Deep learning of chest X‑rays can predict mechanical ventilation outcome in ICU‑admitted COVID‑19 patients

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk factors for COVID-19. It is proposed that image data, specifically bedside computed X-ray (CXR), provide additional predictive information on mortality following mechanical ventilation that can be incorporated in the guidelines. Deep transfer learning was used to extract convolutional features from a systematically collected, multi-institutional dataset of COVID-19 ICU patients. A model predicting outcome of mechanical ventilation (remission or mortality) was trained on the extracted features and compared to a model based on known, aggregated risk factors. The model reached a 0.702 area under the curve (95% CI 0.707-0.694) at predicting mechanical ventilation outcome from pre-intubation CXRs, higher than the risk factor model. Combining imaging data and risk factors increased model performance to 0.743 AUC (95% CI 0.746-0.732). Additionally, a post-hoc analysis showed an increase performance on high-quality than low-quality CXRs, suggesting that using only high-quality images would result in an even stronger model

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the course of the disease is closely linked to the outcome. As such, evaluation of future severity from current CXR would be highly desirable. We trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from an open-source dataset (COVID-19 image data collection) and from a multi-institutional local ICU dataset. The data was grouped into pairs of sequential CXRs and were categorized into three categories: 'Worse', 'Stable', or 'Improved' on the basis of radiological evolution ascertained from images and reports. Classical machine-learning algorithms were trained on the deep learning extracted features to perform immediate severity evaluation and prediction of future radiological trajectory. Receiver operating characteristic analyses and Mann-Whitney tests were performed. Deep learning predictions between "Worse" and "Improved" outcome categories and for severity stratification were significantly different for three radiological signs and one diagnostic ('Consolidation', 'Lung Lesion', 'Pleural effusion' and 'Pneumonia'; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between 'Worse' and 'Improved' cases with a 0.81 (0.74-0.83 95% CI) AUC in the open-access dataset and with a 0.66 (0.67-0.64 95% CI) AUC in the ICU dataset. Features extracted from the CXR could predict disease severity with a 52.3% accuracy in a 4-way classification. Severity evaluation trained on the COVID-19 image data collection had good out-of-distribution generalization when testing on the local dataset, with 81.6% of intubated ICU patients being classified as critically ill, and the predicted severity was correlated with the clinical outcome with a 0.639 AUC. CXR deep learning features show promise for classifying disease severity and trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions

Pour une démocratie socio-environnementale : cadre pour une plate-forme participative « transition écologique »

Contribution publiée in Penser une démocratie alimentaire Volume II – Proposition Lascaux entre ressources naturelles et besoins fondamentaux, F. Collart Dutilleul et T. Bréger (dir), Inida, San José, 2014, pp. 87-111.International audienceL’anthropocène triomphant actuel, avec ses forçages environnementaux et sociaux, est à l’origine de l’accélération des dégradations des milieux de vie sur Terre et de l’accentuation des tensions sociales et géopolitiques. Passer à un anthropocène de gestion équitable, informé et sobre vis-à-vis de toutes les ressources et dans tous les secteurs d’activité (slow anthropocene), impose une analyse préalable sur l’ensemble des activités et des rapports humains. Cette transition dite « écologique », mais en réalité à la fois sociétale et écologique, est tout sauf un ajustement technique de secteurs dits prioritaires et technocratiques. Elle est avant tout culturelle, politique et philosophique au sens propre du terme. Elle est un horizon pour des trajectoires de développement humain, pour des constructions sociales et économiques, censées redéfinir socialement richesse, bien-être, travail etc. La dénomination « transition écologique » est largement véhiculée, mais ses bases conceptuelles ne sont pas entièrement acquises ni même élaborées. Dans ce contexte, les étudiants en première année de Master BioSciences à l’Ecole Normale Supérieure (ENS) de Lyon ont préparé une première étude analytique de ce changement radical et global de société pour mieux comprendre dans quelle société ils souhaitent vivre, en donnant du sens aux activités humaines présentes et à venir. Une trentaine de dossiers sur divers secteurs d’activités et acteurs de la société ont été produits et ont servis de support à cette synthèse. Plus largement, le but est de construire un socle conceptuel et une plate-forme de travail sur lesquels les questions de fond, mais aussi opérationnelles, peuvent être posées et étudiées en permanence. Cette démarche participative est ouverte à la collectivité sur le site http://institutmichelserres.ens-lyon.fr/

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

IV. Les protégés de Théodora

Duchesne Louis. IV. Les protégés de Théodora. In: Mélanges d'archéologie et d'histoire, tome 35, 1915. pp. 57-79

Rapport adressé à l' Académie des Inscriptions et Belles-Lettres, par le directeur de l' Ecole française de Rome, sur la publication des registres pontificaux

Duchesne Louis. Rapport adressé à l' Académie des Inscriptions et Belles-Lettres, par le directeur de l' Ecole française de Rome, sur la publication des registres pontificaux. In: Bibliothèque de l'école des chartes. 1906, tome 67. pp. 352-357

Le Forum de Nerva et ses environs

Duchesne Louis. Le Forum de Nerva et ses environs. Notes sur la topographie de Rome au Moyen-Âge. IV.. In: , . Scripta Minora. Études de topographie romaine et de géographie ecclésiastique. Rome : École Française de Rome, 1973. pp. 73-82. (Publications de l'École française de Rome, 13

S. Maria antiqua

Duchesne Louis. S. Maria antiqua. Notes sur la topographie de Rome au Moyen-Âge. VIII.. In: Scripta Minora. Études de topographie romaine et de géographie ecclésiastique. Rome : École Française de Rome, 1973. pp. 141-165. (Publications de l'École française de Rome, 13-1

Les évêchés d'Italie et l'invasion lombarde (2e article)

Duchesne Louis. Les évêchés d'Italie et l'invasion lombarde (2e article). In: Mélanges d'archéologie et d'histoire, tome 25, 1905. pp. 365-399

Le Liber Pontificalis aux mains des Guibertistes et des Pierléonistes

Duchesne Louis. Le Liber Pontificalis aux mains des Guibertistes et des Pierléonistes. In: Mélanges d'archéologie et d'histoire, tome 38, 1920. pp. 165-193