Epidemiology of Renal Replacement Therapy for Critically Ill Patients across Seven Health Jurisdictions.

INTRODUCTION: Acute kidney injury (AKI) requiring treatment with renal replacement therapy (RRT) is a common complication after admission to an intensive care unit (ICU) and is associated with significant morbidity and mortality. However, the prevalence of RRT use and the associated outcomes in critically patients across the globe are not well described. Therefore, we describe the epidemiology and outcomes of patients receiving RRT for AKI in ICUs across several large health system jurisdictions. METHODS: Retrospective cohort analysis using nationally representative and comparable databases from seven health jurisdictions in Australia, Brazil, Canada, Denmark, New Zealand, Scotland, and the USA between 2006 and 2023, depending on data availability of each dataset. Patients with a history of end-stage kidney disease receiving chronic RRT and patients with a history of renal transplant were excluded. RESULTS: A total of 4,104,480 patients in the ICU cohort and 3,520,516 patients in the mechanical ventilation cohort were included. Overall, 156,403 (3.8%) patients in the ICU cohort and 240,824 (6.8%) patients in the mechanical ventilation cohort were treated with RRT for AKI. In the ICU cohort, the proportion of patients treated with RRT was lowest in Australia and Brazil (3.3%) and highest in Scotland (9.2%). The in-hospital mortality for critically ill patients treated with RRT was almost fourfold higher (57.1%) than those not receiving RRT (16.8%). The mortality of patients treated with RRT varied across the health jurisdictions from 37 to 65%. CONCLUSION: The outcomes of patients who receive RRT in ICUs throughout the world vary widely. Our research suggests that differences in access to and provision of this therapy are contributing factors.

Defining disease severity in atopic dermatitis and psoriasis for the application to biomarker research: an interdisciplinary perspective.

More severe atopic dermatitis and psoriasis are associated with a higher cumulative impact on quality of life, multimorbidity and healthcare costs. Proactive, early intervention in those most at risk of severe disease may reduce this cumulative burden and modify the disease trajectory to limit progression. The lack of reliable biomarkers for this at-risk group represents a barrier to such a paradigm shift in practice. To expedite discovery and validation, the BIOMarkers in Atopic Dermatitis and Psoriasis (BIOMAP) consortium (a large-scale European, interdisciplinary research initiative) has curated clinical and molecular data across diverse study designs and sources including cross-sectional and cohort studies (small-scale studies through to large multicentre registries), clinical trials, electronic health records and large-scale population-based biobanks. We map all dataset disease severity instruments and measures to three key domains (symptoms, inflammatory activity and disease course), and describe important codependencies and relationships across variables and domains. We prioritize definitions for more severe disease with reference to international consensus, reference standards and/or expert opinion. Key factors to consider when analysing datasets across these diverse study types include explicit early consideration of biomarker purpose and clinical context, candidate biomarkers associated with disease severity at a particular point in time and over time and how they are related, taking the stage of biomarker development into account when selecting disease severity measures for analyses, and validating biomarker associations with disease severity outcomes using both physician- and patient-reported measures and across domains. The outputs from this exercise will ensure coherence and focus across the BIOMAP consortium so that mechanistic insights and biomarkers are clinically relevant, patient-centric and more generalizable to current and future research efforts.

Atopic dermatitis (AD), and psoriasis are long-term skin conditions that can significantly affect people's lives, especially when symptoms are severe. Approximately 10% of adults and 20% of children are affected by AD, while psoriasis affects around 5% of people in the UK. Both conditions are associated with debilitating physical symptoms (such as itch) and have been linked to depression and anxiety. Biomarkers are naturally occurring chemicals in the human body and have potential to enhance the longer-term management of AD and psoriasis. Currently, there are no routinely used biomarkers that can identify people who experience or will go on to develop severe AD and psoriasis. For this reason, research is under way to understand which biomarkers are linked to severity. In this study, a multidisciplinary team of skin researchers from across Europe, along with patient groups, discussed the complexities of studying severity-related biomarkers. We identified a number of severity measurement approaches and there were recommendations for future biomarker research, including (i) considering multiple measures as no single measure can encompass all aspects of severity, (ii) exploring severity measures recorded by both healthcare professionals and patients, as each may capture different aspects, and (iii) accounting for influencing factors, such as different treatment approaches, that may impact AD and psoriasis severity, which make it challenging to compare findings across studies. Overall, we anticipate that the insights gained from these discussions will increase the likelihood of biomarkers being effectively applied in real-world settings, to ultimately improve outcomes for people with AD and psoriasis.

