methods: We conducted a scoping review of the literature on digital health relevant for medical education. Key topics were split into three sub-categories: knowledge (facts, concepts, and information), skills (ability to carry out tasks) and attitudes (ways of thinking or feeling). Thereafter, we used a modified Delphi method where experts rated digital health topics over two rounds based on whether topics should be included in the curriculum for medical students on a scale from 1 (strongly disagree) to 5 (strongly agree). A predefined cut-off of ≥4 was used to identify topics that were critical to include in a digital health curriculum for medical students. Results: The scoping review resulted in a total of 113 included articles, with 65 relevant topics extracted and included in the questionnaire. The topics were rated by 18 experts, all of which completed both questionnaire rounds. A total of 40 (62%) topics across all three sub-categories met the predefined rating cut-off value of ≥4. Conclusion: An expert panel identified 40 important digital health topics within knowledge, skills, and attitudes for medical students to be taught. These can help guide medical educators in the development of future digital health curricula.

Digital technologies are rapidly being integrated into a wide range of health fields. This new domain, often termed ‘digital health’, has the potential to significantly improve healthcare outcomes and global health equity more broadly. However, its effective implementation and responsible use are contingent on building a health workforce with a sufficient level of knowledge and skills to effectively navigate the digital transformations in health. More specifically, the next generation of health professionals—namely youth—must be adequately prepared to maximise the potential of these digital transformations. In this commentary, we highlight three priority areas which should be prioritised in digital education to realise the benefits of digital health: capacity building, opportunities for youth, and an ethics-driven approach. Firstly, capacity building requires educational frameworks and curricula to not only be updated, but to also place an emphasis on interdisciplinary learning. Secondly, opportunities are important for youth to meaningfully participate in decision-making processes and gain invaluable practical experiences. Thirdly, training in digital ethics and the responsible use of data as a standard component of education will help to safeguard against potential future inequities resulting from the implementation and use of digital health technologies, Digital technologies are rapidly being integrated into a wide range of health fields. This new domain, often termed ‘digital health’, has the potential to significantly improve healthcare outcomes and global health equity more broadly. However, its effective implementation and responsible use are contingent on building a health workforce with a sufficient level of knowledge and skills to effectively navigate the digital transformations in health. More specifically, the next generation of health professionals—namely youth—must be adequately prepared to maximise the potential of these digital transformations. In this commentary, we highlight three priority areas which should be prioritised in digital education to realise the benefits of digital health: capacity building, opportunities for youth, and an ethics-driven approach. Firstly, capacity building requires educational frameworks and curricula to not only be updated, but to also place an emphasis on interdisciplinary learning. Secondly, opportunities are important for youth to meaningfully participate in decision-making processes and gain invaluable practical experiences. Thirdly, training in digital ethics and the responsible use of data as a standard component of education will help to safeguard against potential future inequities resulting from the implementation and use of digital health technologies.

Plenty of digital resources are out there to help medical students learn—but how do you choose which is right for you? Mark Khurana looks at the different platforms available and presents some of his favourite ways to learn The volume of information you need to learn in a short space of time for medical school can be daunting, and efficiency is key. Fortunately the digital age has presented medical students with new mediums through which to learn.1,2 In this article I look at their pros and cons and provide some high quality examples, Plenty of digital resources are out there to help medical students learn - but how do you choose which is right for you? Mark Khurana looks at the different platforms available and presents some of his favourite ways to learn

