Real-world Settings Research Articles

A novel digital twin strategy to enable the translation of evidence from randomized control trials to new populations

Abstract Background Randomized clinical trials (RCTs) are essential to guide medical practice; however, their generalizability to a given population is often uncertain. Between the SPRINT and ACCORD trials, only SPRINT found a significant reduction in major cardiovascular events (MACE) with intensive blood pressure control, but ACCORD did not, without clear evidence of whether this reflected differences in enrolled patients. Purpose To use a novel RCT digital twin-based approach to demonstrate the translation of an RCT to a different population, leveraging the differences in populations and treatment effects in SPRINT and ACCORD. Methods We developed a statistically informed Generative Adversarial Network (GAN) model that leverages relationships between covariates and outcomes using Directed Acyclic Graphs (DAGs). This model can generate a digital twin of an RCT (RCT-Twin) conditioned on covariate distributions from a second patient population while maintaining these relationships (Fig A). Using this, we generated the (i) RCT-Twin of SPRINT, which was conditioned on the 10 most disparate covariates drawn from ACCORD, and (ii) an RCT-Twin of ACCORD conditioned on SPRINT. To demonstrate treatment effect estimates of each RCT conditioned on the other RCT’s patient population, we evaluated the cardiovascular event-free survival of 10 iterations of these cross-trained RCT-Twins against the original trials. Results Using 9361 SPRINT participants and conditioning on 4733 ACCORD participants, we generated 10 ACCORD-conditioned SPRINT-Twin datasets. We confirmed that the RCT-Twins were consistently balanced between treatment and controls across all measured covariates (mean absolute standardized mean difference (MASMD) 0.019, SD 0.018), as expected for real RCTs. We also confirmed that covariates of the ACCORD-conditioned SPRINT-Twins were closer to ACCORD than SPRINT (MASMD 0.0082 vs 0.46, SD 0.016 vs 0.20), suggestive of successful conditioning. Most importantly, across iterations, ACCORD-conditioned SPRINT-Twin datasets reproduced the overall non-significant effect size seen in ACCORD (5-year MACE hazard ratio (95% confidence interval) of 0.88 (0.73-1.06) in ACCORD vs median 0.87 (0.68-1.13) in the ACCORD-conditioned SPRINT-Twins, Fig B), while the SPRINT-conditioned ACCORD-Twin datasets reproduced the significant effect size seen in SPRINT (0.75 (0.64-0.89) vs median 0.79 (0.72-0.86) in the SPRINT-conditioned ACCORD-Twins, Fig C). Conclusions Our novel conditioned digital twin approach simulates RCT-derived effects in different patient populations by translating these effects to the covariate distributions of the patients. This key methodological advance may enable the direct translation of RCT-derived effects into disparate patient populations and may enable causal inference in real-world settings.

Catheter-directed treatment in acute pulmonary embolism

Abstract Background Pulmonary embolism (PE) is a potentially life-threatening emergency. PE occurs when venous thrombi embolize to the pulmonary circulation, resulting in vascular occlusion, impairing gas exchange and circulation. Initial risk stratification of acute PE is based on clinical symptoms, cardiac adaptations, comorbidities, and, in particular signs of haemodynamic instability. The primary aim of the treatment is to restore blood flow to the affected areas of the lungs, resolving/removing embolus burden and preventing further clot formation. In patients with severe PE, comprising decompensation or intended hemodynamic compromise, immediate reperfusion is recommended. Catheter-directed therapies (CDT) are an innovative treatment option for patients with severe PE to resolve embolus and restore pulmonic perfusion. These procedures are less invasive and are supposed to have a lower risk of bleeding complications compared to systemic thrombolysis or surgical embolectomy. Recent studies have shown that CDT are safe and effective treatment options for PE. Purpose Nevertheless, CDT have to demonstrate their non-inferiority and benefits regarding patients’ outcomes in real-world settings. Methods The German nationwide inpatient sample was used to identify and include all hospitalizations of patients with PE 2005-2020 in Germany. PE patients were stratified for use of CDT. Temporal trends of the usage and the impact of CDT on case-fatality and other outcomes were investigated (source: RDC of the Federal Statistical Office and the Statistical Offices of the federal states, DRG Statistics 2005-2020, own calculations). Results Overall, 1,373,084 hospitalisations of patients with PE (55.9% aged ≥70 years; 53.0% females) were included in this study 2005-2020. Among these, 427,238 (31.1%) were categorized as severe PE and 3330 (0.2%) were treated with CDT with an annual increase from 0.17% (2005) to 0.51% (2020). PE patients of younger age, male sex, with previous surgery, and with severe PE were more often treated with CDT. In patients with severe PE, CDT was attributed to lower MACCE (28.2% vs. 34.2%, P<0.001) and in-hospital case-fatality rate (24.9% vs. 31.0%, P<0.001), but higher prevalence of major bleeding (29.5% vs. 17.5%, P<0.001). CDT was associated with reduced MACCE (OR 0.91 [95%CI 0.83-0.99], P=0.031), a trend towards lower case-fatality (OR 0.92 [95%CI 0.84-1.01], P=0.068), but increased major bleeding (OR 2.12 [95%CI 1.92-2.33], P<0.001) in severe PE. The benefit of CDT regarding case-fatality was age-dependent, with the largest benefit in the 8th and 9th decade of life. Conclusions Although the annual rate of CDT increased from 2005 to 2020 in Germany, only 0.2% of the PE patients were treated with CDT. Selection criteria for CDT treatment were younger age, male sex, previous surgery, and severe PE. CDT treatment was associated with reduced MACCE and case-fatality rate in PE patients with severe PE.

