Fibrose pulmonaire idiopathique : les recommandations sont-elles appliquées en pratique clinique quotidienne ?

Contexte : La fibrose pulmonaire idiopathique (FPI) est une pneumopathie infiltrante diffuse d'étiologie inconnue touchant principalement des personnes âgées de 60 à 70 ans. Elle se caractérise par une destruction irréversible du parenchyme pulmonaire avec péjoration progressive de la fonction respiratoire. Des directives internationales concernant le diagnostic et la prise en charge de la FPI ont été publiées pour la première fois en 2000 et mises à jour en 2011. L'adhérence aux directives a été précédemment évaluée au moyen d'enquêtes sur les pratiques des médecins, mais jamais par des séries de cas. Méthodes : Analyse rétrospective des processus diagnostiques et de l'adhérence aux directives chez une série de patients diagnostiqués avec FPI après la publication des directives de 2000 (avant la mise à jour de 2011). Les données ont été récoltées précédemment par un groupe de travail suisse (SIOLD). Résultats : Les cas ont été rapportés par 19 institutions (incluant 4 hôpitaux universitaires) ou médecins de 9 cantons différents. Parmi 92 patients avec un diagnostic de FPI (hommes 70%, âge médian 72 ans, médiane de la capacité vitale forcée initiale 84%, médiane du facteur de transfert du monoxyde de carbone initial 53%), seuls 26% remplissaient tous les critères diagnostiques de 2000, alors que 49% ne remplissaient pas tous les critères requis et 25% avaient des caractéristiques considérées comme incompatibles avec une FPI. Des taux similaires ont été trouvés pour l'adhérence aux directives de 2011. 30% des patients ont eu une biopsie pulmonaire chirurgicale. Ces derniers étaient significativement plus jeunes (66 vs 75 ans, p<0.001). La biopsie pulmonaire chirurgicale était moins fréquente lorsque les caractéristiques typiques de la FPI étaient présentes à l'imagerie thoracique (20 vs 60%, p=0.007). 62% des cas ont été diagnostiqués en pratique privée ou dans un hôpital régional, et 33% des cas ont été diagnostiqués dans un service hospitalier de pneumologie. Seuls 54% des patients ont été évalués par un centre de soins tertiaire. Une évaluation multidisciplinaire formelle n'a eu lieu que dans 13% des cas. Conclusions : Les critères diagnostiques n'étaient souvent pas remplis. Comme recommandé, la biopsie pulmonaire était plus souvent réalisée lorsque l'imagerie n'était pas typique pour la FPI. L'évaluation multidisciplinaire ainsi que l'évaluation par un centre de soins tertiaire doivent être encouragées

Equalization Reserves for Natural Catastrophes and Shareholder Value: a Simulation Study

This paper investigates the effects on the company value for shareholders of keeping equalization reserves for catastrophic risk in an insurance company. We perform an extensive simulation study to compare the performance of the company with and without equalization reserves for several standard profitability measures. Equalization reserves turn out to be beneficial for shareholders in terms of the resulting expected Sharpe ratio and also with respect to the value of the call option on assets at some reasonably large maturity time. Moreover, the expected total discounted tax payments are not smaller when using equalization reserves. The results are robust with respect to model parameters such as interest rate, time horizon, cost of raising capital and business cycle dynamics

Embolies pulmonaires tumorales [Pulmonary tumor embolism]

Pulmonary tumor embolism is characterized by the occlusion of pulmonary vessels by tumor clots, which can be found in the proximal arteries (macro-embolism) or the small vessels (micro-embolism). The clinical presentation is mainly a progressive dyspnea associated with pulmonary hypertension and subacute cor pulmonale. The diagnosis is difficult, mostly made post-mortem. It is rarely obtained through a combination of multiple diagnostic tests (chest CT, ventilation-perfusion scanning, pulmonary artery cytology, biopsy). Treatment is based on the one of the underlying cancer. The prognosis is poor, and patients usually die within weeks to months. It is a rare cause of pulmonary hypertension that must be considered even without a prior oncological diagnosis

Human HELB is a processive motor protein that catalyzes RPA clearance from single-stranded DNA

