IRIS UniSR (’Università Vita-Salute San Raffaele)
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Nephrotoxicity in locally advanced head and neck cancer: when the end justifies the means to preserve nutritional status during chemoradiation
No full textCisplatin is a nephrotoxic agent able to damage renal function both in acute and chronic phases. Radiotherapy concomitant with cisplatin 100 mg/m2 given once every 3 weeks is the curative standard of care for locally advanced head and neck cancer. A prospective evaluation of a wide range of biochemical and anthropometrical parameters, handgrip strength, risk of malnutrition, visual analogue scale of appetite, and body composition was performed before, during, and after concomitant chemoradiotherapy in 60 consecutive patients affected by locally advanced head and neck cancer. The treatment dramatically influenced every clinical and laboratory parameter, especially regarding nutritional status despite a high protein intake. In terms of medium eGFR decay, chemoradiotherapy reduced the renal function of about 8 ml/min/1.73m2 in 6 weeks, harboring some cases of mild acute kidney injury and acute kidney disease. Furthermore, patients with eGFR < 60 mL/min/1.73m2 pre-treatment were just 3 (5%), becoming 5 (8.3%) at the end despite the high-protein diet implemented following ESPEN guidelines. The drop in eGFR did not correlate with weight loss during treatment or with anthropometric parameters pre and post. Nutritional counselling pre-, during, post-treatments plays a crucial role in preventing malnutrition and sarcopenia, leading to better oncological and nephrological outcomes too
Stratify and ImmunoWELL JCV tests performances in a real-world multiple sclerosis cohort: possible clinical implications of biosimilar Natalizumab use
No full textThe language of gait: interpreting emotional states through gait videos
No full textIntroduction: Gait integrates sensorimotor and affective processes, serving both locomotor function and emotional expression. This embodiment framework has clinical relevance in neurodegenerative disorders and suggests potential for emotion-based modulation of gait. Objectives: This study developed and tested a range of emotion-specific gait videos to assess whether healthy individuals could correctly recognize different emotions, in order to identify standardized stimuli for future research on emotion recognition and embodied simulation in neurological patients. Methods: We created a video questionnaire featuring an actress walking with gait patterns meant to convey eight emotions: happiness, surprise, fear, anxiety, disgust, sadness, anger, and neutral. Her facial expressions were either visible or blurred to focus attention on body movements. Participants selected the recognized emotion from a list and rated its valence and intensity. Recognition accuracy, specificity, sensitivity, valence, and intensity scores were used to identify the most effective video for each emotion. Results: 110 healthy subjects (aged 25-40 years) participated in the questionnaire. Most emotions-neutral, happiness, sadness, fear, and anger-were recognized with high accuracy (> 90%), specificity and sensitivity in blurred-face videos. Disgust and surprise were harder to identify, and anxiety was often confused with fear. Valence and intensity ratings aligned with the intended emotions for both blurred and visible faces, although they were generally higher for visible facial expressions. Conclusion: This study validates emotional gait videos as reliable stimuli for emotion recognition in healthy adults, laying the groundwork for their use in research on emotional embodiment in neurological disorders. These stimuli offer a tool for exploring emotion-gait interactions and developing emotion-based neurorehabilitation strategies
Etica tradizionale ed etica critica
No full textQuesto volume affronta la sfida di ripensare l’etica oltre i confini della sua tradizione teorica, proponendo una pro- spettiva critica radicata nelle pratiche sociali effettive e nelle relazioni di potere che le strutturano. L’etica critica qui delineata non si limita a valutare comportamenti o a risolvere dilemmi astratti, ma si propone come strumento di emancipazio- ne: un’indagine normativa sulle condizioni che ostacolano la pie- na realizzazione dell’essere umano, nelle sue molteplici forme di vita. A differenza dell’etica applicata, che tende ad assumere come neutre o immutabili le dinamiche sociali esistenti, l’etica critica smaschera le logiche di dominio sottese a tali dinamiche, ponendosi come leva per il cambiamento. Attraverso analisi che spaziano dall’intelligenza artificiale alla crisi ecologica, dal lavo- ro alle disuguaglianze di genere, il volume offre strumenti teorici e pratici per interpretare criticamente il presente e contribuire alla sua trasformazione
Fatal fall from a height: is it possible to apply artificial intelligence techniques for height estimation?
