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

Urinalysis parameters for predicting severity in coronavirus disease 2019 (COVID-19)

Urinalysis Parameters for Predicting Severity in Coronavirus Disease 2019 (COVID-19

Laboratory predictors of death from coronavirus disease 2019 (COVID-19) in the area of Valcamonica, Italy

Background Comprehensive information has been published on laboratory tests which may predict worse outcome in Asian populations with coronavirus disease 2019 (COVID-19). The aim of this study is to describe laboratory findings in a group of Italian COVID-19 patients in the area of Valcamonica, and correlate abnormalities with disease severity. Methods The final study population consisted of 144 patients diagnosed with COVID-19 (70 who died during hospital stay and 74 who survived and could be discharged) between March 1 and 30, 2020, in Valcamonica Hospital. Demographical, clinical and laboratory data were collected upon hospital admission and were then correlated with outcome (i.e. in-hospital death vs. discharge). Results Compared to patients who could be finally discharged, those who died during hospital stay displayed significantly higher values of serum glucose, aspartate aminotransferase (AST), creatine kinase (CK), lactate dehydrogenase (LDH), urea, creatinine, high-sensitivity cardiac troponin I (hscTnI), prothrombin time/international normalized ratio (PT/INR), activated partial thromboplastin time (APTT), D-dimer, C reactive protein (CRP), ferritin and leukocytes (especially neutrophils), whilst values of albumin, hemoglobin and lymphocytes were significantly decreased. In multiple regression analysis, LDH, CRP, neutrophils, lymphocytes, albumin, APTT and age remained significant predictors of in-hospital death. A regression model incorporating these variables explained 80% of overall variance of in-hospital death. Conclusions The most important laboratory abnormalities described here in a subset of European COVID-19 patients residing in Valcamonica are highly predictive of in-hospital death and may be useful for guiding risk assessment and clinical decision-making