Testing reinforcement learning explainability methods in a multi-agent cooperative environment

The adoption of algorithms based on Artificial Intelligence (AI) has been rapidly increasing during the last years. However, some aspects of AI techniques are under heavy scrutiny. For instance, in many cases, it is not clear whether the decisions of an algorithm are well-informed and reliable. Having an answer to these concerns is crucial in many domains, such as those in were humans and intelligent agents must cooperate in a shared environment. In this paper, we introduce an application of an explainability method based on the creation of a Policy Graph (PG) based on discrete predicates that represent and explain a trained agent’s behaviour in a multi-agent cooperative environment. We also present a method to measure the similarity between the explanations obtained and the agent’s behaviour, by building an agent with a policy based on the PG and comparing the behaviour of the two agents.This work has been partially supported by the H2020 knowlEdge European project (Grant agreement ID: 957331).Peer ReviewedPostprint (published version

Explainable agents adapt to human behaviour

When integrating artificial agents into physical or digital environments that are shared with humans, agents are often equipped with opaque Machine Learning methods to enable adapting their behaviour to dynamic human needs and environment. This brings about agents that are also opaque and therefore hard to explain. In previous work, we show that we can reduce an opaque agent into an explainable Policy Graph (PG) which works accurately in multi-agent environments. Policy Graphs are based on a discretisation of the world into propositional logic to identify states, and the choice of which discretiser to apply is key to the performance of the reduced agent. In this work, we explore this further by 1) reducing a single agent into an explainable PG, and 2) enforcing collaboration between this agent and an agent trained from human behaviour. The human agent is computed by using GAIL from a series of human-played episodes, and kept unchanged. We show that an opaque agent created and trained to collaborate with the human agent can be reduced to an explainable, non-opaque PG, so long as predicates regarding collaboration are included in the state representation, by showing the difference in reward between the agent and its PG. Code is available at https://github.com/HPAI-BSC/explainable-agents-with-humansThis work has been partially supported by EU Horizon 2020 Project StairwAI (grant agreement No. 101017142).Peer ReviewedPostprint (published version