Background Solid organ transplant (SOT) recipients are at a high risk of developing cytomegalovirus (CMV) post-transplant (tx) with many experiencing a recurrence shortly after clearing the first episode. We aimed to identify risk factors associated with CMV infection and recurrence. Methods SOT recipients (≥ 18 years) transplanted between 2011-2016 were investigated for factors associated with CMV infection within 1 year from baseline and recurrent CMV within 6 months of stopping CMV treatment for the first infection using cumulative incidence curves and Cox proportional hazards models. Baseline was defined as either tx date or date of stopping CMV prophylaxis for those initiating CMV prophylaxis within 7 days of tx. Individuals with breakthrough CMV while on prophylaxis were excluded (n=29). Results We included 755 SOT recipients, 173(23%) developed CMV infection within one year of baseline with CMV disease present at diagnosis in 17% of the cases. The risk of CMV infection was lower in patients with low (aHR 0.19, 95%CI 0.12-0.29) and intermediate (aHR 0.26, 95%CI 0.18-0.36) risk CMV IgG serostatus compared to high risk (Figure1). Liver and lung tx, female sex, older age and year of tx were also associated with an increased risk of CMV infection (Figure 2). Among the 470 (62%) patients who received CMV prophylaxis those who received < 85 days had a higher risk of CMV infection than those receiving ≥ 85 days (aHR 1.80, 95%CI 1.19-2.72). 99 recipients were investigated for recurrent CMV; 40 (40%) experienced relapse within 6 months of stopping treatment for their first infection. The risk of recurrent CMV was significantly lower in those with low (aHR 0.20, 95%CI 0.06-0.74) and intermediate risk serostatus (aHR 0.40, 95%CI 0.19-0.84) (Figure 3). Older age (aHR 1.23 per 5 years older, 95%CI 1.06-1.44) was also significantly associated with recurrent CMV infection (Figure 4). Conclusion Recurrent CMV infection remains a signif, Background Solid organ transplant (SOT) recipients are at a high risk of developing cytomegalovirus (CMV) post-transplant (tx) with many experiencing a recurrence shortly after clearing the first episode. We aimed to identify risk factors associated with CMV infection and recurrence. Methods SOT recipients (≥ 18 years) transplanted between 2011-2016 were investigated for factors associated with CMV infection within 1 year from baseline and recurrent CMV within 6 months of stopping CMV treatment for the first infection using cumulative incidence curves and Cox proportional hazards models. Baseline was defined as either tx date or date of stopping CMV prophylaxis for those initiating CMV prophylaxis within 7 days of tx. Individuals with breakthrough CMV while on prophylaxis were excluded (n=29). Results We included 755 SOT recipients, 173(23%) developed CMV infection within one year of baseline with CMV disease present at diagnosis in 17% of the cases. The risk of CMV infection was lower in patients with low (aHR 0.19, 95%CI 0.12-0.29) and intermediate (aHR 0.26, 95%CI 0.18-0.36) risk CMV IgG serostatus compared to high risk (Figure1). Liver and lung tx, female sex, older age and year of tx were also associated with an increased risk of CMV infection (Figure 2). Among the 470 (62%) patients who received CMV prophylaxis those who received < 85 days had a higher risk of CMV infection than those receiving ≥ 85 days (aHR 1.80, 95%CI 1.19-2.72). 99 recipients were investigated for recurrent CMV; 40 (40%) experienced relapse within 6 months of stopping treatment for their first infection. The risk of recurrent CMV was significantly lower in those with low (aHR 0.20, 95%CI 0.06-0.74) and intermediate risk serostatus (aHR 0.40, 95%CI 0.19-0.84) (Figure 3). Older age (aHR 1.23 per 5 years older, 95%CI 1.06-1.44) was also significantly associated with recurrent CMV infection (Figure 4). Figure 3 Risk of recurrent CMV infection in th

Background Transplant recipients are an immunologically vulnerable patient group and are at elevated risk of Clostridioides difficile infection (CDI) compared with other hospitalized populations. However, risk factors for CDI post-transplant are not fully understood. Methods Adults undergoing solid organ (SOT) and hematopoietic stem cell transplant (HSCT) from January 2010 to February 2017 at Rigshospitalet, University of Copenhagen, Denmark, were retrospectively included. Using nationwide data capture of all CDI cases, the incidence and risk factors of CDI were assessed. Results A total of 1687 patients underwent SOT or HSCT (1114 and 573, respectively), with a median follow-up time (interquartile range) of 1.95 (0.52–4.11) years. CDI was diagnosed in 15% (164) and 20% (114) of the SOT and HSCT recipients, respectively. CDI rates were highest in the 30 days post-transplant for both SOT and HSCT (adjusted incidence rate ratio [aIRR], 6.64; 95% confidence interval [CI], 4.37–10.10; and aIRR, 2.85; 95% CI, 1.83–4.43, respectively, compared with 31–180 days). For SOT recipients, pretransplant CDI and liver and lung transplant were associated with a higher risk of CDI in the first 30 days post-transplant, whereas age and liver transplant were risk factors in the later period. Among HSCT recipients, myeloablative conditioning and a higher Charlson Comorbidity Index were associated with a higher risk of CDI in the early period but not in the late period. Conclusions Using nationwide data, we show a high incidence of CDI among transplant recipients. Importantly, we also find that risk factors can vary relative to time post-transplant