Discrete Choice Experiment on Financial Incentives for Engaging Young Adults in Vaping Cessation Programs

Introduction Contingency management involves rewarding individuals based on objective evidence of behavioral changes. This study explores preferences for financial incentives in vaping cessation programs. Methods A discrete choice experiment (DCE) was conducted among young adult current e-cigarette users aged 19-29. DCE attributes (and levels) included reward amount ($100, $300), reward schedule (consistent value, escalating value), reward procedure (gain-framed, loss-framed), vaping education modules (yes, no), text messaging support (yes, no), and cost ($30, $100). Participants were randomized into one of the four blocks, each containing four choice sets. Each choice set presented two hypothetical vaping cessation programs. Choice data (n × choice sets × alternative programs = 154 × 4 × 2 = 1,232 observations) were analyzed using generalized estimation equation models. Results Participants showed a preference for vaping cessation programs offering a higher reward amount (odds ratio [OR] = 11.5; 95% CI,7.0-19.2), gain-framed rewards for sustained abstinence (OR = 1.4; 95% CI,1.0-1.8), text messaging support (OR = 1.9; 95% CI,1.4-2.5), and a lower program cost (OR = 2.6; 95% CI,1.8-3.8). Interaction tests showed significant effects of the rewards procedure among daily e-cigarette users (adjusted OR [AOR] = 2.1; 95% CI,1.3-3.5), but not some-day users; and among those with no quit attempts in the past six months (AOR = 2.7; 95% CI,1.5-4.7), but not those with previous quit attempts. Female participants preferred text messaging support (AOR = 3.6; 95% CI,2.3-5.4), whereas male participants did not show this preference. Conclusion A multifaceted vaping cessation intervention augmented with financial incentives might improve participation and engagement among young adults. Future studies should investigate how these attributes can enhance program reach and vaping abstinence outcomes in real-world settings.

A novel dynamic risk score to predict venous thromboembolism (VTE) recurrences after 3 months of anticoagulation in patients with incident VTE and without active cancer

Abstract Background Predicting the risk of recurrent venous thromboembolism (rVTE) during and following anticoagulation is complex. Current models lack the ability to adapt to changing patient conditions over time and fail to account for the direct impact of anticoagulation in real-world clinical settings. Purpose To develop a dynamic risk prediction model for rVTE to help clinicians decide on the duration of anticoagulant therapy in conjunction with a model for bleeding (also submitted to the conference). Methods UK Clinical Practice Research Datalink data (2001-2020) was used to generate a retrospective cohort with first VTE who had received 3 months of anticoagulation. Patient episodes of rVTE were evaluated. Covariates were collected at baseline and subsequently as time-varying data to capture changes post-VTE. Hazards with 95% confidence intervals (CI) were estimated and covariates included in a Fine & Gray model used as predictors of rVTE. An additive (logarithmic) scoring scheme was developed from subdistribution hazard ratios, discrimination (expressed by the C-statistic) estimated from 10-fold cross-validation. Results 51,465 patients with a first VTE were included; 4041 rVTE were identified in 200,698 person-years of observation. Incidence rates for rVTE were 2.01 per 100 person-years. Nineteen independent predictors of rVTE (recorded before or after the VTE diagnosis) were included in the model, 13 associated with increased risk and 6 with decreased risk, Table 1. Patients recognised as lower-risk, medium and higher-risk (10.5%, 37% and 52.5% of the population, respectively, at 90 days after first VTE, assuming no anticoagulation treatment) had an annualised rVTE incidence rate of 2.20, 3.84, and 7.44 per 100 person-years. The C-statistic for rVTE was 0.65 (95%CI, 0.64-0.66). The points scored can be added or subtracted to predict risk (Table 2). Conclusions Our dynamic risk score effectively identifies patients at risk of rVTE three months post their initial VTE diagnosis. It allows for continuous monitoring of risk, and modelling of treatment impact, providing clinicians with a pragmatic tool to help determine treatment duration, and adapt their strategies in response to evolving patient conditions.Table 1:Predictors for VTE recurrenceTable 2:VTE recurrence risk score