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis

Background: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with COVID-19-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior non-invasive respiratory support on outcomes. Methods: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICU) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of intensive care unit (ICU) admission. Propensity score (PS) matching was used to achieve balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different timepoint (48 h from ICU admission) for early and delayed intubation. Results: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After PS matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%, p =0.01), ICU mortality (25.7% versus 36.1%, p=0.007) and 90-day mortality (30.9% versus 40.2%, p=0.02) when compared to the early intubation group. Very similar findings were observed when we used a 48-hour timepoint for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth wave, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (n=294) who were intubated earlier. The subgroup of patients undergoing NIV (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. Conclusions: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received high-flow nasal cannula.Financial support was provided by the Instituto de Salud Carlos III de Madrid (COV20/00110, ISCIII), Fondo Europeo de Desarrollo Regional (FEDER), "Una manera de hacer Europa", and the Centro de Investigación Biomedica En Red – Enfermedades Respiratorias (CIBERES). DdGC has received financial support from the Instituto de Salud Carlos III (Miguel Servet 2020: CP20/00041), co-funded by European Social Fund (ESF)/”Investing in your future”.Peer ReviewedArticle signat per 70 autors/es: Jordi Riera*1,2; Enric Barbeta*2,3,4; Adrián Tormos5; Ricard Mellado-Artigas2,3; Adrián Ceccato6; Anna Motos4; Laia Fernández-Barat4; Ricard Ferrer1; Darío García-Gasulla5; Oscar Peñuelas7; José Ángel Lorente7; Rosario Menéndez8; Oriol Roca1,2; Andrea Palomeque4,9; Carlos Ferrando2,3; Jordi SoléViolán10; Mariana Novo11; María Victoria Boado12; Luis Tamayo13; Ángel Estella14, Cristóbal Galban15; Josep Trenado16; Arturo Huerta17; Ana Loza18; Luciano Aguilera19; José Luís García Garmendia20; Carme Barberà21; Víctor Gumucio22; Lorenzo Socias23; Nieves Franco24; Luis Jorge Valdivia25; Pablo Vidal26; Víctor Sagredo27; Ángela Leonor Ruiz-García28; Ignacio Martínez Varela29; Juan López30; Juan Carlos Pozo31; Maite Nieto32; José M Gómez33; Aaron Blandino34; Manuel Valledor35; Elena Bustamante-Munguira36; Ángel Sánchez-Miralles37; Yhivian Peñasco38; José Barberán39; Alejandro Ubeda40; Rosario Amaya-Villar41; María Cruz Martín42; Ruth Jorge43; Jesús Caballero44; Judith Marin45; José Manuel Añón46; Fernando Suárez Sipmann47; Guillermo Muñiz2,48;Álvaro Castellanos-Ortega49; Berta Adell-Serrano50; Mercedes Catalán51; Amalia Martínez de la Gándara52; Pilar Ricart53; Cristina Carbajales54; Alejandro Rodríguez55; Emili Díaz6; Mari C de la Torre56; Elena Gallego57; Luisa Cantón-Bulnes58; Nieves Carbonell59, Jessica González60, David de Gonzalo-Calvo60, Ferran Barbé60 and Antoni Torres2,4,9 on behalf of the CiberesUCICOVID Consortium. // 1. Critical Care Department, Hospital Universitari Vall d’Hebron; SODIR, Vall d’Hebron Institut de Recerca, Barcelona, Spain. 2. CIBER de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain. 3.Surgical Intensive Care Unit, Hospital Clínic de Barcelona, Barcelona, Spain. 4. Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), University of Barcelona (UB), Barcelona, Spain. 5. Barcelona Supercomputing Center (BSC), Barcelona, Spain. 6. Critical Care Center, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí I3PT, Sabadell, Spain. Universitat Autonoma de Barcelona (UAB), Spain. 7. Hospital Universitario de Getafe, Universidad Europea, Madrid, Spain. 8. Pneumology Department, Hospital Universitario y Politécnico La Fe/Instituto de Investigación Sanitaria (IIS) La Fe, 46026 Valencia, Spain; Pneumology Department, Hospital Universitario y Politécnico La Fe, Avda, Fernando Abril Martorell 106, 46026 Valencia, Spain. 9.Respiratory Intensive Care Unit, Hospital Clínic de Barcelona, Barcelona, Spain. 10. Critical Care Department, Hospital Dr. Negrín Gran Canaria. Universidad Fernando Pessoa. Las Palmas, Gran Canaria, Spain. 