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Biomedical subjects

Arianna Smerieri

Publications and source records attributed to Arianna Smerieri.

12 recordsLinked to original sources
PubMed2006

Cyclic alternating pattern (CAP) alterations in narcolepsy.

BACKGROUND AND PURPOSE: Narcolepsy is a sleep disorder with clinical symptoms attributed to a reduced activation of the arousal system. Cyclic alternating pattern (CAP) is the expression of rhythmic arousability during non-rapid eye movement (NREM) sleep. CAP parameters, arousals and conventional sleep measures were studied in narcoleptic patients with cataplexy. PATIENTS AND METHODS: Data were collected from all-night polysomnographic (PSG) recordings and the multiple sleep latency test (MSLT) on the intervening day of 25 drug-naive patients (10 males and 15 females; mean age: 34+/-16 years) after adaptation and exclusion of other sleep disorders. A group of 25 age- and gender-matched normal sleepers were selected as controls. Each PSG recording was subdivided into sleep cycles. Analysis of CAP included classification of A phases into subtypes A1, A2, and A3. RESULTS: There was an increase in sleep period time mainly due to an increased wake time after sleep onset. REM latency was sharply reduced. The percentage of NREM sleep was slightly reduced and the balance between light sleep (S1+S2) and deep sleep (S3+S4) showed a curtailment of the former, while deep sleep was slightly increased. Excluding sleep cycles with sleep onset REM periods (SOREMPs), the duration of ordered sleep cycles was not different between narcoleptics and controls. The two groups showed similar values of arousal index, while CAP time, CAP rate, number of CAP cycles and of phase A subtypes (in particular subtypes A1) were significantly reduced in narcoleptic patients. CONCLUSIONS: The reduced periods of CAP in narcoleptic NREM sleep could be the electroencephalographic (EEG) expression of a generally reduced arousability or an increased strength of sleep-promoting forces in the balance between sleep and arousal systems. This can explain some of the clinical correlates of the disorder, i.e. excessive sleepiness, short sleep latency and impaired attentive performances, even without any sign of arousal-induced sleep fragmentation.

Adolescent↗
PubMed2005

Reorganization of sleep patterns in severe OSAS under prolonged CPAP treatment.

OBJECTIVE: To evaluate the immediate and long-term recovery processes of sleep and daytime vigilance in patients with sleep apnea syndrome (OSAS) after continuous CPAP treatment. METHODS: Five consecutive polysomnographic (PSG) studies were carried out on 10 male patients with severe OSAS. The first recording (baseline) was accomplished without ventilatory support (N0). The other 4 recordings were carried out during the CPAP titration night (N1), during the second night of treatment (N2), during the third night of treatment (N3), and after 30 days of regular CPAP use (N30). Ten age-balanced healthy male subjects were selected from the Parma Sleep Center database as controls. Respiratory variables, conventional PSG variables, arousals, CAP (cyclic alternating pattern) variables, and daytime function (including MSLT) were quantified. ANOVA followed by post-hoc tests explored the differences between controls and OSAS patients in the different recording conditions (N0, N1, N2, N3, N30). The PSG measures that showed significant ANOVA values were correlated with the MSLT scores. RESULTS: Values of control subjects were recovered by REM sleep, REM latency, subtypes A3 and arousal index during N1, by CAP rate and total arousals during N2, by deep sleep (stages 3 + 4) during N3, by light sleep (stages 1 + 2) during N30. The only measures which remained below control values even after 1 month of sustained treatment were the amount of CAP cycles and A1 subtypes. MSLT scores correlated significantly with CAP rate, deep sleep and arousals. CONCLUSIONS: The changes induced by CPAP treatment do not restore immediately a normal sleep structure, which is re-established with different time scales SIGNIFICANCE: The modifications of sleep patterns and the different adjustments of phase A subtypes allow us to monitor the reorganization of sleep in OSAS patients treated with CPAP and the hierarchy of the mechanisms involved in sleep regulation.

Adult↗
PubMed2005

Sleep cyclic alternating pattern in normal preschool-aged children.

