Modeling of glycogen resynthesis according to insulin concentration: Towards a system for prevention of late-onset exercise-induced hypoglycemia in Type 1 diabetes patients

One of the major barriers for physical activity in type 1 diabetes (T1D) patients is the risk of exercise-induced hypoglycemia, in particular the late-onset one. The identification of the relation between glycogen resynthesis rate after an exercise and insulin concentration would allow the development of new predictive models. The aim of the present work was thus to investigate this relation in T1D patients. We recruited 8 T1D subjects which underwent two 24-h observational experimental sessions: complete rest and a 3-hours treadmill walk. Glucose and insulin concentrations were measured throughout the two sessions. Comparing the data collected in the two sessions, the net glucose uptake was calculated; positive values were suggestive of glycogen repletion while negative values suggested liver glycogen breakdown. A significant correlation (r=0.742, p<0.001) was observed between insulin concentration and net glucose uptake, with the negative values corresponding to time periods showing the lowest insulin concentrations. In conclusion, the present study preliminarily assessed the impact of insulin concentration on the risk of late onset hypoglycemia, which is the first step towards a comprehensive and personalized system for prevention of exercise-induced hypoglycemia in Type 1 diabetes patients

Brain oscillatory patterns in mild cognitive impairment due to Alzheimer's and Parkinson's disease: An exploratory high-density EEG study

Objective: We investigated brain cortical activity alterations, using a resting-state 256-channel high-density EEG (hd-EEG), in Alzheimer's (AD) and Parkinson's (PD) disease subjects with mild cognitive impairment (MCI) and correlations between quantitative spectral EEG parameters and the global cognitive status assessed by Montreal Cognitive Assessment (MoCA) score. Methods: Fifteen AD-MCI, eleven PD-MCI and ten age-matched healthy-controls (HC) underwent hd-EEG recordings and neuropsychological assessment. Cerebrospinal fluid biomarker analysis was performed to obtain well-characterized groups. EEG spectral features were extracted and the differences between the three groups, as well as correlations with MoCA, were investigated. Results: The results showed significantly lower alpha2 power and alpha2/alpha1 ratio in both AD-MCI and PD-MCI compared to controls. The significantly higher theta and lower beta power and alpha/theta ratio were observed in PD-MCI compared to AD-MCI and HC. MoCA score correlated inversely with theta power and directly with alpha2 and beta powers, as well as with alpha2/alpha1 and alpha/theta ratios. Conclusions: This study highlighted significant differences in EEG patterns in AD-MCI and PD-MCI patients and remarked the role of EEG parameters as possible surrogate markers of cognitive status in both neurodegenerative diseases. Significance: In addition to well-established biomarkers, our findings could support early detection of cognitive dysfunction in neurodegenerative disorders and could help to monitor disease progression and therapeutic responses

Return to school in the COVID-19 era: considerations for temperature measurement

COVID-19 pandemics required a reorganisation of social spaces to prevent the spread of the virus. Due to the common presence of fever in the symptomatic patients, temperature measurement is one of the most common screening protocols. Indeed, regulations in many countries require temperature measurements before entering shops, workplaces, and public buildings. Due to the necessity of providing rapid non-contact and non-invasive protocols to measure body temperature, infra-red thermometry is mostly used. Many countries are now facing the need to organise the return to school and universities in the COVID-19 era, which require solutions to prevent the risk of contagion between students and/or teachers and technical/administrative staff. This paper highlights and discusses some of the strengths and limitations of infra-red cameras, including the site of measurements and the influence of the environment, and recommends to be careful to consider such measurements as a single \u201csafety rule\u201d for a good return to normality

ASL MRI and 18F-FDG-PET in autoimmune limbic encephalitis: clues from two paradigmatic cases

Background: Autoimmune limbic encephalitis (LE) is a neurological condition characterized by seizures and cognitive dysfunction. Fluorine-18 fluorodeoxyglucose (18F-FDG-PET) has recently proved to be an important diagnostic tool in this condition since it may highlight brain metabolism abnormalities in a very early stage of the disease. Two main 18F-FDG-PET patterns have been described: the mixed hypermetabolic/hypometabolic and the neurodegenerative one. Arterial spin labeling (ASL) is an MRI technique showing brain perfusion, rarely used in autoimmune neurological conditions. The aim of the present study was to study patients with LE with both techniques, in order to compare their results. Methods: Two patients with LE underwent to 18F-FDG-PET and ASL MRI scans using the pseudo-continuous arterial spin labeling (PCASL) technique. Areas of altered perfusion and metabolism were analyzed by visual inspection, and findings were compared between the two techniques. Results: In the first patient, a relapsing LGI-1 LE, right hippocampal hypermetabolism was detected by 18F-FDG-PET (mixed hypermetabolic/hypometabolic pattern), while ASL MRI showed right hippocampal increased perfusion. In the second patient, a seronegative LE, 18F-FDG-PET scan detected a left hemispheric hypoperfusion (neurodegenerative pattern) and ASL MRI yielded similar results. The two 18F-FDG-PET patterns of altered metabolism were similarly detected by ASL imaging. Conclusion: ASL and 18F-FDG-PET findings are strongly concordant in LE. ASL imaging was able to detect the two main 18F-FDG-PET patterns previously described in patients with LE

e-Health solution for home patient telemonitoring in early post-acute TIA/Minor stroke during COVID-19 pandemic