Human DNA helicase B (HELB) is a poorly characterized helicase suggested to play both positive and negative regulatory roles in DNA replication and recombination. In this work, we used bulk and single-molecule approaches to characterize the biochemical activities of HELB protein with a particular focus on its interactions with Replication Protein A (RPA) and RPA–single-stranded DNA (ssDNA) filaments. HELB is a monomeric protein that binds tightly to ssDNA with a site size of ∼20 nucleotides. It couples ATP hydrolysis to translocation along ssDNA in the 5′ to 3′ direction accompanied by the formation of DNA loops. HELB also displays classical helicase activity, but this is very weak in the absence of an assisting force. HELB binds specifically to human RPA, which enhances its ATPase and ssDNA translocase activities but inhibits DNA unwinding. Direct observation of HELB on RPA nucleoprotein filaments shows that translocating HELB concomitantly clears RPA from ssDNA. This activity, which can allow other proteins access to ssDNA intermediates despite their shielding by RPA, may underpin the diverse roles of HELB in cellular DNA transactions.[Significance] Single-stranded DNA (ssDNA) is a key intermediate in many cellular DNA transactions, including DNA replication, repair, and recombination. Nascent ssDNA is rapidly bound by the Replication Protein A (RPA) complex, forming a nucleoprotein filament that both stabilizes ssDNA and mediates downstream processing events. Paradoxically, however, the very high affinity of RPA for ssDNA may block the recruitment of further factors. In this work, we show that RPA–ssDNA nucleoprotein filaments are specifically targeted by the human HELB helicase. Recruitment of HELB by RPA–ssDNA activates HELB translocation activity, leading to processive removal of upstream RPA complexes. This RPA clearance activity may underpin the diverse roles of HELB in replication and recombination.Work in the laboratory of M.S.D. was supported by an Elizabeth Blackwell Early Career Fellowship from the University of Bristol (to O.J.W.) and Wellcome Trust Investigator Grant 100401/Z/12/Z (to M.S.D.). Work in the laboratory of E.A. was supported by NIH Grants GM130746 (to E.A.) and GM133967 (to E.A.). F.M.-H. acknowledges support from the European Research Council under European Union Horizon 2020 Research and Innovation Program Grant Agreement 681299. Work in the laboratory of F.M.-H. was also supported by Spanish Ministry of Science and Innovation Grants BFU2017-83794-P (AEI/FEDER, UE; to F.M.-H.) and PID2020-112998GB-100 (AEI/10.13039/501100011033; to F.M.-H.) and Comunidad de Madrid Grants Tec4-Bio–S2018/NMT-4443 (to F.M.-H.) and NanoBioCancer–Y2018/BIO-4747 (to F.M.-H.)

Lessons Learned From Interdisciplinary Efforts to Combat COVID-19 Misinformation: Development of Agile Integrative Methods From Behavioral Science, Data Science, and Implementation Science

BACKGROUND: Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals\u27 preventive behaviors, including masking, testing, and vaccine uptake. OBJECTIVE: In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation. METHODS: We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a novel methodological framework, comprising qualitative inquiry, computational methods, and quantitative network models to analyze publicly available social media data sets to model content-specific misinformation dynamics and guide content tailoring efforts. As part of community needs assessment, we conducted 11 semistructured interviews, 4 listening sessions, and 3 focus groups with community scientists. Further, we used our data repository with 416,927 COVID-19 social media posts to gather information diffusion patterns through digital channels. RESULTS: Our results from community needs assessment revealed the complex intertwining of personal, cultural, and social influences of misinformation on individual behaviors and engagement. Our social media interventions resulted in limited community engagement and indicated the need for consumer advocacy and influencer recruitment. The linking of theoretical constructs underlying health behaviors to COVID-19-related social media interactions through semantic and syntactic features using our computational models has revealed frequent interaction typologies in factual and misleading COVID-19 posts and indicated significant differences in network metrics such as degree. The performance of our deep learning classifiers was reasonable, with an F-measure of 0.80 for speech acts and 0.81 for behavior constructs. CONCLUSIONS: Our study highlights the strengths of community-based field studies and emphasizes the utility of large-scale social media data sets in enabling rapid intervention tailoring to adapt grassroots community interventions to thwart misinformation seeding and spread among minority communities. Implications for consumer advocacy, data governance, and industry incentives are discussed for the sustainable role of social media solutions in public health

Measuring and controlling medical record abstraction (MRA) error rates in an observational study.

BACKGROUND: Studies have shown that data collection by medical record abstraction (MRA) is a significant source of error in clinical research studies relying on secondary use data. Yet, the quality of data collected using MRA is seldom assessed. We employed a novel, theory-based framework for data quality assurance and quality control of MRA. The objective of this work is to determine the potential impact of formalized MRA training and continuous quality control (QC) processes on data quality over time. METHODS: We conducted a retrospective analysis of QC data collected during a cross-sectional medical record review of mother-infant dyads with Neonatal Opioid Withdrawal Syndrome. A confidence interval approach was used to calculate crude (Wald\u27s method) and adjusted (generalized estimating equation) error rates over time. We calculated error rates using the number of errors divided by total fields ( all-field error rate) and populated fields ( populated-field error rate) as the denominators, to provide both an optimistic and a conservative measurement, respectively. RESULTS: On average, the ACT NOW CE Study maintained an error rate between 1% (optimistic) and 3% (conservative). Additionally, we observed a decrease of 0.51 percentage points with each additional QC Event conducted. CONCLUSIONS: Formalized MRA training and continuous QC resulted in lower error rates than have been found in previous literature and a decrease in error rates over time. This study newly demonstrates the importance of continuous process controls for MRA within the context of a multi-site clinical research study