GLARE-SSCPM: an Intelligent System to Support the Treatment of Comorbid Patients

The development of software tools supporting physicians in the treatment of comorbid patients is a challenging goal and a hot topic in Medical Informatics and Artificial Intelligence. Computer Interpretable Guidelines (CIGs) are consolidated tools to support physicians with evidence-based recommendations in the treatment of patients affected by a specific disease. However, the applications of two or more CIGs on comorbid patients is critical, since dangerous interactions between (the effects of) actions from different CIGs may arise. GLARE-SSCPM is the first tool supporting, in an integrated way, (i) the knowledge-based detection of interactions, (ii) the management of the interactions, and (iii) the final merge of (part of) the CIGs operating on the patient. GLARE-SSCPM is characterized by being very supportive to physicians, providing them support for focusing, interaction detection, and for an hypothesize and test approach to manage the detected interactions. To achieve such goals, it provides advanced Artificial Intelligence techniques. Preliminary tests in the educational context, within the RoPHS project, have provided encouraging results

Minimally invasive spleen-preserving distal pancreatectomy: real-world data from the italian national registry of minimally invasive pancreatic surgery

Aim: Minimally invasive distal pancreatectomy has become the standard of care for benign and low malignant lesions. Spleen preservation in this setting has been proposed to reduce surgical trauma and long-term sequelae. The aim of the current study is to present real-world data on indications, techniques, and outcomes of spleen-preserving distal pancreatectomy (SPDP). Methods: Patients who underwent SPDP and distal pancreatectomy with splenectomy (DPWS) were extracted from the 2019-2022 Italian National Registry for Minimally Invasive Pancreatic Surgery (IGoMIPS). Perioperative and pathological data were collected. Results: One hundred and ten patients underwent SPDP and five hundred and seventy-eight underwent DPWS. Patients undergoing SPDP were significantly younger (56 vs. 63.5 years; P < 0.001). Seventy-six percent of SPDP cases were performed in six out of thirty-four IGoMIPS centers. SPDP was performed predominantly for Neuroendocrine Tumors (43.6% vs.23.5%; P < 0.001) and for smaller lesions (T1 57.6% vs. 29.8%; P < 0.001). The conversion rate was higher in the case of DPWS (7.6% vs. 0.9%; P = 0.006), even when pancreatic cancer was ruled out (5.0% vs. 0.9%; P = 0.045). The robotic approach was most commonly used for SPDP (50.9% vs. 29.7%; P < 0.001). No difference in postoperative outcomes and length of stay was observed between the two groups, as well as between robotic and laparoscopic approaches in the SPDP group. A trend toward a lower rate of postoperative sepsis was observed after SPDP (0.9% vs. 5.2%; P = 0.056). In 84.7% of SPDP, splenic vessels were preserved (Kimura procedure) without an impact on short-term postoperative outcomes. Conclusion: In this registry analysis, SPDP was feasible and safe. The Kimura procedure was prevalent over the Warshaw procedure. The typical patient undergoing SPDP was young with a neuroendocrine tumor at an early stage. Robotic assistance was used more frequently for SPDP than for DPWS

Linguistic profile automated characterisation in pluripotential clinical high-risk mental state (CHARMS) conditions: methodology of a multicentre observational study

Introduction: Language is usually considered the social vehicle of thought in intersubjective communications. However, the relationship between language and high- order cognition seems to evade this canonical and unidirectional description (ie, the notion of language as a simple means of thought communication). In recent years, clinical high at-risk mental state (CHARMS) criteria (evolved from the Ultra-High-Risk paradigm) and the introduction of the Clinical Staging system have been proposed to address the dynamicity of early psychopathology. At the same time, natural language processing (NLP) techniques have greatly evolved and have been successfully applied to investigate different neuropsychiatric conditions. The combination of at-risk mental state paradigm, clinical staging system and automated NLP methods, the latter applied on spoken language transcripts, could represent a useful and convenient approach to the problem of early psychopathological distress within a transdiagnostic risk paradigm. Methods and analysis: Help-seeking young people presenting psychological distress (CHARMS+/− and Clinical Stage 1a or 1b; target sample size for both groups n=90) will be assessed through several psychometric tools and multiple speech analyses during an observational period of 1-year, in the context of an Italian multicentric study. Subjects will be enrolled in different contexts: Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Section of Psychiatry, University of Genoa—IRCCS Ospedale Policlinico San Martino, Genoa, Italy; Mental Health Department—territorial mental services (ASL 3—Genoa), Genoa, Italy; and Mental Health Department—territorial mental services (AUSL—Piacenza), Piacenza, Italy. The conversion rate to full-blown psychopathology (CS 2) will be evaluated over 2 years of clinical observation, to further confirm the predictive and discriminative value of CHARMS criteria and to verify the possibility of enriching them with several linguistic features, derived from a fine-grained automated linguistic analysis of speech. Ethics and dissemination: The methodology described in this study adheres to ethical principles as formulated in the Declaration of Helsinki and is compatible with International Conference on Harmonization (ICH)-good clinical practice. The research protocol was reviewed and approved by two different ethics committees (CER Liguria approval code: 591/2020—id.10993; Comitato Etico dell’Area Vasta Emilia Nord approval code: 2022/0071963). Participants will provide their written informed consent prior to study enrolment and parental consent will be needed in the case of participants aged less than 18 years old. Experimental results will be carefully shared through publication in peer- reviewed journals, to ensure proper data reproducibility. Trial registration number DOI:10.17605/OSF.IO/BQZTN