Patient journey from the appearance of red flags to the diagnosis of transthyretin cardiac amyloidosis (ATTR-CM) in Japan: a nationwide retrospective study using a medical claims database

Abstract Introduction Transthyretin amyloid cardiomyopathy (ATTR-CM) is an under-recognized cause of common cardiovascular conditions in the elderly, with relatively high rates among patients diagnosed with heart failure (HF) with preserved ejection fraction. In addition to cardiac symptoms such as HF, extracardiac symptoms such as carpal tunnel syndrome (CTS) and lumbar spinal stenosis (LSS) are also red flags for ATTR-CM. Tafamidis is currently the only disease-modifying therapy approved for the treatment of patients with ATTR-CM and is likely to be more effective in the earlier stage. Patients with ATTR-CM often undergo a long and difficult diagnostic journey because of the nonspecificity of clinical manifestations, resulting in delays in establishing the correct diagnosis. Purpose To identify the timing of appearance of comorbidities in patients with ATTR-CM during diagnosis. Methods In this retrospective, non-interventional, observational study using a claims database (dataset period: April 1, 2014–August 31, 2021), adult patients with a diagnosis of ATTR-CM or prescription for tafamidis 80 mg were included. The index date was defined as the first date of recording ATTR-CM diagnosis or the prescription of tafamidis 80 mg, whichever was earlier. The baseline period was defined as the period between the index date and 6 months before the index date. The onset date was defined as the first date of recording diagnosis of the first red-flags that was suspicious for ATTR-CM. Results Of 11,101,578 patients in the database, 246 patients with ATTR-CM met the inclusion criteria. A total of 239 patients were included, of whom 139 had received tafamidis 80 mg. The median (range) age at the index date was 79.0 (46.0–95.0) years, and 79.9% (191/239) were male. The most frequently reported comorbidity defined as onset of ATTR-CM was conduction disorders (88.7%) followed by atrial fibrillation/atrial flutter (50.6%), hypertensive heart disease (19.7%), aortic stenosis (15.9%), and hypertrophic cardiomyopathy (11.7%), with the median (interquartile range [IQR]) time to the index date being 15.5 (5.0–24.5), 14.0 (5.0–22.0), 9.0 (2.0–18.0), 5.0 (2.0–16.0), and 12.0 (6.5–21.5) months, respectively (Fig. 1). LSS (23.9%), neuropathy (13.0%), and CTS (7.5%) were frequently observed as extracardiac symptoms at baseline, and the median (IQR) time from appearance to the index date was 19 (9.0–28.0), 5.0 (1.0–16.0), and 18.0 (14.0–25.0) months, respectively (Fig. 2). Conclusions This study elucidated the time lag between the appearance of cardiac and extracardiac complications of ATTR-CM and its diagnosis in real-world clinical settings. These novel findings highlight the potential for earlier detection of ATTR-CM.

Framework for approaching federated causal inference based on real-world observational data sources

Abstract Context Causal inference methods, generally requiring detailed individual information, allow us to evaluate public health interventions in real-world observational settings. When comparing interventions across borders and for this purpose leveraging distributed sensitive individual-level data, a federated approach can be aided. However, reusing such distributed data while maintaining privacy and interoperability, is a challenging endeavor. Methodological framework In the context of the BY-COVID project, a methodological framework to approach federated causal inference was published in October 2023. It is presented as a set of guidelines in the form several consecutive steps, starting with defining a research question, to building a causal model, translating the causal model into data requirements captured within a Common Data Model (CDM), generating synthetic data complying with the requirements captured in the CDM, and developing interoperable analysis scripts which can be distributed for deployment in different federated nodes. The proposed framework was built through implementing and combining existing methodologies and taking into account the principles of legal, organizational, semantic and technical interoperability. Objectives This presentation will provide an overview of the proposed framework, and its demonstration by performing an international comparison of the real-world effectiveness of SARS-CoV-2 primary vaccination campaigns in preventing infections at different federated sites. Challenges encountered (e.g. difficulties in complying with data requirements by linking heterogeneous local data sources) and lessons learned in the course of the demonstrator will be highlighted. Implications We aim to contribute to a public health research field where the rapid assessment of emerging population-health research questions (potentially feeding into evidence-based policy-making) is achievable, in that way contributing to European pandemic preparedness.

