72 research outputs found
The Introduction of the “Balanced Budget” Principle into the Italian Constitution: What Perspectives for the Financial Autonomy of Regional and Local Governments?
This paper analyses the impact on regional and local authorities of Articles 117 and 119 of the Italian Constitution as amended by Constitutional Law no. 1/2012.
In particular, it attempts to verify whether the new formulation of these constitutional provisions materializes the risk of a significant reduction in the financial autonomy of both Regions and Local Governments.
With the constitutional reform the legislative competence of “harmonization of public account” has become an exclusive State competence, the “balanced budget” principle has been extended to Regions and local authorities and public borrowing has been broadly prohibited.
What is the actual significance of the changes introduced by Constitutional Law no. 1/2012 for the financial autonomy of Italian sub-national authorities?
Is it time to recognise that the goals of financial independence of Italian fiscal federalism, launched by the reform of Title V of the IC, must give way to a new organization of public finance, where a central role is played by the central government in order to comply with the financial constraints arising from new challenges of the European economic integration process
Erratum to: Long-acting methylphenidate formulations in the treatment of attention-deficit/hyperactivity disorder: a systematic review of head-to-head studies
Validation of the Quantitative Checklist for Autism in Toddlers in an Italian Clinical Sample of Young Children With Autism and Other Developmental Disorders.
Background: The Quantitative Checklist for Autism in Toddlers (Q-CHAT) is parent-report screening questionnaire for detecting threshold and sub-threshold autistic features in toddlers. The Q-CHAT is a dimensional measure normally distributed in the general population sample and is able to differentiate between a group of children with a diagnosis of autism and unselected toddlers. Objectives: We aim to investigate the psychometric properties, score distribution, and external validity of the Q-CHAT in an Italian clinical sample of young children with autism versus children with developmental delay and typically developing children. Method: N = 126 typically developing children (TD), n = 139 children with autism, and n = 50 children presenting developmental delay (DD) were administered the Q-CHAT. Standardized measures of cognitive functions, language, and behaviors were also obtained. Results: The Q-CHAT scores were normally distributed and demonstrated adequate internal consistency and good item to total score correlations. The mean Q-CHAT score in the autism group was significantly higher than those found in the DD sample and TD children. No difference on the mean Q-CHAT score between DD and TD children was found. The accuracy of the Q-CHAT to discriminate between autism and TD was very good. Two different cut-points (27 and 31, respectively) maximized sensitivity and specificity for autism versus TD and DD, respectively. Finally, higher Q-CHAT scores were correlated with lower language and social communication skills. Conclusions: In clinical settings, the Q-CHAT demonstrated good psychometric properties and external validity to discriminate autism children not just from children with typical development but also from children with developmental delay
1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome
We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers
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Use of Machine Learning to Investigate the Quantitative Checklist for Autism in Toddlers (Q-CHAT) towards Early Autism Screening.
In the past two decades, several screening instruments were developed to detect toddlers who may be autistic both in clinical and unselected samples. Among others, the Quantitative CHecklist for Autism in Toddlers (Q-CHAT) is a quantitative and normally distributed measure of autistic traits that demonstrates good psychometric properties in different settings and cultures. Recently, machine learning (ML) has been applied to behavioral science to improve the classification performance of autism screening and diagnostic tools, but mainly in children, adolescents, and adults. In this study, we used ML to investigate the accuracy and reliability of the Q-CHAT in discriminating young autistic children from those without. Five different ML algorithms (random forest (RF), naĂŻve Bayes (NB), support vector machine (SVM), logistic regression (LR), and K-nearest neighbors (KNN)) were applied to investigate the complete set of Q-CHAT items. Our results showed that ML achieved an overall accuracy of 90%, and the SVM was the most effective, being able to classify autism with 95% accuracy. Furthermore, using the SVM-recursive feature elimination (RFE) approach, we selected a subset of 14 items ensuring 91% accuracy, while 83% accuracy was obtained from the 3 best discriminating items in common to ours and the previously reported Q-CHAT-10. This evidence confirms the high performance and cross-cultural validity of the Q-CHAT, and supports the application of ML to create shorter and faster versions of the instrument, maintaining high classification accuracy, to be used as a quick, easy, and high-performance tool in primary-care settings
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Use of Machine Learning to Investigate the Quantitative Checklist for Autism in Toddlers (Q-CHAT) towards Early Autism Screening.
Evaluation of acute cardiovascular effects of immediate-release methylphenidate in children and adolescents with attention-deficit hyperactivity disorder
The Impact of Methylphenidate on Pubertal Maturation and Bone Age in ADHD Children and Adolescents:Results from the ADHD Drugs Use Chronic Effects (ADDUCE) Project
Objective: The short-term safety of methylphenidate (MPH) has been widely demonstrated; however the long-term safety is less clear. The aim of this study was to investigate the safety of MPH in relation to pubertal maturation and to explore the monitoring of bone age.Method: Participants from ADDUCE, a two-year observational longitudinal study with three parallel cohorts (MPH group, no-MPH group, and a non-ADHD control group), were compared with respect to Tanner staging. An Italian subsample of medicated-ADHD was further assessed by the monitoring of bone age.Results: The medicated and unmedicated ADHD groups did not differ in Tanner stages indicating no higher risk of sexual maturational delay in the MPH-treated patients. The medicated subsample monitored for bone age showed a slight acceleration of the bone maturation after 24 months, however their predicted adult height remained stable.Conclusion: Our results do not suggest safety concerns on long-term treatment with MPH in relation to pubertal maturation and growth.</p
The Impact of Methylphenidate on Pubertal Maturation and Bone Age in ADHD Children and Adolescents:Results from the ADHD Drugs Use Chronic Effects (ADDUCE) Project
Objective: The short-term safety of methylphenidate (MPH) has been widely demonstrated; however the long-term safety is less clear. The aim of this study was to investigate the safety of MPH in relation to pubertal maturation and to explore the monitoring of bone age.Method: Participants from ADDUCE, a two-year observational longitudinal study with three parallel cohorts (MPH group, no-MPH group, and a non-ADHD control group), were compared with respect to Tanner staging. An Italian subsample of medicated-ADHD was further assessed by the monitoring of bone age.Results: The medicated and unmedicated ADHD groups did not differ in Tanner stages indicating no higher risk of sexual maturational delay in the MPH-treated patients. The medicated subsample monitored for bone age showed a slight acceleration of the bone maturation after 24 months, however their predicted adult height remained stable.Conclusion: Our results do not suggest safety concerns on long-term treatment with MPH in relation to pubertal maturation and growth.</p
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