No full textFall from a height trauma is characterized by a multiplicity of injuries, related to multiple factors. The height of the fall is the factor that most influences the kinetic energy of the body and appears to be one of the factors that most affects the extent of injury. The purpose of this work is to evaluate, through machine learning algorithms, whether the autopsy injury pattern can be useful in estimating fall height. 455 victims of falls from a height which underwent a complete autopsy were retrospectively analyzed. The cases were enlisted by dividing them into 7 groups according to the height of the fall: 6 or less meters; 9 m, 12 m, 15 m, 18 m, 21 m, 24 m or more. Autoptic data were registered through the use of a previously published visceral and skeletal table. A total of 25 descriptors were used. Reduction of values in the range, standard and robust scaling were used as preprocessing methods. Principal Component Analysis, Single Value Decomposition and Independent Component Analysis were applied for dimensionality reduction. Cross validation was performed with 5 internal and external folds to ensure the validity of the results. The learning algorithms that generated the best models were Linear Regression, Support Vector Regressor, Kernel Ridge, Decision trees and Random forests. The best mean absolute error was 4.58 +/- 1.28 m when dimensionality reduction was applied. Without any dimensionality reduction, the best result was 4.37 +/- 1.27 m, suggesting a good performance of the proposed algorithms, with better performance when dimensionality is not automatically reduced.Fall from a height trauma is characterized by a multiplicity of injuries, related to multiple factors. The height of the fall is the factor that most influences the kinetic energy of the body and appears to be one of the factors that most affects the extent of injury. The purpose of this work is to evaluate, through machine learning algorithms, whether the autopsy injury pattern can be useful in estimating fall height. 455 victims of falls from a height which underwent a complete autopsy were retrospectively analyzed. The cases were enlisted by dividing them into 7 groups according to the height of the fall: 6 or less meters; 9 m, 12 m, 15 m, 18 m, 21 m, 24 m or more. Autoptic data were registered through the use of a previously published visceral and skeletal table. A total of 25 descriptors were used. Reduction of values in the range, standard and robust scaling were used as preprocessing methods. Principal Component Analysis, Single Value Decomposition and Independent Component Analysis were applied for dimensionality reduction. Cross validation was performed with 5 internal and external folds to ensure the validity of the results. The learning algorithms that generated the best models were Linear Regression, Support Vector Regressor, Kernel Ridge, Decision trees and Random forests. The best mean absolute error was 4.58 ± 1.28 m when dimensionality reduction was applied. Without any dimensionality reduction, the best result was 4.37 ± 1.27 m, suggesting a good performance of the proposed algorithms, with better performance when dimensionality is not automatically reduced
Impella Versus VA-ECMO for Patients with Cardiogenic Shock: Preliminary Cost-Effectiveness Analysis in the Italian Context
No full textIntroduction: Cardiogenic shock (CS) is a life-threatening failure of the heart to supply adequate blood, requiring immediate treatment. Although nowadays Impella® heart pumps and veno-arterial extra-corporeal membrane oxygenation (VA-ECMO) are both widely employed in routine clinical practice for the management of patients with CS, extensive comparative information on their cost-effectiveness is lacking. The aim of the present study was to conduct a cost-effectiveness analysis comparing Impella to VA-ECMO in patients with CS from the National Healthcare Service (NHS) perspective in Italy. A secondary objective was to compare costs from both NHS and hospital perspectives. Methods: A Markov model projected, on a lifetime horizon, life years (LYs), quality-adjusted life years (QALYs), and costs associated with Impella and VA-ECMO. Costs from the NHS perspective were estimated mainly through Italian reimbursement rates, while hospital costs were derived from a clinical center in Italy. Results: From an NHS perspective, Impella showed lower costs and better life expectancy and patients’ quality of life (€50,303, 1.544 LYs, 0.905 QALYs) compared to VA-ECMO (€76,795, 1.391 LYs, 0.784 QALYs). DRG overall reimbursements for Impella (€49,998) do not completely cover the hospital costs and the cost for the technology (€57,770). Conversely, the hospital cost for the strategy VA-ECMO (€52,190) is lower than the NHS overall reimbursements (€76,790). Conclusions: Our analysis suggests that Impella may be cost-saving over VA-ECMO, while also providing better health outcomes for patients with CS; however, discrepancies in costs and reimbursement rates were observed, likely due to variability in patient care and hospital resource utilization. Future real-world studies are needed to confirm these findings, but decision-makers can use this data as an initial reference for health technology assessments in Italy
Elements of a Radical Democracy.Kierkegaardian Sources to Hannah Arendt’s Political Theory
No full textThis paper delves into the enduring influence of Søren Kierkegaard’s philosophy on early 20th-century German thought, particularly into its political reading by Hannah Arendt. The investigation seeks to grasp the political potentials inherent in Kierkegaardian theological concepts, namely the construction of the single political subject in its engagement with the universal, and the deriving interplay between consensus and dissensus. Consequently, a Kierkegaardian political theology is outlined. The formal structure of the Kierkegaardian selfhood, as defined by its relationship with an unbounded entity, captivated the minds of various German philosophers in the first half of the 20th century (section 1). Arendt employs Kierkegaardian ideas to explore deeper the relationship between the political actor and the historical net of spontaneities (sections 2 and 3). Building upon this framework, the article examines how Arendt applies these ideas in her discussions of consensus and dissensus (section 4). Lastly, the article suggests how a Kierkegaardian political theology, as enriched through Arendtian insights, can actually strengthen the operation of a radical form of democracy in contemporary societies
