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Currently, distribution system operators (DSOs) are asked to operate distribution grids, managing the rise of the distributed generators (DGs), the rise of the load correlated to heat pump and e-mobility, etc. Nevertheless, they are asked to minimize investments in new sensors and telecommunication links and, consequently, several nodes of the grid are still not monitored and tele-controlled. At the same time, DSOs are asked to improve the network’s resilience, looking for a reduction in the frequency and impact of power outages caused by extreme weather events. The paper presents a machine learning GIS-based approach to estimate a secondary substation’s load profiles, even in those cases where monitoring sensors are not deployed. For this purpose, a large amount of data from different sources has been collected and integrated to describe secondary substation load profiles adequately. Based on real measurements of some secondary substations (medium-voltage to low-voltage interface) given by Unareti, the DSO of Milan, and georeferenced data gathered from open-source databases, unknown secondary substations load profiles are estimated. Three types of machine learning algorithms, regression tree, boosting, and random forest, as well as geographic information system (GIS) information, such as secondary substation locations, building area, types of occupants, etc., are considered to find the most effective approach.

BackgroundFrailty is the most important short- and long-term predictor of disability in the elderly and, thus, might influence the clinical outcome of acute treatment of stroke.ObjectiveTo evaluate whether frailty predicts short- and long-term all-cause mortality and neurological recovery in elderly patients who underwent reperfusion acute treatment of stroke.MethodsThe study included consecutive patients older than 65 years who underwent reperfusion treatment in a single stroke unit from 2015 to 2016. Predictors of stroke outcomes were assessed including demographics, baseline NIHSS, time to needle, treatment and medical complications. Premorbid frailty was assessed with a comprehensive geriatric assessment including functional, nutritional, cognitive, social and comorbidities status. At three and twelve months, all-cause death and clinical recovery (using modified Rankin scale, mRS) were evaluated.ResultsOne-hundred and two patients who underwent acute reperfusion treatment for stroke entered the study (mean age 77.5, 65–94 years). Frailty was diagnosed in 32 out of 102 patients and associated with older age (p = 0.001) but no differences in baseline NIHSS score, vascular risk profile or treatment management strategy. Frailty status was associated with worse improvement at 24 h and higher in-hospital mortality. At follow-up, frail patients showed poorer survival at 3 (25% vs 3%, p = 0.008) and 12 (38% vs 7%, p = 0.001) months. Frailty was the best predictor of neurological recovery at one year follow-up (mRS 3.2 ± 1.9 vs 1.9 ± 1.9).DiscussionFrailty is an important predictor of efficacy of acute treatment of stroke beyond classical predictors of stroke outcomes. Larger longitudinal studies are, thus, warranted to evaluate the risk–benefit of reperfusion treatment in the growing elderly frail population.

We hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scans of patients with acute intracerebral hemorrhage (ICH). This retrospective multicenter cohort study analyzed 520 non-enhanced CT scans and clinical data of patients with acute spontaneous ICH. Clinical outcome at hospital discharge was dichotomized into good outcome and poor outcome using different modified Rankin Scale (mRS) cut-off values. Predictive performance of a random forest machine learning approach based on filter- and texture-derived high-end image features was evaluated for differentiation of functional outcome at mRS 2, 3, and 4. Prediction of survival (mRS ≤ 5) was compared to results of the ICH Score. All models were tuned, validated, and tested in a nested 5-fold cross-validation approach. Receiver-operating-characteristic area under the curve (ROC AUC) of the machine learning classifier using image features only was 0.80 (95% CI [0.77; 0.82]) for predicting mRS ≤ 2, 0.80 (95% CI [0.78; 0.81]) for mRS ≤ 3, and 0.79 (95% CI [0.77; 0.80]) for mRS ≤ 4. Trained on survival prediction (mRS ≤ 5), the classifier reached an AUC of 0.80 (95% CI [0.78; 0.82]) which was equivalent to results of the ICH Score. If combined, the integrated model showed a significantly higher AUC of 0.84 (95% CI [0.83; 0.86], P value <0.05). Accordingly, sensitivities were significantly higher at Youden Index maximum cut-offs (77% vs. 74% sensitivity at 76% specificity, P value <0.05). Machine learning–based evaluation of quantitative high-end image features provided the same discriminatory power in predicting functional outcome as multidimensional clinical scoring systems. The integration of conventional scores and image features had synergistic effects with a statistically significant increase in AUC.

The paper aims to provide primary substations’ optimal siting and timing to expand existing distribution networks. The proposed methodology relies on three main features: a geographic information system for capturing, elaborating, and displaying spatial input data; a particle swarm optimization algorithm to locate and timing the new primary substations; a Voronoi diagram-based approach to find the primary substation service areas and loading. The optimization criteria follow the approach of serving every customer from the nearest primary substation to ensure that the distribution delivery distance is as short as possible, reducing feeders’ cost, electric losses, and service interruption exposure. The algorithm also considers the primary substation transformers’ capacity limit. Thanks to Unareti, the distribution system operator of Milan and Brescia, the methodology was tested by carrying out several simulations, progressively increasing the number of new primary substations. The results obtained confirm the proposed approach’s effectiveness and show that the methodology is a valuable tool to guide Unareti, and distribution system operators in general, in expanding distribution networks to face the challenges of the energy transition.