Solidarity and reciprocity during the COVID-19 pandemic: a longitudinal qualitative interview study from Germany.

BACKGROUND: While solidarity practices were important in mitigating the Coronavirus Disease 2019 (COVID-19) pandemic, their limits became evident as the pandemic progressed. Taking a longitudinal approach, this study analyses German residents' changing perceptions of solidarity practices during the COVID-19 pandemic and examines potential reasons for these changes. METHODS: Adults living in Germany were interviewed in April 2020 (n = 46), October 2020 (n = 43) and October 2021 (n = 40) as part of the SolPan Research Commons, a large-scale, international, qualitative, longitudinal study uniquely situated in a major global public health crisis. Interviews were analysed using qualitative content analysis. RESULTS: While solidarity practices were prominently discussed and positively evaluated in April 2020, this initial enthusiasm waned in October 2020 and October 2021. Yet, participants still perceived solidarity as important for managing the pandemic and called for institutionalized forms of solidarity in October 2020 and October 2021. Reasons for these changing perceptions of solidarity included (i) increasing personal and societal costs to act in solidarity, (ii) COVID-19 policies hindering solidarity practices, and (iii) a perceived lack of reciprocity as participants felt that solidarity practices from the state were not matching their individual efforts. CONCLUSIONS: Maintaining solidarity contributes to maximizing public health during a pandemic. Institutionalized forms of solidarity to support those most in need contribute to perceived reciprocity among individuals, which might increase their motivation to act in solidarity. Thus, rather than calling for individual solidarity during times of crisis, authorities should consider implementing sustaining solidarity-based social support systems that go beyond immediate crisis management.

Translating theories of justice into a practice model for triage of scarce intensive care resources during a pandemic.

During the COVID-19 pandemic, national triage guidelines were developed to address the anticipated shortage of life-saving resources, should ICU capacities be overloaded. Rationing and triage imply that in addition to individual patient interests, interests of population health have to be integrated. The transfer of theoretical and empirical knowledge into feasible and useful practice models and their implementation in clinical settings need to be improved. This paper analyzes how triage protocols could translate abstract theories of distributive justice into concrete material and procedural criteria for rationing intensive care resources during a pandemic. We reconstruct the development and implementation of a rationing protocol at a German university hospital: describing the ethical challenge of triage, clarifying the aspirational norms, and summarizing specific norms of fair triage and allocation for developing an institutional policy and practice model and implementing it. We reflect on how critical topics are seen by clinicians and what helped manage the perceived burdens of the triage dilemma. We analyze what can be learned from this debate regarding the difficult issues around triage protocols and their potential implementation into clinical settings. Analyzing the ought-to-is gap of triage, integrating abstract ethical principles into practical concepts, and evaluating those should clarify the benefits and risks of different allocation options. We seek to inform debates on triage concepts and policies to ensure the best possible treatment and fair allocation of resources as well as to help protect patients and professionals in worst-case scenarios.

Acceptance of Social Media Recruitment for Clinical Studies Among Patients With Hepatitis B: Mixed Methods Study.

