Memorization test and resting state EEG components in mild and subjective cognitive impairment

BACKGROUND: Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer's disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. OBJECTIVE: The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. METHOD: We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. RESULTS: During cognitive task, \u3b1-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The \u3b1 -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. CONCLUSION: This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Connectivity and frequency analyses of sleep EEG in ADHD and healthy children

Il disturbo da deficit di attenzione/iperattivit\ue0 (ADHD), \ue8 un disturbo neurocomportamentale caratterizzato da deficit di attenzione, iperattivit\ue0 e impulsivit\ue0. Attualmente, la diagnosi di ADHD si basa su questionari standard come DSM-IV e DSM-V. Si tratta di interviste strutturate, compilate da genitori e insegnanti, per valutare la presenza e il livello di gravit\ue0 delle sintomatologie in diversi ambiti sociali. Tuttavia, questa metodologia indiretta e soggettiva dovrebbe essere supportata da misure pi\uf9 obiettive basate sull'analisi clinica strumentale. In passato, l'EEG \ue8 stato utilizzato per estrarre e valutare il rapporto tra le potenze nelle bande theta e beta (theta/beta ratio). Tale rapporto era stato definito dalla FDA (Food and Drug Administration) come misura diagnostica per l'ADHD. Negli ultimi 5 anni, a causa dell'elevato numero di studi che non hanno confermato i valori di specificit\ue0 di questo rapporto nell'ADHD, esso \ue8 stato dichiarato non utilizzabile ai fini diagnostici. Il problema fondamentale nella diagnosi dell'ADHD \ue8 la mancanza di un qualsiasi marker fisiologico o biologico della malattia. \par Negli ultimi anni, l'ADHD \ue8 stato anche correlato con vari problemi del sonno e la copresenza di questi ultimi intensifica la sintomatologia preesistente. Sebbene l'associazione tra disturbi del sonno e ADHD sia ben nota, la correlazione con aspetti pi\uf9 specifici legati alla microstruttura del sonno e con eventuali modificazioni del funzionamento cerebrale, durante il sonno, non \ue8 stata ancora completamente compresa. \par Uno degli aspetti della microstruttura del sonno che ha visto un crescente interesse nell'ambito della ricerca sui disturbi neurologici e altre patologie sono i fusi del sonno. Le loro variazioni e anomalie sono state associate alle facolt\ue0 cognitive e all'intelligenza, a varie condizioni di malattia (ad es. Schizofrenia, ritardo mentale, anormale maturazione), a processi di recupero post-ictus, nonch\ue9 si credono essere coinvolti nel consolidamento della memoria durante il sonno. In aggiunta all'interesse per i fusi del sonno, vi \ue8 anche un aumento degli studi relativi alle modifiche dinamiche delle attivit\ue0 del cervello nel sonno. \par L'attivit\ue0 oscillatoria del cervello, in termini di potenza dell'EEG e dell'analisi della connettivit\ue0, \ue8 stata poco studiata nell'ADHD, cos\uec come anche le variazioni temporali prima, durante e dopo l'evento del fuso non sono ancora state indagate. Questa tesi studia l'attivit\ue0 EEG attraverso l'analisi spettrale e attraverso parametri legati alla teoria dei grafi, al fine di fornire informazioni pi\uf9 dettagliate sul funzionamento del cervello durante il sonno nell'ADHD ed eventualmente valutare la possibilit\ue0 di utilizzare queste caratteristiche come nuovi biomarcatori. \par La novit\ue0 descritta consiste nell'analisi di diverse epoche temporali, scelte dagli spettri di potenza del segnale EEG. L'analisi spettrale e della connettivit\ue0 hanno evidenziato differenze tra il fuso e le altre due epoche, rispettivamente prima e dopo il fuso, in entrambi i gruppi analizzati (ADHD e soggetti sani) in quasi tutti i parametri. Inoltre, il confronto tra i due gruppi ha mostrato che le differenze erano concentrate nell'emisfero sinistro. Ultimo ma non meno importante, i risultati portano l'attenzione sulla banda gamma e confermano la sempre pi\uf9 crescente letteratura, riguardante questa banda. Ci\uf2, sottolinea come le attivit\ue0 presenti in questa gamma abbiano un significato cognitivo in grado di descrivere e differenziare alcuni disturbi neuropsichiatrici.Attention-deficit / hyperactivity disorder (ADHD) is a neurobehavioral disorder characterized by attention deficit, hyperactivity, and impulsivity. Currently, the diagnosis of ADHD is based on standard questionnaires such as DSM-IV and DSM-V. These are structured interviews, administrated to parents and teachers, to evaluate the presence and the severity level of the symptoms in different social fields. However, this indirect and subjective methodology should be supported by more objective measures based on instrumental clinical analyses. \par In the past, the EEG was used to extract and evaluate the ratio between the powers in the theta and beta bands (theta/beta ratio). This ratio was defined by the FDA (Food and Drug Administration) as a diagnostic measure for ADHD. In the last 5 years, this ratio has been declared not diagnostic, due to the high number of studies that did not confirm its specificity values in ADHD. The fundamental problem in diagnosing ADHD is the lack of any physiological or biological marker of the disease. \par In recent years, ADHD has also been related to various sleep problems and their coexistence intensifies the pre-existing symptomatology. Although the association between sleep disorders and ADHD is well known, the correlation with more specific aspects related to the microstructure of sleep and with possible modifications of brain functioning during sleep has not been completely understood. \par One of the aspects of sleep microstructure that has seen a growing interest in neurological disorders research and other diseases research are sleep spindles. Their variations and disruptions have been associated with cognitive faculties and intelligence, with various disease conditions (eg Schizophrenia, mental retardation, abnormal maturation), with post-stroke recovery processes, and they seem to be involved in sleep-dependent memory consolidation. In addition to the interest in sleep spindles, there is also an increase in studies related to dynamic changes in brain activity during sleep. \par The oscillatory activity of the brain, in terms of EEG power and analysis of connectivity, has been poorly studied in ADHD, as well as the temporal variations before, during and after the spindle event have not yet been investigated. Therefore, this doctoral thesis studies EEG activity, through spectral analysis and parameters related to graph theory, in order to provide more detailed information about brain functioning during sleep in ADHD and to evaluate the possibility of using these features as new biomarkers. \par The novelty described in this thesis consists in the analysis of different time periods, chosen after the power spectra analysis of the EEG signal, in order to evaluate temporal and dynamic changes of spindles activity. Spectral and connectivity analysis showed differences between the spindle and the other two epochs, before and after spindle onset respectively, in both groups in almost all parameters. Furthermore, the comparison between the two groups showed that the differences were concentrated in the left hemisphere. Last but not least, the results raise attention to the gamma band and confirm the increasingly growing literature concerning this band, thus underlining how the activities in this frequency range have a cognitive meaning able to describe and differentiate some neuropsychiatric disorders