Real-time coaching programs for Manage-How-You-Drive insurance schemes: Analysis of retention after feedback removal
No full textManage-How-You-Drive (MHYD) is an innovative usage-based insurance scheme where drivers are charged premiums based on their safety performance, incorporating real-time coaching programs to provide drivers with contingent feedback, nudging them to drive more safely. As limited research exists on these novel schemes, this study aims to confirm their effectiveness, by expanding the sample size and the scope of analysis from a previous study by the authors, and to specifically focus on the retention of improved behavior and the impact of driver characteristics and feedback types on retention. A driving simulator experiment involving 100 drivers was used to test four feedback systems, with different modality (auditory vs. visual) and valence (i.e., pleasantness of the feedback: positive vs. negative), based on the occurrence of Elevated Gravitational-Force Events (EGFEs, i.e., harsh acceleration/deceleration events). Drivers completed three trials, spaced four weeks apart. The first trial served as a baseline without any feedback, in the second trial one of the feedback systems was presented, and the third trial had no feedback. Program effectiveness and retention were assessed based on EGFE occurrences and mean acceleration/deceleration. Its indirect influence on speeding, tailgating, and lateral control was investigated to assess potential additional enduring effects on safety performance. Drivers, especially those identified as “aggressive” during the baseline trial, not only significantly benefited from using the coaching program, but were also able to at least partially retain such benefits in terms of acceleration/deceleration, speeding and tailgating, irrespective of feedback type. These findings highlight the potential practical advantages of MHYD real-time coaching systems for road safety
A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study
No full textBorderline personality disorder (BPD) is associated with a high risk of suicide. Despite several risk factors being known, identifying vulnerable patients in clinical practice remains a challenge so far. The current study aimed at predicting suicide attempts among BPD patients during disorder-specific psychotherapeutic interventions exploiting machine learning techniques. The study took into account several potential predictors relevant to BPD psychopathology: emotion dysregulation, temperamental and character factors, attachment style, impulsivity, and aggression. The sample included 69 patients with BPD who completed the Temperament and Character Inventory, Attachment Style Questionnaire, Difficulties in Emotion Regulation Scale, Barratt Impulsiveness Scale, and Aggression Questionnaire at baseline and after 6 months of psychotherapy. To detect future suicide attempts, baseline questionnaires were entered as predictors into an elastic net penalized regression, whose predictive performance was assessed through nested fivefold cross-validation. At the same time, 5000 iterations of a non-parametric bootstrap were used to determine predictors’ robustness. The elastic net model discriminating BPD suicide attempters from non-attempters reached a balanced accuracy of 64.09% and an area under the receiver operating curve of 70.44%. High preoccupation with relationships, harm avoidance, and reward dependence, along with low motor impulsiveness, verbal aggression, cooperativeness, and self-transcendence were the most contributing predictors. Our findings suggest that interpersonal vulnerability and internalizing factors are the strongest predictors of future suicide attempts in BPD. Machine learning on self-report psychological scales may be helpful to identify individuals at suicidal risk, potentially helping clinical settings to develop individualized preventive strategies
Contribution of Polygenic Scores to Progression Independent of Relapse Activity in Multiple Sclerosis
No full textBackground: Despite effective therapeutic control of relapses, many patients with multiple sclerosis (MS) experience, from the earliest phases of disease, disability accrual, which mostly occurs as progression independent of relapse activity (PIRA). In this observational study, we aimed at evaluating the genetic contribution to PIRA, using polygenic risk scores (PRS) in a cohort of 1162 Italian patients. Methods: PRS were derived from the largest multi-centric genome-wide association study on MS severity, conducted on more than 20,000 patients. The scores were computed at 5 p-value thresholds after a clumping procedure. Association with the rate of PIRA events was tested by fitting negative binomial regression models. Results: Analyses revealed a trend for association of PRS with the rate of PIRA events, which were significant in the subset of patients with age at onset ≤ 50 years (Rate Ratio = 1.148, 95% CI: 1.01 to 1.304, p = 0.0328). An interaction effect was identified between PRS and AAO, indicating a significant mild antagonistic effect (RRint = 0.98, 95% CI: 0.96 to 1.0, p = 0.033). Conclusions: Our results suggest an influence of severity-related genetic load on the rate of PIRA events, especially in subjects with disease onset before the age of 50 years, characterized by a less prominent effect of aging processes on disability accumulation. This finding supports previous observations from other studies of an age-dependent influence of genetic risk scores on complex traits