Life-long individual planning in children with developmental disability: the active role of parents in the Italian experience

AbstractMany young adults with neurodevelopmental disorders experience poor transition outcomesin key areas, including employment, health care, and independent living. Innovativewelfare models highlight the importance of involving the local community, and inparticular the parents, as important stakeholders capable to generate services and affectlocal economy. As indicated by the World Health Organization, the availability of person-centered responses, also providing a health budget, appears to be the basis for takinginto account person’s rights to self-determination. Health services and local stakeholderscould play an important role to facilitate the implementation of support networks thatare functional for an effective social inclusion. In order to improve current practices intransitioning to adulthood, it is of paramount importance to collect and learn from theliving experience of people with neurodevelopmental disabilities and their families

Diabetic peripheral neuropathic pain is a stronger predictor of depression than other diabetic complications and comorbidities.

Aims: To investigate the independent effect on depression of painless diabetic polyneuropathy, painful diabetic polyneuropathy, and general and diabetes-related comorbidities. Methods: In 181 patients, the presence of painless diabetic polyneuropathy, painful diabetic polyneuropathy, comorbidities and depression was assessed using the Michigan Neuropathy Screening Instrument Questionnaire, the Michigan Diabetic Neuropathy Score, nerve conduction studies, the Douleur Neuropathique en 4 Questions, the Charlson Comorbidity Index and the Beck Depression Inventory-II. Results: In all, 46 patients met the criteria of confirmed painless diabetic polyneuropathy and 25 of painful diabetic polyneuropathy. Beck Depression Inventory-II scores indicative of mild-moderate-severe depression were reached in 36 patients (19.7%). In a multiple logistic regression analysis (including age, sex, body mass index, being unemployed, duration, haemoglobin A1c, insulin treatment, systolic blood pressure, nephropathy, retinopathy, Charlson Comorbidity Index and painful diabetic polyneuropathy), female sex (odds ratio: 5.9, p = 0.005) and painful diabetic polyneuropathy (odds ratio: 4.6, p = 0.038) were the only independent predictors of depression. Multiple regression analysis, including Douleur Neuropathique en 4 Questions and Michigan Diabetic Neuropathy Score instead of painful diabetic polyneuropathy, showed that Douleur Neuropathique en 4 Questions, in addition to female sex, was a significant predictor of depressive symptoms severity (p =0.005). Conclusion: Painful diabetic polyneuropathy is a greater determinant of depression than other diabetes-related complications and comorbidities. Painful symptoms enhance depression severity more than objective insensitivity

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Beta-Blocker Use in Older Hospitalized Patients Affected by Heart Failure and Chronic Obstructive Pulmonary Disease: An Italian Survey From the REPOSI Register

Beta (β)-blockers (BB) are useful in reducing morbidity and mortality in patients with heart failure (HF) and concomitant chronic obstructive pulmonary disease (COPD). Nevertheless, the use of BBs could induce bronchoconstriction due to β2-blockade. For this reason, both the ESC and GOLD guidelines strongly suggest the use of selective β1-BB in patients with HF and COPD. However, low adherence to guidelines was observed in multiple clinical settings. The aim of the study was to investigate the BBs use in older patients affected by HF and COPD, recorded in the REPOSI register. Of 942 patients affected by HF, 47.1% were treated with BBs. The use of BBs was significantly lower in patients with HF and COPD than in patients affected by HF alone, both at admission and at discharge (admission, 36.9% vs. 51.3%; discharge, 38.0% vs. 51.7%). In addition, no further BB users were found at discharge. The probability to being treated with a BB was significantly lower in patients with HF also affected by COPD (adj. OR, 95% CI: 0.50, 0.37-0.67), while the diagnosis of COPD was not associated with the choice of selective β1-BB (adj. OR, 95% CI: 1.33, 0.76-2.34). Despite clear recommendations by clinical guidelines, a significant underuse of BBs was also observed after hospital discharge. In COPD affected patients, physicians unreasonably reject BBs use, rather than choosing a β1-BB. The expected improvement of the BB prescriptions after hospitalization was not observed. A multidisciplinary approach among hospital physicians, general practitioners, and pharmacologists should be carried out for better drug management and adherence to guideline recommendations

Validation of DN4 as a screening tool for neuropathic pain in painful diabetic polyneuropathy.

Aims DN4(DouleurNeuropathique en 4Questions) is a screening tool for neuropathic pain consisting of interviewquestions (DN4-interview) and physical tests. It has not formally been validated in diabetes. We evaluated the validity and diagnostic accuracy of DN4 and DN4-interview in identifying neuropathic pain of painful diabetic polyneuropathy. Methods In 158 patients with diabetes, the presence of diabetic polyneuropathy and neuropathic pain was assessed using scoring system for symptoms and signs, quantitative sensory testing, nerve conduction studies, pain history, numerical rating scale, and Short-Form McGill Pain Questionnaire. Painful diabetic polyneuropathy was defined as the presence of diabetic polyneuropathy plus chronic neuropathic pain in the same area as neuropathic deficits. Ablinded investigator performed DN4. Results The DN4 score was significantly related to all the neurological and electrophysiological measurements and to Short- FormMcGill Pain Questionnaire (q = 0.58, P < 0.0001). DN4 and DN4-interview scores showed a high diagnostic accuracy for painful diabetic polyneuropathy with areas under the receiver operating characteristic curve of 0.94 and 0.93, respectively. At the cut-off of 4, DN4 displayed sensitivity of 80%, specificity of 92%, positive predictive value (PPV) of 82%, negative predictive value (NPV) of 91%, and likelihood ratio for a positive result (LR+)of 9.6.At the cut-offof 3,DN4-interviewshowed sensitivity and specificity of 84%, PPV of 71%, NPV of 92%, and LR+ of 5.3. Conclusions This is thefirst validation study ofDN4for painful diabetic polyneuropathy, which supports itsusefulness as both a screening tool for neuropathic pain in diabetes and a reliable component of the diagnostic work up for painful diabetic polyneuropathy

Search for linkage to schizophrenia on the X and Y chromosomes.

Markers for X chromosome loci were used in linkage studies of a large group of small families (n = 126) with at least two schizophrenic members in one sibship. Based on the hypothesis that a gene for schizophrenia could be X-Y linked, with homologous loci on both X and Y, our analyses included all families regardless of the pattern of familial inheritance. Lod scores were computed with both standard X-linked and a novel X-Y model, and sib-pair analyses were performed for all markers examining the sharing of maternal alleles. Small positive lod scores were obtained for loci pericentromeric, from Xp11.4 to Xq12. Lod scores were also computed separately in families selected for evidence of maternal inheritance and absence of male to male transmission of psychosis. The lod score for linkage to the locus DXS7 reached a maximum of 1.83 at 0.08% recombination, assuming dominant inheritance on the X chromosome in these families (n = 34). Further investigation of the X-Y homologous gene hypothesis focussing on this region is warranted