Power Spectral Density Analysis in Spindles Epochs in Healthy Children

Sleep spindles are important components of the N-REM stage-2 in the sleep electroencephalogram (EEG). They are oscillatory EEG activities of fusiform morphology in the range of 10\u201316 Hz [1], and a duration between 0.5 and 3 s. Spindles have been associated with cognitive skills and sleep-dependent memory consolidation. The aim of this study is to assess differences in the before (\u201cpre\u201d), during (\u201cdur\u201d) and after (\u201cpost\u201d) spindle epochs by means of main power spectral bands delta (2\u20134 Hz), theta (4\u20138 Hz), alpha (8\u201312 Hz), beta (12\u201330 Hz), gamma (30\u201344 Hz), total (2\u201344 Hz) and sigma bands (12\u201316 Hz), calculated by the Welch periodogram, and by Fractal dimension (FD). The analysis was carried out on 7 healthy children (mean age = 8.90 \ub1 1.34 years) deprived of sleep on the day of the acquisition to enhance the deep sleep during the recording. For each EEG record (standard 10\u201320, 19 electrodes, sampling rate 512 Hz), two neurophysiologists labeled the start and the end points of the three sleep epochs. The results showed statistical differences between \u201cdur\u201d and both \u201cpre\u201d and \u201cpost\u201d epochs in almost all channels (except O1 and O2) for all bands, except gamma. Furthermore, the values of FD were significantly different between \u201cdur\u201d and both \u201cpre\u201d and \u201cpost\u201d epochs, for all channels. The FD values in \u201cdur\u201d epochs were smaller than in both \u201cpre\u201d and \u201cpost\u201d ones, showing a lower EEG complexity during spindles, compared with the \u201cpre\u201d and \u201cpost\u201d epochs. FD values in \u201cpost\u201d epochs were found similar to those in \u201cpre\u201d periods. These differences could be useful to comprehend the spindles changes during sleep time. Moreover, these data could help on understanding the system generator of the spindles