11. Servei de Medicina Intensiva, Hospital Universitari Son Espases, Palma de Mallorca, Illes Balears, Spain. 12. Hospital Universitario de Cruces, Barakaldo, Spain. 13. Critical Care Department, Hospital Universitario Río Hortega de Valladolid, Valladolid, Spain. 14. Departamento Medicina Facultad Medicina Universidad de Cádiz. Hospital Universitario de Jerez, Jerez de la Frontera, Spain. 15. Department of Medicine, CHUS, Complejo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain. 16. Servicio de Medicina Intensiva, Hospital Universitario Mútua de Terrassa, Terrassa, Barcelona, Spain. 17. Pulmonary and Critical Care Division; Emergency Department, Clínica Sagrada Família, Barcelona, Spain. 18. Hospital Virgen de Valme, Sevilla, Spain. 19. Hospital de Basurto, Bilbao, Spain. 20. Intensive Care Unit, Hospital San Juan de Dios del Aljarafe, Bormujos, Sevilla, Spain. 21. Hospital Santa Maria; IRBLleida, Lleida, Spain. 22. Department of Intensive Care. Hospital Universitari de Bellvitge, L’Hospitalet de Llobregat, Barcelona, Spain. Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain. 23. Intensive Care Unit, Hospital Son Llàtzer, Palma de Mallorca, Illes Balears, Spain. 24. Hospital Universitario de Móstoles, Madrid, Spain. 25. Hospital Universitario de León, León, Spain. 26. Complexo Hospitalario Universitario de Ourense, Ourense, Spain. 27. Hospital Universitario de Salamanca, Salamanca, Spain. 28. Servicio de Microbiología Clínica, Hospital Universitario Príncipe de Asturias – Departamento de Biomedicina y Biotecnología, Universidad de Alcalá de Henares, Madrid, Spain. 29. Critical Care Department, Hospital Universitario Lucus Augusti, Lugo, Spain. 30. Complejo Asistencial Universitario de Palencia, Palencia, Spain. 31. UGC-Medicina Intensiva, Hospital Universitario Reina Sofia, Instituto Maimonides IMIBIC, Córdoba, Spain. 32. Hospital Universitario de Segovia, Segovia, Spain. 33. Hospital General Universitario Gregorio Marañón, Madrid, Spain. 34. Servicio de Medicina Intensiva, Hospital Universitario Ramón y Cajal, Madrid, Spain. 35. Hospital Universitario "San Agustín", Avilés, Spain. 36. Department of Intensive Care Medicine, Hospital Clínico Universitario Valladolid, Valladolid, Spain. 37. Servicio de Medicina Intensiva. Hospital Universitario Sant Joan d´Alacant, Alicante, Spain. 38. Servicio de Medicina Intensiva, Hospital Universitario Marqués de Valdecilla, Santander, Spain. 39. Hospital Universitario HM Montepríncipe, Universidad San Pablo-CEU, Madrid, Spain. 40. Servicio de Medicina Intensiva, Hospital Punta de Europa, Algeciras, Spain. 41. Intensive Care Clinical Unit, Hospital Universitario Virgen de Rocío, Sevilla, Spain. 42. Hospital Universitario Torrejón- Universidad Francisco de Vitoria, Madrid, Spain. 43. Intensive Care Department, Hospital Nuestra Señora de Gracia, Zaragoza, Spain. 44. Critical Care Department, Hospital Universitari Arnau de Vilanova; IRBLleida, Lleida, Spain. 45. Critical Care Department, Hospital del Mar-IMIM, Barcelona, Spain. 46. Hospital Universitario la Paz, Madrid, Spain. 47. Intensive Care Unit, Hospital Universitario La Princesa, Madrid, Spain. 48. Departamento de Biología Funcional. Instituto Universitario de Oncología del Principado de Asturias, Universidad de Oviedo; Instituto de Investigación Sanitaria del Principado de Asturias, Hospital Central de Asturias, Oviedo, Spain. 49. Hospital Universitario y Politécnico la Fe, Valencia, Spain. 50. Hospital de Tortosa Verge de la Cinta, Tortosa, Tarragona, Spain. 51. Department of Intensive Care Medicine, Hospital Universitario 12 de Octubre, Madrid, Spain. 52. Hospital Universitario Infanta Leonor, Madrid, Spain. 53. Servei de Medicina Intensiva, Hospital Universitari Germans Trias, Badalona, Spain. 54. Intensive Care Unit, Hospital Álvaro Cunqueiro, Vigo, Spain. 55. Hospital Universitari Joan XXIII de Tarragona, Tarragona, Spain. 56. Hospital de Mataró de Barcelona, Spain. 57. Unidad de Cuidados Intensivos, Hospital Universitario San Pedro de Alcántara, Cáceres, Spain. 58. Unidad de Cuidados Intensivos, Hospital Virgen Macarena, Sevilla, Spain. 59. Intensive Care Unit, Hospital Clínico y Universitario de Valencia, Valencia, Spain. 60. Translational Research in Respiratory Medicine, Respiratory Department, Hospital Universitari Aranu de Vilanova and Santa Maria, IRBLleida, Lleida, Spain.Postprint (published version