Background: When it comes to critical early post-acute TIA/stroke phase, there is a lack of a comprehensive multi-parametric telemonitoring system. The COVID-19 emergency, its related global mobility restrictions and fear of hospitalization further highlighted the need of a comprehensive solution. Objective: We aimed to design and test a pragmatic e-Health system based on multiparametric telemonitoring to support of TIA/stroke patients in sub-acute phase during the COVID-19 pandemic. Methods: We proposed a telemonitoring system and protocol for TIA/minor stroke patients during COVID-19 pandemic for patients at risk of stroke recurrence. This system involves the use of portable devices for BP/HR/SpO2/temperature sensing, panic-button, gateway, and a dedicated ICT platform. The protocol is a 14-day multiparametric telemonitoring, therapy, and emergency intervention based on vital sign alteration notifications. We conducted a proof-of-concept validation test on 8 TIA/minor stroke patients in the early post-acute phase (&lt; 14 days from ischemic event). Results: The proposed solution allowed to promptly and remotely identify vital sign alterations at home during the early post-acute phase, allowing therapy and behavioral intervention adjustments. Also, we observed a significant improvement of quality of life, as well as a significant reduction of anxiety and depression status. TUQ showed ease of use, good interface quality and high user satisfaction of the proposed solution. The 3-month follow-up showed total adherence of prescribed therapy and no stroke/TIA recurrence or other emergency department admissions. Conclusion: The proposed e-Health solution and telemonitoring protocol may be highly useful for early post-acute remote patient management, thus supporting constant monitoring and patient adherence to the treatment pathway, especially during the COVID-19 emergency

Wake-up Stroke Outcome Prediction by Interpretable Decision Tree Model

Outcome prediction in wake-up ischemic stroke (WUS) is important for guiding treatment strategies, in order to improve recovery and minimize disability. We aimed at producing an interpretable model to predict a good outcome (NIHSS 7-day<5) in thrombolysis treated WUS patients by using Classification and Regression Tree (CART) method. The study encompassed 104 WUS patients and we used a dataset consisting of demographic, clinical and neuroimaging features. The model was produced by CART with Gini split criterion and evaluated by using 5-fold cross-validation. The produced decision tree model was based on NIHSS at admission, ischemic core volume and age features. The predictive accuracy of model was 86.5% and the AUC-ROC was 0.88. In conclusion, in this preliminary study we identified interpretable model based on clinical and neuroimaging features to predict clinical outcome in thrombolysis treated wake-up stroke patients

Multimodal CT pc-ASPECTS in infratentorial stroke: diagnostic and prognostic value

Background and purpose: Diagnosis of posterior circulation stroke may be challenged. National Institutes of Health Stroke Scale (NIHSS) and brain imaging (non-contrast brain computed tomography-CT) are used for diagnosis; evaluation on posterior circulation stroke remains a limit of NIHSS, and the value of non-contrast CT (NCCT) is limited due to artifacts caused by the bones of the base of the skull. We tested the validity and prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) in patients with posterior circulation stroke. Methods: Pc-ASPECTS allots the posterior circulation 10 points. We studied 50 patients with posterior circulation stroke. We applied pc-ASPECTS to NCCT, CT angiography, and CT Perfusion. We evaluated the correlation of pc-ASPECT with outcome parameters for stroke. Results: Out of 50 patients, CTP showed abnormalities in 34 cases. The pc-ASPECT score calculated on brain CT and on the brain CT + angio CT had a sensibility of 24%, calculated on brain CT, angio CT and CTPerfusion gain a sensibility of 72%. Pc-ASPECT MTT resulted to be the more reliable parameter: outcome given by NIHSS score at discharge, mRS at discharge, and at 3 months was more severe in patients with Pc-ASPECT MTT alteration. Outcome given by NIHSS score at discharge and mRS at discharge and 1 at 3 months was more severe in patients with higher NIHSS score at admission. Conclusion: We evaluated the usefulness of pc-ASPECTS on CTP in predicting functional outcome in acute posterior circulation stroke that appears to be a powerful marker for predicting functional outcome

Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs’ motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5–9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units

Impact of intrapulmonary percussive ventilation settings on respiratory mechanics parameters

Intrapulmonary percussive ventilation (IPV) is an airway clearance technique recently introduced as an alternative to conventional chest physiotherapy in chronic obstructive pulmonary diseases (COPD). A new portable device delivering IPV, called Impulsator\uae (Percussionaire Corporation, Sandpoint, Idaho, USA), has been introduced for IPV home therapy with the aim to foster COPD patients\u2019 autonomy. Nevertheless, the lack of detailed information about the exact functioning of the device restricts the possibility of treatment optimization, possibly reducing the clinical usefulness of the therapy. This work aims to obtain quantitative information about the physical variables related to the use of the Impulsator\uae (e.g. pulsatile flow and pressure magnitudes), allowing treatment personalization