A Big-Data-Analytics Framework for Supporting Classification of ADHD and Healthy Children via Principal Component Analysis of EEG Sleep Spindles Power Spectra

Attention Deficit Hyperactivity Disorder (ADHD) diagnosis is essentially clinical and research of biomarkers represents a current great challenge. The interest in sleep spindle has been increased after the description of their role in cognitive functions and of their involvement in neurodevelopmental disorders. We aimed to investigate this peculiar aspect of sleep through EEG spectral analysis of three different spindle epochs (ante, spindle, post), in order to provide more and detailed information on sleep brain functioning in ADHD. These features can be analyzed via well-known big data analytics methods. In our case, they were evaluated by using classification methods to support ADHD diagnosis. We combined ADHD\u2019s related PSD features (i.e. theta, beta and sigma bands) with principal component analysis (PCA) for data dimensional reduction, and Linear Supported Vector Machine (Linear-SVM) as classification algorithm. In all bands and epochs, power values in Control group were higher than in ADHD children, although not statistically significant in all cases. Significant differences between ADHD and Control group were not detected for spindle epoch, while for ante and post epochs spectral power differed significantly in theta, beta and sigma bands. Results highlighted the possibility of using our new approach as a possible hallmark for ADHD. Indeed the analysis of PSD parameters combined with PCA and Linear-SVM classification resulted in a highly (94.1%) accurate discrimination between the two groups. The novelty of the approach is PSD analysis of different sleep spindles epochs combined with principal component analysis and Linear Supported Vector Machine classification. This study demonstrated the importance of analyzing sleep microstructures in ADHD. Encouraging results supports the potentiality of using EEG measures with specific methodologies we applied and should be confirmed in a large clinical study

Circadian blood pressure pattern in positive drug responsive hypertensives, hypertensives and normotensives, and gender influences.

Circadian rhythm is a characteristic behavior of human physiology and it is known that, in healthy subjects, blood pressure (BP) increases during the day and decreases during the night, as a result of sleep-wake changes. Some studies highlighted that female had lower office BP values than male and this should be considered for define the threshold of hypertension. With the introduction of the Holter Blood Pressure Measurement, it has been possible to record the blood pressure for 24 hours. This innovation allowed to analyze the circadian Blood pressure pattern (CBPP) and some studies identified the differences between normotensives and hypertensives subjects. In this study, we examined the circadian pattern in positive drug responsive hypertensive patients in respect of negative ones and of normotensive subjects and the differences due to gender. The results demonstrated that positive drug responsive hypertensive patients had the same circadian blood pressure pattern as normotensives. Moreover, the difference in circadian blood pressure values between male and female was about 2-4 mmHg

A mobile app for the self-management of type 1 diabetes as tool for preventing of exercise-associated glycemic imbalances

mHealth is a growing field of research, concerning the great potentialities of mobile technology as a tool for self-management of chronic conditions. Physical activity greatly influences blood glucose levels, therefore for type 1 diabetes patients is important to adapt their diet and therapy in order to avoid exercise-induced hyperglycemia and hypoglycemia. The later represents one of the major barriers to physical activity and it limits volitional exercise in type 1 diabetes patients. However, there is lack of stand-alone mobile tool that provides the support to the patient in order to perform physical activity and exercise under safe glycaemia levels. Recently, Exercise Carbohydrate Requirement Estimating Software (ECRES) algorithm was proposed to calculate patient-exercise tailored glucose supplement required to maintain safe blood glucose levels during physical activity. The objective of this study was to develop a mobile App which implements an individualized predictive system for blood glucose in type 1 diabetes, depending on exercise strength. Its usability and accuracy were compared to original ECRES estimating software in 15 volunteer subjects. The developed application provides relevant feedback to patients on carbohydrate intake needed to carry out a planned physical activity, in a safe manner. Furthermore, application provides other important features, for self-management of this chronicity, reported in recent literature: entry of blood glucose values, display of diabetes-related data, such as blood glucose readings and their analysis, carbohydrate intake, insulin doses, and easy data export. The application also incorporates food atlas in order to facilitate carbohydrates calculation. The results of the test showed that developed application accurately implements ECRES algorithm and the self-management features. In conclusion, proposed App could be a useful support tool to diabetes type 1 patents. The results should be confirmed in larger clinical study