Criteri di valutazione medico-legale della narcolessia

Impairment due to narcolepsy strongly limits job performance, but there are no standard criteria to assess disability in people with narcolepsy and a scale of disease severity is still lacking. We explored: 1. the interobserver reliability among Italian Medical Commissions making disability and handicap benefit decisions for people with narcolepsy, searching for correlations between the recognized disability degree and patients’ features; 2. the willingness to report patients to the driving licence authority; 3. possible sources of variance in judgement. Fifteen narcoleptic patients were examined by four Medical Commissions in simulated sessions. Raw agreement and interobserver reliability among Commissions were calculated for disability and handicap benefit decisions and for driving licence decisions. Levels of judgement differed on percentage of disability (p<0.001), severity of handicap (p=0.0007) and the need to inform the driving licence authority (p=0.032). Interobserver reliability ranged from Kappa = - 0.10 to Kappa = 0.35 for disability benefit decision and from Kappa = - 0.26 to Kappa = 0.36 for handicap benefit decision. The raw agreement on driving licence decision ranged from 73% to 100% (Kappa not calculable). Spearman’s correlation between percentages of disability and patients’ features showed correlations with age, daytime naps, sleepiness, cataplexy and quality of life. This first interobserver reliability study on social benefit decisions for narcolepsy shows the difficulty of reaching an agreement in this field, mainly due to variance in interpretation of the assessment criteria. The minimum set of indicators of disease severity correlating with patients’ self assessments encourages a disability classification of narcolepsy.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Sonic Hedgehog pathway impairment in Neural Precursor Cells of the Ts65Dn mouse, an animal model of Down syndrome

Mental retardation in Down syndrome (DS) has been imputed to the decreased brain volume, which is evident starting from the early phases of development. Recent studies in a widely used mouse model of DS, the Ts65Dn mouse, have shown that neurogenesis is severely impaired during the early phases of brain development, suggesting that this defect may be a major determinant of brain hypotrophy and mental retardation in individuals with DS. Recently, it has been found that in the cerebellum of Ts65Dn mice there is a defective responsiveness to Sonic Hedgehog (Shh), a potent mitogen that controls cell division during brain development, suggesting that failure of Shh signaling may underlie the reduced proliferation potency in DS. Based on these premises, we sought to identify the molecular mechanisms underlying derangement of the Shh pathway in neural precursor cells (NPCs) from Ts65Dn mice. We found that the expression levels of the Shh receptor Patched1 (Ptch1) were increased compared to controls both at the RNA and protein level. Partial silencing of Ptch1 expression in trisomic NPCs restored cell proliferation, indicating that proliferation impairment was due to Ptch1 overexpression. We further found that the overexpression of Ptch1 in trisomic NPCs is related to increased levels of AICD, a transcription-promoting fragment of amyloid precursor protein (APP). Increased AICD binding to the Ptch1 promoter favored its acetylated status, thus enhancing Ptch1 expression. Taken together, these data provide novel evidence that Ptch1 over expression underlies derangement of the Shh pathway in trisomic NPCs, with consequent proliferation impairment. The demonstration that Ptch1 over expression in trisomic NPCs is due to an APP fragment provides a link between this trisomic gene and the defective neuronal production that characterizes the DS brain.

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Investigating the role of Copy Number Variants in Specific Language Impairment and identification of new candidate genes

Specific language impairment (SLI) is a complex neurodevelopmental disorder defined as an unexpected failure to develop normal language abilities for no obvious reason. Copy number variants (CNVs) are an important source of variation in the susceptibility to neuropsychiatric disorders. Therefore, a CNV study within SLI families was performed to investigate the role of structural variants in SLI. Among the identified CNVs, we focused on CNVs on chromosome 15q11-q13, recurrently observed in neuropsychiatric conditions, and a homozygous exonic microdeletion in ZNF277. Since this microdeletion falls within the AUTS1 locus, a region linked to autism spectrum disorders (ASD), we investigated a potential role of ZNF277 in SLI and ASD. Frequency data and expression analysis of the ZNF277 microdeletion suggested that this variant may contribute to the risk of language impairments in a complex manner, that is independent of the autism risk previously described in this region. Moreover, we identified an affected individual with a dihydropyrimidine dehydrogenase (DPD) deficiency, caused by compound heterozygosity of two deleterious variants in the gene DPYD. Since DPYD represents a good candidate gene for both SLI and ASD, we investigated its involvement in the susceptibility to these two disorders, focusing on the splicing variant rs3918290, the most common mutation in the DPD deficiency. We observed a higher frequency of rs3918290 in SLI cases (1.2%), compared to controls (~0.6%), while no difference was observed in a large ASD cohort. DPYD mutation screening in 4 SLI and 7 ASD families carrying the splicing variant identified six known missense changes and a novel variant in the promoter region. These data suggest that the combined effect of the mutations identified in affected individuals may lead to an altered DPD activity and that rare variants in DPYD might contribute to a minority of cases, in conjunction with other genetic or non-genetic factors.