A novel dynamic risk score to predict Clinically Significant Bleeding (CSB) after 3 months of anticoagulation in patients with incident Venous ThromboEmbolism (VTE) and without active cancer

Abstract Background Predicting the risk of clinically significant bleeding (CSB), bleeding requiring hospitalisation or fatal bleeding, during and following anticoagulation is complex. Current models lack the ability to adapt to changing patient conditions over time and fail to account for the direct impact of anticoagulation in real-world clinical settings. Purpose To develop a dynamic risk prediction model for CSB to help clinicians decide on the duration of anticoagulant therapy in conjunction with a model for recurrences of VTE (also submitted to the conference). Methods UK Clinical Practice Research Datalink data (2001-2020) was used to generate a retrospective cohort with first VTE who had received 3 months of anticoagulation. Patient episodes of CSB and recurrent VTE were evaluated. Covariates were collected at baseline and subsequently as time-varying data to capture changes post-VTE. Hazards with 95% confidence intervals (CI) were estimated and covariates included in a Fine & Gray model used as predictors of CSB. An additive (logarithmic) scoring scheme was developed from subdistribution hazard ratios, discrimination (expressed by the C-statistic) estimated from 10-fold cross-validation. Results 51,621 patients with a first VTE were included; 3307 CSB were identified in 206,292 person-years of observation. Incidence rates for CSB were 1.60 per 100 person-years. 18 independent predictors of CSB (recorded before or after the VTE diagnosis) were included in the model, Table 1. Patients recognised as lower-risk, medium and higher-risk (67.5 %, 15.9 % and 16.7 % of the population, respectively, at 90 days after first VTE, assuming no anticoagulation treatment) had an annualised incidence rate of 0.84, 2.94, and 9.45 per 100 person-years. The C-statistic for CSB was 0.78 (95%CI, 0.77-0.79). The points scored can be added to predict risk (Table 2). Conclusions Our dynamic score effectively identifies patients at risk of CSB three months post their initial VTE diagnosis. It allows for continuous monitoring of risk, and modelling of treatment impact, providing clinicians with a pragmatic tool to help determine treatment duration, and adapt their strategies in response to evolving patient conditions.Table 1:Predictors for CSBTable 2:CSB risk score

KardioNet Digital - a structured care model involving digital tools for intersectoral communication and a patient-focused strategy for treatment of heart failure

Abstract Introduction Inefficiencies and discontinuities in care at the interfaces within Germany's healthcare system, especially between acute and outpatient care, present significant challenges in managing patients with heart failure (HF). The management complexity of HF has increased with the advent of new digital tools, though patient acceptance of these tools remains contentious. The prevention of loss of diagnostic and therapeutic information for this complex disease is crucial for cross-sectoral communication (hospital - office-based cardiologist - general practitioner) and quality of care. Purpose Our goal was to examine the impact of digital app-supported coordination of HF management across different healthcare providers from hospital discharge to the ambulatory sector and to assess patients' acceptance of a structured care program. A patient-focused digital strategy, supported by a Heart Failure Nurse (HFN), aimed to facilitate structured follow-up and patient empowerment, focusing on patient-reported outcomes and experiences (refer to Table 1). Results Out of 401 patients screened during their hospital stay for HF, only 57 (14.9% male, 12.6% female) participated in the KardioNet Digital (KND) program. NYHA classifications were I (3.5%), II (49.1%), III (40.4%), and IV (7.1%); Diagnoses included CMP (26, 45.6%), CAD (19, 33.3%), valvular HF (8, 14.0%), and others (4, 7.0%). The mean age was 55.03 years, with a notable difference in participation based on age (≥70 years: 9.5% male, 33.3% female; <70 years: 90.5% male, 66.7% female). Age was a significant determinant of program participation. Patients who regularly used the app benefited from several features: A total of 35 alerts (17 patients) were triggered for reasons such as bodyweight increase (2kg or more) and device-induced alerts (i.e. false shock delivery, 3x slow-VT, Syncope), leading the HFN to contact the patients. This early intervention prevented rehospitalization due to decompensation of heart failure in 11 patients (64.7%) and addressed device-related alarms for organizing an emergency hospital visit by HFN. Despite substantial incentives, such as support from an HFN and expedited appointments with specialists for follow-up therapy, refusal rates were high (refer to Table 2). Conclusion A structured, digitally supported cross-sectoral care model for heart failure patients can potentially improve care coordination and outcomes. However, the success of such programs critically depends on patient willingness and the seamless integration into existing healthcare structures. Despite valuable incentives, we observed low acceptance of the program. Even among motivated participants (14.1%), there is a significant need for substantial support and education on digital literacy for the widespread implementation of digital tools in real-world settings for the treatment of heart failure.Workflow of structured digital supportReasons for Declining Participation