BACKGROUND: Social media platforms are increasingly used to recruit patients for clinical studies. Yet, patients' attitudes regarding social media recruitment are underexplored. OBJECTIVE: This mixed methods study aims to assess predictors of the acceptance of social media recruitment among patients with hepatitis B, a patient population that is considered particularly vulnerable in this context. METHODS: Using a mixed methods approach, the hypotheses for our survey were developed based on a qualitative interview study with 6 patients with hepatitis B and 30 multidisciplinary experts. Thematic analysis was applied to qualitative interview analysis. For the cross-sectional survey, we additionally recruited 195 patients with hepatitis B from 3 clinical centers in Germany. Adult patients capable of judgment with a hepatitis B diagnosis who understood German and visited 1 of the 3 study centers during the data collection period were eligible to participate. Data analysis was conducted using SPSS (version 28; IBM Corp), including descriptive statistics and regression analysis. RESULTS: On the basis of the qualitative interview analysis, we hypothesized that 6 factors were associated with acceptance of social media recruitment: using social media in the context of hepatitis B (hypothesis 1), digital literacy (hypothesis 2), interest in clinical studies (hypothesis 3), trust in nonmedical (hypothesis 4a) and medical (hypothesis 4b) information sources, perceiving the hepatitis B diagnosis as a secret (hypothesis 5a), attitudes toward data privacy in the social media context (hypothesis 5b), and perceived stigma (hypothesis 6). Regression analysis revealed that the higher the social media use for hepatitis B (hypothesis 1), the higher the interest in clinical studies (hypothesis 3), the more trust in nonmedical information sources (hypothesis 4a), and the less secrecy around a hepatitis B diagnosis (hypothesis 5a), the higher the acceptance of social media as a recruitment tool for clinical hepatitis B studies. CONCLUSIONS: This mixed methods study provides the first quantitative insights into social media acceptance for clinical study recruitment among patients with hepatitis B. The study was limited to patients with hepatitis B in Germany but sets out to be a reference point for future studies assessing the attitudes toward and acceptance of social media recruitment for clinical studies. Such empirical inquiries can facilitate the work of researchers designing clinical studies as well as ethics review boards in balancing the risks and benefits of social media recruitment in a context-specific manner.

Practical Benefits, Challenges, and Recommendations on Social Media Recruitment: Multi-Stakeholder Interview Study.

BACKGROUND: The increasing use of social media opens new opportunities for recruiting patients for research studies. However, systematic evaluations indicate that the success of social media recruitment in terms of cost-effectiveness and representativeness depends on the type of study and its purpose. OBJECTIVE: This study aims to explore the practical benefits and challenges of recruiting study participants with social media in the context of clinical and nonclinical studies and provide a summary of expert advice on how to conduct social media-based recruitment. METHODS: We conducted semistructured interviews with 6 patients with hepatitis B who use social media and 30 experts from the following disciplines: (1) social media researchers or social scientists, (2) practical experts for social media recruitment, (3) legal experts, (4) ethics committee members, and (5) clinical researchers. The interview transcripts were analyzed using thematic analysis. RESULTS: We found diverging expert opinions regarding the challenges and benefits of social media recruitment for research studies in four domains: (1) resources needed, (2) representativeness, (3) web-based community building, and (4) privacy considerations. Moreover, the interviewed experts provided practical advice on how to promote a research study via social media. CONCLUSIONS: Even though recruitment strategies should always be sensitive to individual study contexts, a multiplatform approach (recruiting via several different social media platforms) with mixed-methods recruitment (web-based and offline recruitment channels) is the most beneficial recruitment strategy for many research studies. The different recruitment methods complement each other and may contribute to improving the reach of the study, the recruitment accrual, and the representativeness of the sample. However, it is important to assess the context- and project-specific appropriateness and usefulness of social media recruitment before designing the recruitment strategy.

Preparing for the Worst-Case Scenario in a Pandemic: Intensivists Simulate Prioritization and Triage of Scarce ICU Resources.

