Ocular-following responses in school-age children

: Ocular following eye movements have provided insights into how the visual system of humans and monkeys processes motion. Recently, it has been shown that they also reliably reveal stereoanomalies, and, thus, might have clinical applications. Their translation from research to clinical setting has however been hindered by their small size, which makes them difficult to record, and by a lack of data about their properties in sizable populations. Notably, they have so far only been recorded in adults. We recorded ocular following responses (OFRs)-defined as the change in eye position in the 80-160 ms time window following the motion onset of a large textured stimulus-in 14 school-age children (6 to 13 years old, 9 males and 5 females), under recording conditions that closely mimic a clinical setting. The OFRs were acquired non-invasively by a custom developed high-resolution video-oculography system, described in this study. With the developed system we were able to non-invasively detect OFRs in all children in short recording sessions. Across subjects, we observed a large variability in the magnitude of the movements (by a factor of 4); OFR magnitude was however not correlated with age. A power analysis indicates that even considerably smaller movements could be detected. We conclude that the ocular following system is well developed by age six, and OFRs can be recorded non-invasively in young children in a clinical setting

Toward a diagnostic CART model for Ischemic heart disease and idiopathic dilated cardiomyopathy based on heart rate total variability

Diagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process

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

Personalized setup of high frequency percussive ventilator by estimation of respiratory system viscoelastic parameters

2013/2014High Frequency Percussive Ventilation (HFPV) is a non-conventional ventilatory modality which has proven highly effective in patients with severe gas exchange impairment. However, at the present time, HFPV ventilator provides only airway pressure measurement. The airway pressure measurements and gas exchange analysis are currently the only parameters that guide the physician during the HFPV ventilator setup and treatment monitoring. The evaluation of respiratory system resistance and compliance parameters in patients undergoing mechanical ventilation is used for lung dysfunctions detection, ventilation setup and treatment effect evaluation. Furthermore, the pressure measured by ventilator represents the sum of the endotracheal tube pressure drop and the tracheal pressure. From the clinical point of view, it is very important to take into account the real amount of pressure dissipated by endotracheal tube to avoid lung injury. HFPV is pressure controlled logic ventilation, thus hypoventilation and hyperventilation cases are possible because of tidal volume variations in function of pulmonary and endotracheal tube impedance. This thesis offers a new approach for HFPV ventilator setup in accordance with protective ventilatory strategy and optimization of alveolar recruitment using estimation of the respiratory mechanics parameters and endotracheal pressure drop. Respiratory system resistance and compliance parameters were estimated, firstly in vitro and successively in patients undergoing HFPV, applying least squares regression on Dorkin high frequency model starting from measured respiratory signals. The Blasius model was identified as the most adequate to estimate pressure drop across the endotracheal tube during HFPV. Beside measurement device was developed in order to measure respiratory parameters in patients undergoing HFPV. The possibility to tailor HFPV ventilator setup, using respiratory signals measurement and estimation of respiratory system resistance, compliance and endotracheal tube pressure drop, provided by this thesis, opens a new prospective to this particular ventilatory strategy, improving its beneficial effects and minimizing ventilator-induced lung damage.XXVII Ciclo198

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and early Parkinson\u27s disease patients

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson\u27s disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems

Heat risk exacerbation potential for neurology patients during the COVID-19 pandemic and related isolation

COVID-19 may increase the risk of heat-related symptoms during hot weather since vulnerable populations, including the elderly and those with neurological disabilities, must continue to self-isolate, often indoors. Within the chronic neurological patient population, indoor conditions in summer months present a hazard because of impaired and/or altered thermoregulation, including poor hydration status due to both autonomic and behavioral dysfunction(s). To address this increased risk, telemedicine protocols should include an assessment of the patient’s environmental parameters, and when combined with physiological data from wearable devices, identify those with neurological diseases who are at higher risk of heat illness. Personalized medicine during times of self-isolation must be encouraged, and using smart technology in ambient assisted living solutions, including e-health to monitor physiological parameters are highly recommended, not only during extreme weather conditions but also during times of increased isolation and vulnerability.</p

A Novel Non-Invasive Thermometer for Continuous Core Body Temperature: Comparison with Tympanic Temperature in an Acute Stroke Clinical Setting

There is a growing research interest in wireless non-invasive solutions for core temperature estimation and their application in clinical settings. This study aimed to investigate the use of a novel wireless non-invasive heat flux-based thermometer in acute stroke patients admitted to a stroke unit and compare the measurements with the currently used infrared (IR) tympanic temperature readings. The study encompassed 30 acute ischemic stroke patients who underwent continuous measurement (Tcore) with the novel wearable non-invasive CORE device. Paired measurements of Tcore and tympanic temperature (Ttym) by using a standard IR-device were performed 3&ndash;5 times/day, yielding a total of 305 measurements. The predicted core temperatures (Tcore) were significantly correlated with Ttym (r = 0.89, p &lt; 0.001). The comparison of the Tcore and Ttym measurements by Bland&ndash;Altman analysis showed a good agreement between them, with a low mean difference of 0.11 &plusmn; 0.34 &deg;C, and no proportional bias was observed (B = &minus;0.003, p = 0.923). The Tcore measurements correctly predicted the presence or absence of Ttym hyperthermia or fever in 94.1% and 97.4% of cases, respectively. Temperature monitoring with a novel wireless non-invasive heat flux-based thermometer could be a reliable alternative to the Ttym method for assessing core temperature in acute ischemic stroke patients

Modeling of Carbohydrates Oxidation Rate During Exercise in Type 1 Highly-Trained Diabetic Patients

Management of Type 1 Diabetes (T1D) in the context of exercise or sports competition still represents a great challenge for athletes living with this disease, due to the wide excursions in blood glucose level with increased risk of life threatening hypoglycemia. Recently, an algorithm called ECRES has been developed to estimate patient-exercise tailored carbohydrates (CHO) supplement required to maintain safe blood glucose levels during physical activity. This method estimates a CHO supplement based on the patient\u2019s habitual therapy, the specific patient\u2019s insulin sensitivity and the overall amount of CHO oxidized during the specific exercise. The last is based on the glucose pulse relation, i.e. the relation between heart rate (HR) and CHO oxidation rate, already studied in sedentary and moderately-trained subjects, but not in well-trained athletes. This study aimed to model the glucose pulse relation during exercise in type 1 highly trained diabetic patients and in healthy subjects. HR, oxygen consumption and carbon dioxide production were acquired breath-by-breath in seven T1D and seven well-matched healthy highly-trained subjects at four different exercise intensity levels, as well as at rest. Results showed a linear CHOox-HR relation (CHOox\u2009=\u20090.76 \ub7 %HRmax - 19.6; n\u2009=\u200970, R2\u2009=\u20090.78) with no significant difference between the T1D and healthy athletes (p-value\u2009=\u20090.11). In conclusion, results of this study can be implemented in an updated version of the ECRES algorithm allowing an easy estimate of CHO supplement also in highly trained subjects. This useful support system can enhance the self-management of glycaemia during the training sessions of athletic patients throughout mHealth technologies