Multilinguisme et variétés linguistiques en Europe à l’aune de l’intelligence artificielle Multilinguismo e variazioni linguistiche in Europa nell’era dell’intelligenza artificiale Multilingualism and Language Varieties in Europe in the Age of Artificial Intelligence

Il presente volume è il frutto di una riflessione interdisciplinare e multilingue maturata attorno a diversi eventi organizzati nell’ambito del panel concernente i diritti e le variazioni linguistiche in Europa nell’era dell’intelligenza artificiale all’interno del progetto Artificial Intelligence for European Integration, promosso dal Centro studi sull’Europa TO-EU dell’Università di Torino e cofinanziato dalla Commissione europea. L’interrogativo iniziale che abbiamo voluto sollevare è se l’IA potesse avere un impatto negativo sulle varietà linguistiche e sul multilinguismo, valore “aggiunto” dell’UE, o se potesse, e in che modo, divenire utile per la promozione di essi. Il volume, interamente inedito, può dirsi tra i primi ad affrontare, almeno in Europa, questo tipo di tematiche.This book is the outcome of an interdisciplinary multilingual reflection carried out on research into linguistic rights, multilingualism and language varieties in Europe in the age of artificial intelligence. It is part of the Artificial Intelligence for European Integration project, promoted by the Centre of European Studies To-EU of the University of Turin and co-financed by the European Commission. Our aim was to investigate more generally the negative and/or positive outcomes of AI on language varieties and multilingualism, the latter a key value for the EU. The result is a volume of original unpublished research being made generally available for the first time, at least in Europe.Ce livre a été élaboré à partir d’une réflexion interdisciplinaire et multilingue qui a été menée dans le cadre d’une recherche sur les droits, le multilinguisme et les variétés linguistiques en Europe à l’aune de l’intelligence artificielle à l’intérieur du projet Artificial Intelligence for European Integration promu par le Centre d’études européennes To-EU de l’Université de Turin et cofinancé par la Commission de l’Union européenne. Notre propos était de réfléchir plus généralement sur les conséquences négatives et/ou positives de l’IA sur les variétés linguistiques et le multilinguisme, ce dernier étant une valeur de l’UE. Ce que nous proposons par ce numéro est un livre inédit qui peut se vanter d’être parmi les premiers à s’occuper de ce type de thématique, du moins en Europe

Adherence to antibiotic treatment guidelines and outcomes in the hospitalized elderly with different types of pneumonia

Background: Few studies evaluated the clinical outcomes of Community Acquired Pneumonia (CAP), Hospital-Acquired Pneumonia (HAP) and Health Care-Associated Pneumonia (HCAP) in relation to the adherence of antibiotic treatment to the guidelines of the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) in hospitalized elderly people (65 years or older). Methods: Data were obtained from REPOSI, a prospective registry held in 87 Italian internal medicine and geriatric wards. Patients with a diagnosis of pneumonia (ICD-9 480-487) or prescribed with an antibiotic for pneumonia as indication were selected. The empirical antibiotic regimen was defined to be adherent to guidelines if concordant with the treatment regimens recommended by IDSA/ATS for CAP, HAP, and HCAP. Outcomes were assessed by logistic regression models. Results: A diagnosis of pneumonia was made in 317 patients. Only 38.8% of them received an empirical antibiotic regimen that was adherent to guidelines. However, no significant association was found between adherence to guidelines and outcomes. Having HAP, older age, and higher CIRS severity index were the main factors associated with in-hospital mortality. Conclusions: The adherence to antibiotic treatment guidelines was poor, particularly for HAP and HCAP, suggesting the need for more adherence to the optimal management of antibiotics in the elderly with pneumonia

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)