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic : a matched analysis

The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with COVID-19-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior non-invasive respiratory support on outcomes. This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICU) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of intensive care unit (ICU) admission. Propensity score (PS) matching was used to achieve balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different timepoint (48 h from ICU admission) for early and delayed intubation. Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After PS matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%, p =0.01), ICU mortality (25.7% versus 36.1%, p=0.007) and 90-day mortality (30.9% versus 40.2%, p=0.02) when compared to the early intubation group. Very similar findings were observed when we used a 48-hour timepoint for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth wave, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (n=294) who were intubated earlier. The subgroup of patients undergoing NIV (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received high-flow nasal cannul

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Labour and social security law in Spain in 2015

El informe ha sido elaborado por la Sección Juvenil de la Asociación Española de Derecho del Trabajo y Seguridad SocialEste Informe deja constancia de los cambios normativos más relevantes y de las tendencias judiciales más paradigmáticas del ordenamiento laboral en 2015. En él se observa el imparable dinamismo del Derecho del Trabajo y de la Seguridad Social en España. El documento, consciente de tal mutabilidad, recoge una minuciosa selección de cuestiones esenciales, a juicio de las personas que abordan cada una de las materias, de las que son especialistas; los autores y las autoras, que forman parte de la Sección Juvenil de la Asociación Española de Derecho del Trabajo y de la Seguridad Social, se adscriben a los grupos temáticos por afinidad con sus principales líneas de investigación y su labor docente universitaria. En síntesis, en el Informe “El Derecho del Trabajo y de la Seguridad Social en España en 2015” se puede encontrar información muy útil para los profesionales del iuslaboralismo en materia de derechos fundamentales inespecíficos, contratación laboral y empleo, vicisitudes del contrato de trabajo, derechos colectivos, igualdad y corresponsabilidad, Seguridad Social o prevención de riesgos laborales.This report has as aim leaving a record of the most relevant normative changes and the most paradigmatic judicial trends in Labour Law in 2015. One can easily observe the unstoppable dynamismof Labour and Social Security Law in Spain. The document, conscious of that mutability, collects a thorough selection of key issues, according to the judgement of the authors, all of them specialists and all of them members of the Young Scholars’ Section of the Spanish Association for Labour and Social Security Law. They are part of thematic groups, linked to their main research lines and their teaching task. Summing up, in this report “Labour and Social Security Law in Spain in 2015”, one can easily find useful information for labour lawyers in subjects such as unspecific fundamental rights, work contracts and employment, issues of the labour relationship, collective rights, equality and co-responsibility, Social Security or occupational risk prevention

El Derecho del Trabajo y de la Seguridad Social en España en 2015. Sección Juvenil de la Asociación Española de Derecho del Trabajo y de la Seguridad Social.

Este Informe deja constancia de los cambios normativos más relevantes y de las tendencias judiciales más paradigmáticas del ordenamiento laboral en 2015. En él se observa el imparable dinamismo del Derecho del Trabajo y de la Seguridad Social en España. El documento, consciente de tal mutabilidad, recoge una minuciosa selección de cuestiones esenciales, a juicio de las personas que abordan cada una de las materias, de las que son especialistas; los autores y las autoras, que forman parte de la Sección Juvenil de la Asociación Española de Derecho del Trabajo y de la Seguridad Social, se adscriben a los grupos temáticos por afinidad con sus principales líneas de investigación y su labor docente universitaria. En síntesis, en el Informe “El Derecho del Trabajo y de la Seguridad Social en España en 2015” se puede encontrar información muy útil para los profesionales del iuslaboralismo en materia de derechos fundamentales inespecíficos, contratación laboral y empleo, vicisitudes del contrato de trabajo, derechos colectivos, igualdad y corresponsabilidad, Seguridad Social o prevención de riesgos laborales. This report has as aim leaving a record of the most relevant normative changes and the most paradigmatic judicial trends in Labour Law in 2015. One can easily observe the unstoppable dynamismof Labour and Social Security Law in Spain. The document, conscious of that mutability, collects a thorough selection of key issues, according to the judgement of the authors, all of them specialists and all of them members of the Young Scholars’ Section of the Spanish Association for Labour and Social Security Law. They are part of thematic groups, linked to their main research lines and their teaching task. Summing up, in this report “Labour and Social Security Law in Spain in 2015”, one can easily find useful information for labour lawyers in subjects such as unspecific fundamental rights, work contracts and employment, issues of the labour relationship, collective rights, equality and co-responsibility, Social Security or occupational risk prevention

Collection, processing and analysis of heterogeneous data coming from Spanish hospitals in the context of COVID-19

The COVID-19 pandemic has already caused more than 150,000,000 cases worldwide. In Spain this has lead to a massive and simultaneous saturation of all sanitary regions. Coherently, the quick and consistent understanding of the COVID-19 disease requires of the combined analysis of thousands of medical records generated by dozens of different institutions. In the context of the publicly funded CIBERES-UCI-COVID project, we have gathered, cleaned and preprocessed data from heterogeneous sources – more than 30 hospitals, with different data entry systems – in order to produce a unified database, of more than 6.000 patients, that is used in several clinical studies being carried by different multidisciplinary groups. In this paper, we identify the complexities we encountered, the solutions we applied, and we summarise the statistical and machine learning techniques we have applied for the studies.Peer ReviewedPostprint (published version

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis

Background: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes. Methods: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation. Results: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observed when we used a 48-h time-point for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth waves, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (HFNC) (n=294) who were intubated earlier. The subgroup of patients undergoing noninvasive ventilation (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. Conclusions: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received HFNC