Mild cognitive impairment in medical inpatients: the mini-mental state examination is a promising screening tool

AIM: To assess the prevalence of mild cognitive impairment (MCI) in medical inpatients aged 55-85 years without known cognitive deficits, and how often ward physicians mentioned MCI in their discharge notes. Moreover, we aimed to identify variables associated with MCI and to assess the sensitivity and specificity of the Mini-Mental State Examination (MMSE) for MCI. METHODS: Two neuropsychologists administered a 60-min battery of validated tests to evaluate different cognitive domains. The diagnosis of MCI was based on a prespecified algorithm. The sensitivity and specificity of the MMSE for MCI were calculated. RESULTS: Fifteen patients showed a normal cognitive profile (21.4%), while 55 patients (78.6%) showed MCI. Ward physicians, blinded to the results of the neuropsychological evaluation, did not mention MCI in their discharge notes of any of the evaluated patients. The only variable independently associated with MCI was the MMSE. A MMSE score of < or =28 showed a sensitivity of 85.5% and a specificity of 66.7% for MCI. CONCLUSION: MCI is frequent albeit overlooked in elderly medical inpatients without previously known cognitive deficits. In view of therapies preventing the progression of MCI to dementia, MCI screening will be crucial. The MMSE represents a promising screening tool for MCI in medical inpatients.

Bilateral impairment of concurrent saccade programming in hemispatial neglect

When healthy observers make a saccade that is erroneously directed toward a distracter stimulus, they often produce a corrective saccade within 100ms after the end of the primary saccade. Such short inter-saccadic intervals indicate that programming of the secondary saccade has been initiated prior to the execution of the primary saccade and hence that the two saccades have been programmed concurrently. Here we show that concurrent saccade programming is bilaterally impaired in left spatial neglect, a strongly lateralized disorder of visual attention resulting from extensive right cerebral damage. Neglect patients were asked to make saccades to targets presented left or right of fixation while disregarding a distracter presented in the opposite hemifield. We examined those experimental trials on which participants first made a saccade to the distracter, followed by a secondary (corrective) saccade to the target. Compared to healthy and right-hemisphere damaged control participants the proportion of secondary saccades directing gaze to the target instead of bringing it even closer to the distracter was bilaterally reduced in neglect patients. In addition, the characteristic reduction of secondary saccade latency observed in both control groups was absent in neglect patients, whether the secondary saccade was directed to the left or right hemifield. This pattern is consistent with a severe, bilateral impairment of concurrent saccade programming in left spatial neglect.

Incidence and predictors of atrioventricular conduction impairment after transcatheter aortic valve implantation

Atrioventricular (AV) conduction impairment is well described after surgical aortic valve replacement, but little is known in patients undergoing transcatheter aortic valve implantation (TAVI). We assessed AV conduction and need for a permanent pacemaker in patients undergoing TAVI with the Medtronic CoreValve Revalving System (MCRS) or the Edwards Sapien Valve (ESV). Sixty-seven patients without pre-existing permanent pacemaker were included in the study. Forty-one patients (61%) and 26 patients (39%) underwent successful TAVI with the MCRS and ESV, respectively. Complete AV block occurred in 15 patients (22%), second-degree AV block in 4 (6%), and new left bundle branch block in 15 (22%), respectively. A permanent pacemaker was implanted in 23 patients (34%). Overall PR interval and QRS width increased significantly after the procedure (p <0.001 for the 2 comparisons). Implantation of the MCRS compared to the ESV resulted in a trend toward a higher rate of new left bundle branch block and complete AV block (29% vs 12%, p = 0.09 for the 2 comparisons). During follow-up, complete AV block resolved in 64% of patients. In multivariable regression analysis pre-existing right bundle branch block was the only independent predictor of complete AV block after TAVI (relative risk 7.3, 95% confidence interval 2.4 to 22.2). In conclusion, TAVI is associated with impairment of AV conduction in a considerable portion of patients, patients with pre-existing right bundle branch block are at increased risk of complete AV block, and complete AV block resolves over time in most patients.

Consensus statement of the European Heart Rhythm Association: updated recommendations for driving by patients with implantable cardioverter defibrillators

Patients with an implantable cardioverter defibrillator (ICD) have an ongoing risk of sudden incapacitation that might cause harm to others while driving a car. Driving restrictions vary across different countries in Europe. The most recent recommendations for driving of ICD patients in Europe were published in 1997 and focused mainly on patients implanted for secondary prevention. In recent years there has been a vast increase in the number of patients with an ICD and in the percentage of patients implanted for primary prevention. The EHRA task force on ICD and driving was formed to reassess the risk of driving for ICD patients based on the literature available. The recommendations are summarized in the following table and are further explained in the document, (Table see text). Driving restrictions are perceived as difficult for patients and their families, and have an immediate consequence for their lifestyle. To increase the adherence to the driving restrictions, adequate discharge of education and follow-up of patients and family are pivotal. The task force members hope this document may serve as an instrument for European and national regulatory authorities to formulate uniform driving regulations.