The influence of front-of-pack labelling on consumer decision-making: a comprehensive study using electroencephalography and FaceReader

Front-of-pack labels (FOPL) can influence consumer behaviour in a variety of ways, and companies that prioritise accurate and transparent nutrition labels can see benefits in increased sales and brand loyalty. However, there are several types of FOPL on the market that differ in visual appeal and consumer clarity. The aim of the study was to reveal the impact of the nutrition label Nutri-Score as well as other factors on consumer decision-making when choosing healthier alternatives for selected food types. In addition to traditional research methods such as questionnaires, in-depth interviews, also emerging methods such as eye tracking, FaceReader and electroencephalography were used to collect implicit feedback. Research suggests that there are significant differences between implicit and explicit feedback when examining the impact of Nutri-Score on the decision-making process. Last but not least, the study presents ideas for future research in real-world settings using emerging methods.

Luck in high-stakes firm lottery allocation: A natural experimental test of Coasean efficiency and invariance in a prominent sport finance setting

The NBA Player-Draft is a prominent sport-finance setting, with large rents allocated to teams. Several properties make this setting ideal to study the Coase Theorem in a cartelized-firm setting, where the Theorem’s empirical credence and overall relevance to real-world financial settings continue to be questioned. Identification of a high-stakes, salient setting featuring exogenously-assigned property rights has proven elusive. While several studies examine the Coasean implications of professional sports league drafts, we find draft rights are endogenously-assigned. We cultivate, verify, specify, and examine an exogenously-assigned draft right—draft lottery luck—for the 2000–2015 NBA Drafts. Given its revealed exogeneity, we utilize variation in annual lottery luck as a natural experiment to study the Coase Theorem and find robust evidence for “instantaneous” Coasean efficiency (as in efficiency of the efficient market hypothesis) but also evidence that Coasean invariance, with respect to firm profits, fails. Secondary analysis reveals respective mechanisms and sport-financial implications.

Real-world clinical and economic outcomes from rapid start antiretroviral therapy in HIV: systematic review and meta-analysis.

We aimed to synthesize clinical and economic outcomes of rapid start versus non-rapid antiretroviral therapy (ART) in people with HIV (PWH) in real-world settings. A search was conducted in PubMed, Embase, Web of Science, and ProQuest from January 2017 to January 2023, supplementing a previous search by Ford et.al, 2018. Observational studies investigating clinical or economic outcomes of rapid start ART versus non-rapid ART in PWH were included. Clinical outcomes were mortality, loss-to-follow-up (LTFU), and viral suppression. Economic outcomes were Incremental cost-effectiveness ratio (ICER) values and per patient per month (PPPM) costs. Meta-analyses using random-effects models were performed for clinical outcomes, while qualitative syntheses were conducted for economic outcomes. The quality of clinical and economic studies was assessed. Sixty-two studies were included. The pooled adjusted risk ratio (aRR) for mortality demonstrated a significant reduction in risk of mortality among participants who received rapid start ART compared to non-rapid ART (0.80, 95%CI, 0.65-0.98). For LTFU at 6 and 12 months, the pooled aRR showed increased LTFU for rapid start ART (1.33, 95%CI, 1.15-1.55 and 1.18, 95%CI, 0.74-1.89 respectively). All cost-effectiveness studies reported cost-saving or cost-effective findings. The PPPM costs of rapid start ART across the first 36 months of treatment were consistently lower than non-rapid ART. Rapid ART is associated with reduced mortality and is cost-effective compared to non-rapid ART in real-world settings. Clinicians and policymakers should consider these findings to facilitate rapid start of ART in PWH. Further research on LTFU in PWH is needed.

Real-world federated learning in radiology: hurdles to overcome and benefits to gain.

Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments due to numerous hurdles impeding its translation into practice. The few existing real-world FL initiatives rarely communicate specific measures taken to overcome these hurdles. To bridge this significant knowledge gap, we propose a comprehensive guide for real-world FL in radiology. Minding efforts to implement real-world FL, there is a lack of comprehensive assessments comparing FL to less complex alternatives in challenging real-world settings, which we address through extensive benchmarking. We developed our own FL infrastructure within the German Radiological Cooperative Network (RACOON) and demonstrated its functionality by training FL models on lung pathology segmentation tasks across six university hospitals. Insights gained while establishing our FL initiative and running the extensive benchmark experiments were compiled and categorized into the guide. The proposed guide outlines essential steps, identified hurdles, and implemented solutions for establishing successful FL initiatives conducting real-world experiments. Our experimental results prove the practical relevance of our guide and show that FL outperforms less complex alternatives in all evaluation scenarios. Our findings justify the efforts required to translate FL into real-world applications by demonstrating advantageous performance over alternative approaches. Additionally, they emphasize the importance of strategic organization, robust management of distributed data and infrastructure in real-world settings. With the proposed guide, we are aiming to aid future FL researchers in circumventing pitfalls and accelerating translation of FL into radiological applications.

Real‑world evaluation of the efficacy of immune checkpoint inhibitors in the treatment of metastatic breast cancer.

The present study aimed to assess the efficacy and safety of immune checkpoint inhibitor (ICI)-based therapy in patients with metastatic breast cancer (MBC). Therefore, eligible patients with histologically confirmed MBC, treated with ICI-based therapy, were enrolled. The primary endpoint was progression-free survival (PFS) and the secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS) and safety. A total of 90 patients with MBC, treated with ICI-based therapy, with different treatment lines, were included in the present study. The median age was 50 years (range, 27-76). The predominant tumor subtypes were triple negative (53.3%) and luminal (31.1%) breast cancer. The majority of patients (61.1%) were heavily pretreated (lines of treatment, ≥3). Approximately half of the patients (46.7%) had ≥3 metastatic sites. The overall ORR was 36.7% (33/90 patients), while a DCR of 78.9% (71/90 patients) was also recorded. With a median follow-up of 16.0 months, the median PFS and OS were 4.9 months [95% confidence interval (CI), 3.8-6.1] and 13.9 months (95% CI, 9.5-18.2), respectively. Patients treated with ICIs as first-line therapy exhibited notable improvement, with a median PFS of 11.0 months (95% CI, 6.0-16.0) and a median OS of 24.3 months (95% CI, 11.4-37.2). In addition, the pretreatment blood platelet-to-lymphocyte ratio was an independent risk factor for PFS [hazard ratio (HR)=2.406; 95% CI, 1.325-4.370; P=0.004] and OS (HR=2.376; 95% CI, 1.059-5.328; P=0.036). The most common adverse events were nausea (44.4%), neutropenia (42.0%) and alanine aminotransferase/aspartate aminotransferase elevation (22.2%). Furthermore, three (3.3%) patients developed grade 1/2 immuno-related toxicity and recovered after supportive care. Overall, the present study suggested that the ICI-based therapy exhibited encouraging clinical outcomes with manageable toxicity in patients with MBC in real-world settings, with the most favorable efficacy in first-line treatment.

First-person thought is associated with body awareness in daily life

Sensations from the body are thought to play a critical role in many aspects of conscious experience, including first-person thought. In the present set of studies, we examined within-person relationships between in-the-moment subjective awareness of sensations from the body and self-reported first-person thought in real-world settings using ecological momentary assessment (EMA) protocols. In Study 1, participants reported experiencing greater first-person thoughts in moments when they also reported heightened awareness of sensations from their body, and this relationship was stable over a 4-week period even with mean-level changes in body awareness and first-person thought. In Study 2, we replicated this association in a 1-week EMA protocol using both self-report measures and measures derived from participants’ open-ended descriptions of their ongoing thoughts using a natural language processing approach. Taken together, findings shed light on the role of subjective body awareness in other facets of conscious experience.

Componentizing autonomous underwater vehicles by physical-running algorithms

Autonomous underwater vehicles (AUV) constitute a specific type of cyber-physical system that utilize electronic, mechanical, and software components. A component-based approach can address the development complexities of these systems through composable and reusable components and their integration, simplifying the development process and contributing to a more systematic, disciplined, and measurable engineering approach. In this article, we propose an architecture to design and describe the optimal performance of components for an AUV engineering process. The architecture involves a computing approach that carries out the automatic control of a testbed using genetic algorithms, where components undergo a ‘physical-running’ evaluation. The procedure, defined from a method engineering perspective, complements the proposed architecture by demonstrating its application. We conducted an experiment to determine the optimal operating modes of an AUV thruster with a flexible propeller using the proposed method. The results indicate that it is feasible to design and assess physical components directly using genetic algorithms in real-world settings, dispensing with the corresponding computational model and associated engineering stages for obtaining an optimized and tested operational scope. Furthermore, we have developed a cost-based model to illustrate that designing an AUV from a physical-running perspective encompasses extensive feasibility zones, where it proves to be more cost-effective than an approach based on simulation.