Background: Stroke-induced immunosuppression (SII) represents a negative rehabilitative prognostic factor associated with poor motor performance at discharge from a neurorehabilitation unit (NRB). This study aims to evaluate the association between SII and gait impairment at NRB admission. Methods: Forty-six stroke patients (65.4 ± 15.8 years, 28 males) and 42 healthy subjects (HS), matched for age, sex, and gait speed, underwent gait analysis using an inertial measurement unit at the lumbar level. Stroke patients were divided into two groups: (i) the SII group was defined using a neutrophil-to-lymphocyte ratio ≥ 5, and (ii) the immunocompetent (IC) group. Harmonic ratio (HR) and short-term largest Lyapunov’s exponent (sLLE) were calculated as measures of gait symmetry and stability, respectively. Results: Out of 46 patients, 14 (30.4%) had SII. HR was higher in HS when compared to SII and IC groups (p < 0.01). HR values were lower in SII when compared to IC subjects (p < 0.01). sLLE was lower in HS when compared to SII and IC groups in the vertical and medio-lateral planes (p ≤ 0.01 for all comparisons). sLLE in the medio-lateral plane was higher in SII when compared to IC subjects (p = 0.04). Conclusions: SII individuals are characterized by a pronounced asymmetric gait and a more impaired dynamic gait stability. Our findings underline the importance of devising tailored rehabilitation programs in patients with SII. Further studies are needed to assess the long-term outcomes and the role of other clinical features on gait pattern.

Background The cerebrospinal fluid (CSF)/serum quotient of albumin (QAlb) is the most used biomarker for the evaluation of blood–cerebrospinal fluid barrier (B-CSF-B) permeability. For years QAlb was considered only as an age-related parameter but recently it has also been associated to sex. The aim of the present study was to explore the impact of sex in the determination of B-CSF-B dysfunction. Methods The analysis was retrospectively conducted on subjects consecutively admitted to the neurological ward. CSF and serum albumin levels were measured by immunonephelometry and pathological QAlb thresholds were considered: 6.5 under 40 years, 8.0 in the age 40–60 and 9.0 over 60 years. Results 1209 subjects were included in the study. 718 females and 491 males (age: 15–88 years): 24.6% of patients had a diagnosis of multiple sclerosis, 23.2% suffered from other inflammatory neurological diseases, 24.6% were affected by non-inflammatory neurological diseases, and for 27.6% of patients the final neurological diagnosis could not be traced. Dysfunctional B-CSF-B was detected more frequently (44 vs. 20.1%, p < 0.0001) and median QAlb value were higher (7.18 vs. 4.87, p < 0.0001) in males than in females in the overall study population and in all disease subgroups. QAlb and age were positively correlated both in female (p < 0.0001) and male (p < 0.0001) patients, however the slopes of the two regression lines were not significantly different (p = 0.7149), while the difference between the elevations was extremely significant (p < 0.0001) with a gap of 2.2 units between the two sexes. Finally, in a multivariable linear regression analysis increased age and male sex were independently associated with higher QAlb in the overall study population (both p < 0.001) and after stratification by age and disease group. Conclusions Accordingly, identification and validation of sex-targeted QAlb thresholds should be considered as a novel tool in an effort to achieve more precision in the medical approach.

Stroke affects the interconnection between the nervous and immune systems, leading to a down-regulation of immunity called stroke-induced immunosuppression (SII). The primary aim of this study is to investigate SII role as a predictor of functional, neurological, and motor outcomes in the neurorehabilitation setting (NRB). We conducted a prospective observational study enrolling post-acute stroke patients hospitalized for neurorehabilitation. At NRB admission (T 0 ) and discharge (T 1 ), we assessed presence of SII (defined by a neutrophil-to-lymphocyte ratio ≥ 5) and we evaluated functional independence (Functional Independence Measure-FIM, Barthel Index-BI), motor performances (Tinetti Score, Hauser Ambulation Index) and neurological impairment (NIHSS). We enrolled 96 patients (45.8% females, 70.6 ± 13.9 years, 88.5% ischemic stroke). At T 0 , 15.6% of patients (15/96) had SII. When compared to immunocompetent patients (IC), the SII group was characterized by worse baseline functional independence, motor performances and neurological disability. The same was confirmed at T 1 (FIM p  = 0.012, BI p  = 0.007, Tinetti p  = 0.034, NIHSS p  = 0.001). Neurological disability demonstrated a less pronounced improvement in SII (ΔNIHSS: SII: − 2.1 ± 2.3 vs. IC: − 3.1 ± 2.5, p  = 0.035). SII group presented a higher percentage of infectious complications during the neurorehabilitation period (SII 80% vs. IC 25.9%; p  = 0.001). SII may represent a negative prognostic factor in the neurorehabilitation setting. SII patients were characterized by poorer functional, motor, neurological performances and higher risk of infectious complications. ClinicaTrial registration: NCT05889169.

