Dihydroartemisinin-Piperaquine vs. Artemether-Lumefantrine for First-Line Treatment of Uncomplicated Malaria in African Children: A Cost-Effectiveness Analysis.

Recent multi-centre trials showed that dihydroartemisinin-piperaquine (DP) was as efficacious and safe as artemether-lumefantrine (AL) for treatment of young children with uncomplicated P. falciparum malaria across diverse transmission settings in Africa. Longitudinal follow-up of patients in these trials supported previous findings that DP had a longer post-treatment prophylactic effect than AL, reducing the risk of reinfection and conferring additional health benefits to patients, particularly in areas with moderate to high malaria transmission. We developed a Markov model to assess the cost-effectiveness of DP versus AL for first-line treatment of uncomplicated malaria in young children from the provider perspective, taking into consideration the post-treatment prophylactic effects of the drugs as reported by a recent multi-centre trial in Africa and using the maximum manufacturer drug prices for artemisinin-based combination therapies set by the Global Fund in 2013. We estimated the price per course of treatment threshold above which DP would cease to be a cost-saving alternative to AL as a first-line antimalarial drug. First-line treatment with DP compared to AL averted 0.03 DALYs (95% CI: 0.006-0.07) and 0.001 deaths (95% CI: 0.00-0.002) and saved $0.96 (95$1.23 per course of treatment. DP is superior to AL from both the clinical and economic perspectives for treatment of uncomplicated P. falciparum malaria in young children. A paediatric dispersible formulation of DP is under development and should facilitate a targeted deployment of this antimalarial drug. The use of DP as first-line antimalarial drug in paediatric malaria patients in moderate to high transmission areas of Africa merits serious consideration by health policymakers

Judgment of the Humanness of an Interlocutor Is in the Eye of the Beholder

Despite tremendous advances in artificial language synthesis, no machine has so far succeeded in deceiving a human. Most research focused on analyzing the behavior of “good” machine. We here choose an opposite strategy, by analyzing the behavior of “bad” humans, i.e., humans perceived as machine. The Loebner Prize in Artificial Intelligence features humans and artificial agents trying to convince judges on their humanness via computer-mediated communication. Using this setting as a model, we investigated here whether the linguistic behavior of human subjects perceived as non-human would enable us to identify some of the core parameters involved in the judgment of an agents' humanness. We analyzed descriptive and semantic aspects of dialogues in which subjects succeeded or failed to convince judges of their humanness. Using cognitive and emotional dimensions in a global behavioral characterization, we demonstrate important differences in the patterns of behavioral expressiveness of the judges whether they perceived their interlocutor as being human or machine. Furthermore, the indicators of interest displayed by the judges were predictive of the final judgment of humanness. Thus, we show that the judgment of an interlocutor's humanness during a social interaction depends not only on his behavior, but also on the judge himself. Our results thus demonstrate that the judgment of humanness is in the eye of the beholder

Budget impact analysis of medicines : updated systematic review and implications

This evaluation determines whether published studies to date meet the key characteristics identified for budget impact analyses (BIA) for medicines, accomplished through a systematic review and assessment against identified key characteristics. Studies from 2001 to 2015 on "budget impact analysis" with "drug" interventions were assessed, selected based on their titles/abstracts and full texts, with their characteristics checked according to key criteria. Out of 1984 studies, 92 were identified. Of these, 95% were published in Europe and the USA. 2012 saw the largest number of publications (16%) with a decline thereafter. 48% met up to 6 or 7 out of the 9 key characteristics. Only 22% stated no conflict of interest. The results indicate low adherence to the key characteristics that should be considered for BIAs and strong conflict of interest. This is an issue since BIAs can be of fundamental importance in managing the entry of new medicines including reimbursement decisions

Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry

OBJECTIVE: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. METHODS: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. RESULTS: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. CONCLUSION: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression

Perspectives and Integration in SOLAS Science

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

Association between Tumor Necrosis Factor Inhibitors and the Risk of Hospitalization or Death among Patients with Immune-Mediated Inflammatory Disease and COVID-19

Importance: Although tumor necrosis factor (TNF) inhibitors are widely prescribed globally because of their ability to ameliorate shared immune pathways across immune-mediated inflammatory diseases (IMIDs), the impact of COVID-19 among individuals with IMIDs who are receiving TNF inhibitors remains insufficiently understood. Objective: To examine the association between the receipt of TNF inhibitor monotherapy and the risk of COVID-19-associated hospitalization or death compared with other commonly prescribed immunomodulatory treatment regimens among adult patients with IMIDs. Design, Setting, and Participants: This cohort study was a pooled analysis of data from 3 international COVID-19 registries comprising individuals with rheumatic diseases, inflammatory bowel disease, and psoriasis from March 12, 2020, to February 1, 2021. Clinicians directly reported COVID-19 outcomes as well as demographic and clinical characteristics of individuals with IMIDs and confirmed or suspected COVID-19 using online data entry portals. Adults (age ≥18 years) with a diagnosis of inflammatory arthritis, inflammatory bowel disease, or psoriasis were included. Exposures: Treatment exposure categories included TNF inhibitor monotherapy (reference treatment), TNF inhibitors in combination with methotrexate therapy, TNF inhibitors in combination with azathioprine/6-mercaptopurine therapy, methotrexate monotherapy, azathioprine/6-mercaptopurine monotherapy, and Janus kinase (Jak) inhibitor monotherapy. Main Outcomes and Measures: The main outcome was COVID-19-associated hospitalization or death. Registry-level analyses and a pooled analysis of data across the 3 registries were conducted using multilevel multivariable logistic regression models, adjusting for demographic and clinical characteristics and accounting for country, calendar month, and registry-level correlations. Results: A total of 6077 patients from 74 countries were included in the analyses; of those, 3215 individuals (52.9%) were from Europe, 3563 individuals (58.6%) were female, and the mean (SD) age was 48.8 (16.5) years. The most common IMID diagnoses were rheumatoid arthritis (2146 patients [35.3%]) and Crohn disease (1537 patients [25.3%]). A total of 1297 patients (21.3%) were hospitalized, and 189 patients (3.1%) died. In the pooled analysis, compared with patients who received TNF inhibitor monotherapy, higher odds of hospitalization or death were observed among those who received a TNF inhibitor in combination with azathioprine/6-mercaptopurine therapy (odds ratio [OR], 1.74; 95% CI, 1.17-2.58; P =.006), azathioprine/6-mercaptopurine monotherapy (OR, 1.84; 95% CI, 1.30-2.61; P =.001), methotrexate monotherapy (OR, 2.00; 95% CI, 1.57-2.56; P <.001), and Jak inhibitor monotherapy (OR, 1.82; 95% CI, 1.21-2.73; P =.004) but not among those who received a TNF inhibitor in combination with methotrexate therapy (OR, 1.18; 95% CI, 0.85-1.63; P =.33). Similar findings were obtained in analyses that accounted for potential reporting bias and sensitivity analyses that excluded patients with a COVID-19 diagnosis based on symptoms alone. Conclusions and Relevance: In this cohort study, TNF inhibitor monotherapy was associated with a lower risk of adverse COVID-19 outcomes compared with other commonly prescribed immunomodulatory treatment regimens among individuals with IMIDs