Factors Associated with Lipoprotein(a) Testing Among Multiethnic Individuals.

Lipoprotein(a) [Lp(a)] is a causal risk factor for atherosclerotic cardiovascular disease (ASCVD) and clinical guidelines recommend incorporating Lp(a) testing in routine care. Examine real-world, contemporary clinical testing patterns of Lp(a) among multiethnic populations. In this nested case-control study, we assessed the prevalence and factors associated with Lp(a) testing within a large Northern Californian health system between 2010 and 2021. Incident density matching was used to select controls matched with a case for a case:control ratio of up to 1:5. Conditional logistic regression was used to assess the relationship between Lp(a) testing, sociodemographic, and clinical characteristics. We included individuals aged 18years or older with ≥ 2 primary care visits during the study period. Lp(a) testing rates over time and factors associated with testing based on demographic, medical, and healthcare utilization variables. Of the 1,484,410 individuals in the cohort, 14,818 (1.0%) underwent Lp(a) testing. The median Lp(a) level was 35mg/dL and over a third of individuals had Lp(a) levels > 50mg/dL. After adjustment, South Asian individuals were three times more likely to have undergone Lp(a) testing, as compared to non-Hispanic White individuals [OR = 3.19, (95% CI = 2.98, 3.41)], while those identified as non-Hispanic Black and Hispanic were significantly less likely to have undergone Lp(a) testing [OR = 0.70, (95% CI = 0.62, 0.80) and 0.64 (95% CI = 0.59, 0.69), respectively]. Those with a history of ASCVD had over twice the odds of undergoing testing [OR = 2.14 (95% CI = 1.99, 2.29)], as did individuals with more frequent primary care visits [OR = 1.99 (95% CI = 1.84, 2.15)]. Lp(a) testing rates in real-world settings are low, with significant disparities by race, ethnicity, and healthcare utilization. Expanding access to Lp(a) testing may help reduce disparities within ASCVD risk assessment and treatment as new targeted therapeutic agents become available.

Clustering for mitigating subject variability in driving fatigue classification using electroencephalography source-space functional connectivity features.

While Electroencephalography (EEG)-based driver fatigue state classification models have demonstrated effectiveness, their real-world application remains uncertain. The substantial variability in EEG signals among individuals poses a challenge in developing a universal model, often necessitating retraining with the introduction of new subjects. However, obtaining sufficient data for retraining, especially fatigue data for new subjects, is impractical in real-world settings. In response to these challenges, this paper introduces a hybrid solution for fatigue detection that combines clustering with classification. Unsupervised clustering groups subjects based on their EEG functional connectivity in an alert state, and classification models are subsequently applied to each cluster for predicting alert and fatigue states. Results indicate that classification on clusters achieves higher accuracy than scenarios without clustering, suggesting successful grouping of subjects with similar functional connectivity characteristics through clustering, thereby enhancing the classification process. Furthermore, the proposed hybrid method ensures a practical and realistic retraining process, improving the adaptability and effectiveness of the fatigue detection system in real-world applications.&#xD.

The Regulation of Temperature Fluctuations and Energy Consumption in Buildings Using Phase Change Material–Gypsum Boards in Summer

This study examined the thermal performance of Comfortboard23, a commercial gypsum board from Knauf infused with phase change material (PCM). Structural characterization using XRD and SEM confirmed the presence of microencapsulated PCM within the gypsum matrix. The study does not provide a direct comparison between Comfortboard23 and other PCM-integrated gypsum boards on the market. This is a limitation of the research. A comprehensive comparison would involve testing multiple products under identical conditions, and evaluating factors such as thermal performance, cost-effectiveness, durability, and ease of installation. Thermal characterization involved a novel low-scale thermal chamber to measure U-value, thermal conductivity, heat storage capacity, and dynamic thermal response. Results showed incorporating PCM decreased the U-value by 2% compared to standard gypsum boards. Additionally, PCM inclusion increased heat storage capacity by around 45% and improved dynamic thermal characteristics by decreasing thermal stability coefficient from 0.92 to 0.76 and increasing thermal lag from 0.27 to 0.49 h. The 45% increase in heat storage capacity of Comfortboard23 could lead to a 10–20% reduction in heating and cooling energy consumption, improved thermal comfort, and potential HVAC downsizing. Exact benefits depend on climate, building design, and occupancy patterns, necessitating further research in diverse real-world settings. The findings demonstrate Comfortboard23’s potential for enhancing thermal energy storage in buildings, contributing to energy savings, improved thermal comfort, and reduced temperature fluctuations across varying daily temperatures. Overall, the study highlights the promise of Comfortboard23 as an energy-efficient PCM-integrated building material.