Low levels of serum albumin may increase the risk of infections and mortality in critically ill patients. We tested the hypothesis that admission hypoalbuminemia predicted infectious complications and poor outcome in subjects with acute intracerebral hemorrhage (ICH). We analyzed a single center cohort of ICH patients collected between 1994 and 2015. Pneumonia, urinary tract infection and sepsis were retrospectively identified, according to validated criteria. Serum albumin was measured on admission and hypoalbuminemia was defined as total albumin ≤3.5 g/dL. The association between albumin levels, infections, and mortality at 90 days was tested with multivariable logistic regression analyses. A total of 2010 patients were included (median age 74 years, 54.5% males) of whom 444 (22.1%) had hypoalbuminemia on admission and 763 (38%) died within 90 days. The frequency of pneumonia, urinary tract infection, and sepsis was 19.9, 15.1, and 2.7%, respectively. Hypoalbuminemic patients had lower admission Glasgow coma scale, higher frequency of intraventricular hemorrhage and were more likely to have a history of chronic kidney or liver disease. After adjustment for potential confounders, hypoalbuminemia was an independent predictor of pneumonia [odds ratio (OR) 1.76, 95% confidence interval (CI) 1.34–2.33, p  < 0.001] and sepsis (OR 2.29, 95% CI 1.22–4.30, p  = 0.010). Low levels of albumin were also independently associated with higher mortality at 90 days (OR 1.78, 95% CI 1.30–2.44, p  < 0.001). In conclusion, early hypoalbuminemia is common and predicts poor outcome in ICH patients. Increased susceptibility to pneumonia and sepsis may be the pathophysiological mechanism underlying this association.

Background Hematoma expansion (HE) is common and predicts poor outcome in patients with supratentorial intracerebral hemorrhage (ICH). We investigated the predictors and prognostic impact of HE in infratentorial ICH. Methods We conducted a retrospective analysis of patients with brainstem and cerebellar ICH admitted at seven sites. Noncontrast computed tomography images were analyzed for the presence of hypodensities according to validated criteria, defined as any hypodense region strictly encapsulated within the hemorrhage with any shape, size, and density. Occurrence of HE (defined as > 33% and/or > 6-mL growth) and mortality at 90 days were the outcomes of interest. Their predictors were investigated using logistic regression with backward elimination at p  < 0.1. Logistic regression models for HE were adjusted for baseline ICH volume, antiplatelet and anticoagulant treatment, onset to computed tomography time, and presence of hypodensities. The logistic regression model for mortality accounted for the ICH score and HE. Results A total of 175 patients were included (median age 75 years, 40.0% male), of whom 38 (21.7%) had HE and 43 (24.6%) died within 90 days. Study participants with HE had a higher frequency of hypodensities (44.7 vs. 24.1%, p  = 0.013), presentation within 3 h from onset (39.5 vs. 24.8%, p  = 0.029), and 90-day mortality (44.7 vs. 19.0%, p  = 0.001). Hypodensities remained independently associated with HE after adjustment for confounders (odds ratio 2.44, 95% confidence interval 1.13–5.25, p  = 0.023). The association between HE and mortality remained significant in logistic regression (odds ratio 3.68, 95% confidence interval 1.65–8.23, p  = 0.001). Conclusion Early presentation and presence of noncontrast computed tomography hypodensities were independent predictors of HE in infratentorial ICH, and the occurrence of HE had an independent prognostic impact in this population.

Cerebrovascular diseases are a leading cause of disability and death worldwide. The definition of stroke etiology is mandatory to predict outcome and guide therapeutic decisions. The diagnosis of pathological processes involving intracranial arteries is especially challenging, and the visualization of intracranial arteries’ vessel walls is not possible with routine imaging techniques. Vessel wall magnetic resonance imaging (VW-MRI) uses high-resolution, multiparametric MRI sequences to directly visualize intracranial arteries walls and their pathological alterations, allowing a better characterization of their pathology. VW-MRI demonstrated a wide range of clinical applications in acute cerebrovascular disease. Above all, it can be of great utility in the differential diagnosis of atherosclerotic and non-atherosclerotic intracranial vasculopathies. Additionally, it can be useful in the risk stratification of intracranial atherosclerotic lesions and to assess the risk of rupture of intracranial aneurysms. Recent advances in MRI technology made it more available, but larger studies are still needed to maximize its use in daily clinical practice.