OBJECTIVES: Simulation and evaluation of a prioritization protocol at a German university hospital using a convergent parallel mixed methods design. DESIGN: Prospective single-center cohort study with a quantitative analysis of ICU patients and qualitative content analysis of two focus groups with intensivists. SETTING: Five ICUs of internal medicine and anesthesiology at a German university hospital. PATIENTS: Adult critically ill ICU patients ( n = 53). INTERVENTIONS: After training the attending senior ICU physicians ( n = 13) in rationing, an impending ICU congestion was simulated. All ICU patients were rated according to their likelihood to survive their acute illness (good-moderate-unfavorable). From each ICU, the two patients with the most unfavorable prognosis ( n = 10) were evaluated by five prioritization teams for triage. MEASUREMENTS AND MAIN RESULTS: Patients nominated for prioritization visit ( n = 10) had higher Sequential Organ Failure Assessment scores and already a longer stay at the hospital and on the ICU compared with the other patients. The order within this worst prognosis group was not congruent between the five teams. However, an in-hospital mortality of 80% confirmed the reasonable match with the lowest predicted probability of survival. Qualitative data highlighted the tremendous burden of triage and the need for a team-based consensus-oriented decision-making approach to ensure best possible care and to support professionals. Transparent communication within the teams, the hospital, and to the public was seen as essential for prioritization implementation. CONCLUSIONS: To mitigate potential bias and to reduce the emotional burden of triage, a consensus-oriented, interdisciplinary, and collaborative approach should be implemented. Prognostic comparative assessment by intensivists is feasible. The combination of long-term ICU stay and consistently high Sequential Organ Failure Assessment scores resulted in a greater risk for triage in patients. It remains challenging to reliably differentiate between patients with very low chances to survive and requires further conceptual and empirical research.

Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress' prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence?

Embedded ethics: a proposal for integrating ethics into the development of medical AI.

The emergence of ethical concerns surrounding artificial intelligence (AI) has led to an explosion of high-level ethical principles being published by a wide range of public and private organizations. However, there is a need to consider how AI developers can be practically assisted to anticipate, identify and address ethical issues regarding AI technologies. This is particularly important in the development of AI intended for healthcare settings, where applications will often interact directly with patients in various states of vulnerability. In this paper, we propose that an 'embedded ethics' approach, in which ethicists and developers together address ethical issues via an iterative and continuous process from the outset of development, could be an effective means of integrating robust ethical considerations into the practical development of medical AI.

Practices and Attitudes of Bavarian Stakeholders Regarding the Secondary Use of Health Data for Research Purposes During the COVID-19 Pandemic: Qualitative Interview Study.

BACKGROUND: The COVID-19 pandemic is a threat to global health and requires collaborative health research efforts across organizations and countries to address it. Although routinely collected digital health data are a valuable source of information for researchers, benefiting from these data requires accessing and sharing the data. Health care organizations focusing on individual risk minimization threaten to undermine COVID-19 research efforts, and it has been argued that there is an ethical obligation to use the European Union's General Data Protection Regulation (GDPR) scientific research exemption during the COVID-19 pandemic to support collaborative health research. OBJECTIVE: This study aims to explore the practices and attitudes of stakeholders in the German federal state of Bavaria regarding the secondary use of health data for research purposes during the COVID-19 pandemic, with a specific focus on the GDPR scientific research exemption. METHODS: Individual semistructured qualitative interviews were conducted between December 2020 and January 2021 with a purposive sample of 17 stakeholders from 3 different groups in Bavaria: researchers involved in COVID-19 research (n=5, 29%), data protection officers (n=6, 35%), and research ethics committee representatives (n=6, 35%). The transcripts were analyzed using conventional content analysis. RESULTS: Participants identified systemic challenges in conducting collaborative secondary-use health data research in Bavaria; secondary health data research generally only happens when patient consent has been obtained, or the data have been fully anonymized. The GDPR research exemption has not played a significant role during the pandemic and is currently seldom and restrictively used. Participants identified 3 key groups of barriers that led to difficulties: the wider ecosystem at many Bavarian health care organizations, legal uncertainty that leads to risk-adverse approaches, and ethical positions that patient consent ought to be obtained whenever possible to respect patient autonomy. To improve health data research in Bavaria and across Germany, participants wanted greater legal certainty regarding the use of pseudonymized data for research purposes without the patient's consent. CONCLUSIONS: The current balance between enabling the positive goals of health data research and avoiding associated data protection risks is heavily skewed toward avoiding risks; so much so that it makes reaching the goals of health data research extremely difficult. This is important, as it is widely recognized that there is an ethical imperative to use health data to improve care. The current approach also creates a problematic conflict with the ambitions of Germany, and the federal state of Bavaria, to be a leader in artificial intelligence. A recent development in the field of German public administration known as norm screening (Normenscreening) could potentially provide a systematic approach to minimize legal barriers. This approach would likely be beneficial to other countries.