Preparing for the Implementation of Long-Acting Injectable Cabotegravir for HIV Pre-Exposure Prophylaxis Within the Brazilian Public Health System (ImPrEP CAB Brasil): Qualitative Study.

Although long-acting, injectable cabotegravir (CAB-LA) pre-exposure prophylaxis (PrEP) has proven efficacious for HIV prevention in clinical trials, research is needed to guide effective implementation in real-world settings. Formative work with community members and health care providers (HCPs) is important to provide insight into the needs and contexts of specific populations and reveal potential barriers and facilitators for implementation projects. We aimed to describe the results from formative work to develop an implementation package for CAB-LA PrEP within the ImPrEP CAB Brasil study. ImPrEP CAB Brasil is an implementation study of same-day delivery of CAB-LA PrEP for young sexual and gender minority (SGM) groups (aged 18-30 years) in 6 existing oral PrEP public health clinics. We conducted formative research to prepare for the implementation of ImPrEP CAB Brasil through community mobilization, process mapping with HCPs with experience in CAB-LA, and focus group discussions (FGDs) with young SGM groups (n=92) and HCPs (n=20) to identify initial perceptions of facilitators and barriers for CAB-LA PrEP implementation, refine the mobile health (mHealth) educational tool, and evaluate the acceptability of using a text message appointment reminder intervention through WhatsApp. FGDs were recorded, transcribed, systematically coded, and analyzed with thematic categorization by trained researchers using a qualitative data analysis program ATLAS.ti (version 7). A community mobilization team comprising 34 SGM community leaders collaborated in creating a prototype for an mHealth educational tool and contributed to the planning of peer education activities. We created 3 process maps for each site to describe the initial visit, follow-up visits, and laboratory flow. The main challenge identified for same-day CAB-LA PrEP delivery was the extended duration of clinic visits due to the numerous laboratory tests and HIV counseling steps required. Proposed solutions included having point-of-care HIV rapid tests instead of laboratory tests and additional counseling staff. Barriers for CAB-LA PrEP implementation identified through FGDs were the training of HCPs, support for adherence to injection appointments, and stigma or discrimination against SGM groups and persons using PrEP. The mHealth educational tool and WhatsApp reminders were highly acceptable by SGM groups and HCPs, indicating their potential to support PrEP choice and adherence. Content analysis on the cultural appropriateness of the language and overall clarity of the material contributed to the refinement of the mHealth tool. Structured formative work with SGM persons and HCPs generated important refinements to context-specific materials and plans to launch ImPrEP CAB Brasil in public health clinics. Ongoing implementation monitoring will use the process maps to identify additional barriers and potential solutions to same-day delivery of CAB-LA PrEP. Summative evaluations are needed to measure the effectiveness of the mHealth educational tool to support PrEP choice and the use of WhatsApp appointment reminders.

Isolation and identification of native Chilean entomopathogenic fungi and their potential for the control of Drosophila suzukii

Drosophila suzukii is an invasive pest of berries and other soft-skinned fruits, was first detected in Chile in 2017, and has since spread over 2,800 km from north to south. Sustainable control of the spotted-wing drosophila (SWD) is essential due the negative attitude of the consumers toward the excessive use of insecticides. During a survey in Chile for biological control agents, thirty-two isolates of entomopathogenic fungi (EPF) were isolated from mycotized insects and soil samples, identified through sequence analysis, and tested against D. suzukii adults under laboratory conditions. The EPF identified are Akanthomyces muscarius, Beauveria bassiana, Beauveria pseudobassiana, Clonostachys rosea, Metarhizium alvesii, Metarhizium brunneum and Metarhizium robertsii. Six isolates caused 100 % of mortality of D. suzukii adults within ten days after the initial exposition to conidia; these included four B. bassiana isolates (LSB 110, LSB 114, LSB 122 and LSB 125), one M. robertsii isolate (LSB 115) and one M. brunneum isolate (LSB 127). LSB 122 and LSB 125 induced the shortest lethal time (LT50 4 and 4.2 days, respectively), while Akanthomyces and Clonostachys caused ≤36 % cumulative mortality of the adults at 10 days of exposure. These results indicate that isolates of B. bassiana, M. robertsii and M. brunneum have significant potential as microbial control agents against D. suzukii adults. This study marks a critical step forward in identifying and validating native entomopathogenic fungi in Chile for sustainable pest management. Future work will focus on further testing these isolates under laboratory, semi-field and field conditions to optimize their application in real-world agricultural settings.