213 research outputs found

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

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    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

    Care pathways models and clinical outcomes in disorders of consciousness

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    Objective: Patients with Disorders of consciousness, are persons with extremely low functioning levels and represent a challenge for health care systems due to their high needs of facilitating environmental factors. Despite a common Italian health care path-way for these patients, no studies have analyzed information on how each region have implemented it in its welfare system correlating data with patients’ clinical outcomes. Materials and Methods: A multicenter observational pilot study was realized. Clinicians collected data on the care pathways of patients with Disorder of consciousness by ask-ing 90 patients’ caregivers to complete an ad hoc questionnaire through a structured phone interview. Questionnaire consisted of three sections: sociodemographic data, description of the care pathway done by the patient, and caregiver evaluation of health services and information received.Results: Seventy- three patients were analyzed. Length of hospital stay was different across the health care models and it was associated with improvement in clinical diag-nosis. In long- term care units, the diagnosis at admission and the number of caregivers available for each patient (median value=3) showed an indirect relationship with worsening probability in clinical outcome. Caregivers reported that communication with professionals (42%) and the answer to the need of information were the most critical points in the acute phase, whereas presence of Non- Governmental Organizations (25%) and availability of psychologists for caregivers (21%) were often missing during long-term care. The 65% of caregivers reported they did not know the UN Convention on the Rights of Persons with Disabilities. Conclusion: This study highlights relevant differences in analyzed models, despite a recommended national pathway of care. Future public health considerations and ac-tions are needed to guarantee equity and standardization of the care process in all European countries

    The Australia Telescope 20 GHz (AT20G) Survey: The Bright Source Sample

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    The Australia Telescope 20 GHz (AT20G) Survey is a blind survey of the whole Southern sky at 20 GHz (with follow-up observations at 4.8 and 8.6 GHz) carried out with the Australia Telescope Compact Array (ATCA) from 2004 to 2007. The Bright Source Sample (BSS) is a complete flux-limited subsample of the AT20G Survey catalogue comprising 320 extragalactic (|b|>1.5 deg) radio sources south of dec = -15 deg with S(20 GHz) > 0.50 Jy. Of these, 218 have near simultaneous observations at 8 and 5 GHz. In this paper we present an analysis of radio spectral properties in total intensity and polarisation, size, optical identifications and redshift distribution of the BSS sources. The analysis of the spectral behaviour shows spectral curvature in most sources with spectral steepening that increases at higher frequencies (the median spectral index \alpha, assuming S\propto \nu^\alpha, decreases from \alpha_{4.8}^{8.6}=0.11 between 4.8 and 8.6 GHz to \alpha_{8.6}^{20}=-0.16 between 8.6 and 20 GHz), even if the sample is dominated by flat spectra sources (85 per cent of the sample has \alpha_{8.6}^{20}>-0.5). The almost simultaneous spectra in total intensity and polarisation allowed us a comparison of the polarised and total intensity spectra: polarised fraction slightly increases with frequency, but the shapes of the spectra have little correlation. Optical identifications provided an estimation of redshift for 186 sources with a median value of 1.20 and 0.13 respectively for QSO and galaxies.Comment: 34 pages, 19 figures, tables of data included, replaced with version published in MNRA

    "EDML1": a chronology for the EPICA deep ice core from Dronning Maud Land, Antarctica, over the last 150 000 years.

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    A chronology called EDML1 has been developed for the EPICA ice core from Dronning Maud Land (EDML). EDML1 is closely interlinked with EDC3, the new chronology for the EPICA ice core from Dome-C (EDC) through a stratigraphic match between EDML and EDC that consists of 322 volcanic match points over the last 128 ka. The EDC3 chronology comprises a glaciological model at EDC, which is constrained and later selectively tuned using primary dating information from EDC as well as from EDML, the latter being transferred using the tight stratigraphic link between the two cores. Finally, EDML1 was built by exporting EDC3 to EDML. For ages younger than 41 ka BP the new synchronized time scale EDML1/EDC3 is based on dated volcanic events and on a match to the Greenlandic ice core chronology GICC05 via <sup>10</sup>Be and methane. The internal consistency between EDML1 and EDC3 is estimated to be typically ~6 years and always less than 450 years over the last 128 ka (always less than 130 years over the last 60 ka), which reflects an unprecedented synchrony of time scales. EDML1 ends at 150 ka BP (2417 m depth) because the match between EDML and EDC becomes ambiguous further down. This hints at a complex ice flow history for the deepest 350 m of the EDML ice core

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

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    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

    Antidiabetic Drug Prescription Pattern in Hospitalized Older Patients with Diabetes

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    Objective: To describe the prescription pattern of antidiabetic and cardiovascular drugs in a cohort of hospitalized older patients with diabetes. Methods: Patients with diabetes aged 65 years or older hospitalized in internal medicine and/or geriatric wards throughout Italy and enrolled in the REPOSI (REgistro POliterapuie SIMI—Società Italiana di Medicina Interna) registry from 2010 to 2019 and discharged alive were included. Results: Among 1703 patients with diabetes, 1433 (84.2%) were on treatment with at least one antidiabetic drug at hospital admission, mainly prescribed as monotherapy with insulin (28.3%) or metformin (19.2%). The proportion of treated patients decreased at discharge (N = 1309, 76.9%), with a significant reduction over time. Among those prescribed, the proportion of those with insulin alone increased over time (p = 0.0066), while the proportion of those prescribed sulfonylureas decreased (p < 0.0001). Among patients receiving antidiabetic therapy at discharge, 1063 (81.2%) were also prescribed cardiovascular drugs, mainly with an antihypertensive drug alone or in combination (N = 777, 73.1%). Conclusion: The management of older patients with diabetes in a hospital setting is often sub-optimal, as shown by the increasing trend in insulin at discharge, even if an overall improvement has been highlighted by the prevalent decrease in sulfonylureas prescription

    The “Diabetes Comorbidome”: A Different Way for Health Professionals to Approach the Comorbidity Burden of Diabetes

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    (1) Background: The disease burden related to diabetes is increasing greatly, particularly in older subjects. A more comprehensive approach towards the assessment and management of diabetes’ comorbidities is necessary. The aim of this study was to implement our previous data identifying and representing the prevalence of the comorbidities, their association with mortality, and the strength of their relationship in hospitalized elderly patients with diabetes, developing, at the same time, a new graphic representation model of the comorbidome called “Diabetes Comorbidome”. (2) Methods: Data were collected from the RePoSi register. Comorbidities, socio-demographic data, severity and comorbidity indexes (Cumulative Illness rating Scale CIRS-SI and CIRS-CI), and functional status (Barthel Index), were recorded. Mortality rates were assessed in hospital and 3 and 12 months after discharge. (3) Results: Of the 4714 hospitalized elderly patients, 1378 had diabetes. The comorbidities distribution showed that arterial hypertension (57.1%), ischemic heart disease (31.4%), chronic renal failure (28.8%), atrial fibrillation (25.6%), and COPD (22.7%), were the more frequent in subjects with diabetes. The graphic comorbidome showed that the strongest predictors of death at in hospital and at the 3-month follow-up were dementia and cancer. At the 1-year follow-up, cancer was the first comorbidity independently associated with mortality. (4) Conclusions: The “Diabetes Comorbidome” represents the perfect instrument for determining the prevalence of comorbidities and the strength of their relationship with risk of death, as well as the need for an effective treatment for improving clinical outcomes

    Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

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    Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

    Event reconstruction for KM3NeT/ORCA using convolutional neural networks

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    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
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