STUDY OBJECTIVES: To evaluate the characteristics of the cyclic alternating pattern (CAP) in the sleep of preschool-aged children in order to obtain normative parameters in this age range. DESIGN: Prospective study. SETTINGS: University sleep laboratory. PARTICIPANTS: Ten normal healthy subjects (6 girls and 4 boys, mean age 4.6 years; range 3-6 years) underwent polysomnography recordings for 2 consecutive nights in a standard laboratory setting. Sleep data were stored on a computer using a polysomnography digital system (Embla N7000, Medcare, Iceland). Sleep structure was visually scored according to the Rechtschaffen and Kales criteria. The cyclic alternating pattern was visually scored following the criteria by Terzano et al. These criteria were modified for the purposes of this study because it was noticed that, at the age of the group under analysis, most electroencephalogram arousals, often accompanied by electromyogram activation, are expressed at the level of the electroencephalogram by theta frequencies and not alpha or higher frequencies. MEASUREMENTS AND RESULTS: The CAP rate in preschool-aged children (25.93%) showed a progressive increase with the deepness of sleep, with highest values during non-rapid eye movement (NREM) stage 3 (44.0%) and 4 sleep (46.08%) and lowest values in NREM stage 2 (17.26%). The CAP time showed its longest duration during stage 2 sleep, followed by stage 4, stage 3, and NREM stage 1. The CAP cycle duration showed no differences across NREM stages. The cyclic alternating pattern phase A was longer and phase B was shorter during stage 1 than during stages 2, 3, and 4. A1 phases were the most numerous (63.2%), followed by A2 (21.5%) and by A3 (15.3%). The distribution of A-phase subtypes across NREM sleep stages (A index) showed significant differences for the A1 subtypes that occurred more frequently during stage 3 and 4 sleep than during stages 1 and 2. The A2 index showed no significant differences across NREM sleep stages, while the A3 index was significantly higher during stage 1 sleep than during stages 2, 3, and 4. The analysis of the A1 interval distribution showed a log-normal-like distribution with a peak around 25 seconds for the A1 phases and no clear peak for A2-A3 phases. CONCLUSIONS: The analysis of CAP in preschool-aged children is characterized by an increase of CAP rate during slow-wave sleep and a high percentage of A1 phases and A2 phases. However, the lower percentage of A1 paralleled by an increase of A2 could represent a signal of higher sleep instability in this age group as compared with prepubertal school-aged children.

Adaptation, Physiological↗
PubMed2005

CAP and arousals are involved in the homeostatic and ultradian sleep processes.

There is growing evidence that cyclic alternating pattern (CAP) and arousals are woven into the basic mechanisms of sleep regulation. In the present study, the overnight sleep cycles (SC) of 20 normal subjects were analyzed according to their stage composition, CAP rate, phase A subtypes and arousals. Individual SC were then divided into 10 normalized temporal epochs. CAP parameters and arousals were measured in each epoch and averaged in relation to the SC order. Subtypes A2 and A3 of CAP in non-rapid eye movement (NREM) sleep, and arousals, both in REM and NREM sleep when not coincident with a A2 or A3 phases, were lumped together as fast electroencephalographic (EEG) activities (FA). Subtypes A1 of CAP, characterized by slow EEG activities (SA), were analyzed separately. The time distribution of SA and FA was compared to the mathematical model of normal sleep structure including functions representing the homeostatic process S, the circadian process C, the ultradian process generating NREM/REM cycles and the slow wave activity (SWA) resulting from the interaction between homeostatic and ultradian processes. The relationship between SA and FA and the sleep-model components was evaluated by multiple regression analysis in which SA and FA were considered as dependent variables while the covariates were the process S, process C, SWA, REM-on and REM-off activities and their squared values. Regression was highly significant (P < 0.0001) for both SA and FA. SA were prevalent in the first three SC, and exhibited single or multiple peaks immediately before and in the final part of deep sleep (stages 3 + 4). The peaks of FA were delayed and prevailed during the pre-REM periods of light sleep (stages 1 + 2) and during REM sleep. SA showed an exponential decline across the successive SC, according to the homeostatic process. In contrast, the distribution of FA was not influenced by the order of SC, with periodic peaks of FA occurring before the onset of REM sleep, in accordance with the REM-on switch. The dynamics of CAP and arousals during sleep can be viewed as an intermediate level between cellular activities and macroscale EEG phenomena as they reflect the decay of the homeostatic process and the interaction between REM-off and REM-on mechanisms while are slightly influenced by circadian rhythm.

Activity Cycles↗
PubMed2004

Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method.

OBJECTIVE: To assess inter-rater reliability between different scorers, from different qualified sleep research groups, in scoring visually the Cyclic Alternating Pattern (CAP), to evaluate the performances of a new tool for the computer-assisted detection of CAP, and to compare its output with the data from the different scorers. METHODS: CAP was scored in 11 normal sleep recordings by four different raters, coming from three sleep laboratories. CAP was also scored in the same recordings by means of a new computer-assisted method, implemented in the Hypnolab 1.2 (SWS Soft, Italy) software. Data analysis was performed according to the following steps: (a) the inter-rater reliability of CAP parameters between the four different scorers was carried out by means of the Kendall W coefficient of concordance; (b) the analysis of the agreement between the results of the visual and computer-assisted analysis of CAP parameters was also carried out by means of the Kendall W coefficient; (c) a 'consensus' scoring was obtained, for each recording, from the four scorings provided by the different raters, based on the score of the majority of scorers; (d) the degree of agreement between each scorer and the consensus score and between the computer-assisted analysis and the consensus score was quantified by means of the Cohen's k coefficient; (e) the differences between the number of false positive and false negative detections obtained in the visual and in the computer-assisted analysis were also evaluated by means of the non-parametric Wilcoxon test. RESULTS: The inter-rater reliability of CAP parameters quantified by the Kendall W coefficient of concordance between the four different scorers was high for all the parameters considered and showed values above 0.9 for total CAP time, CAP time in sleep stage 2 and percentage of A phases in sequence; also CAP rate showed a high value (0.829). The most important global parameters of CAP, including total CAP rate and CAP time, scored by the computer-assisted analysis showed a significant concordance with those obtained by the raters. The agreement between the computer-assisted analysis and the consensus scoring for the assignment of the CAP A phase subtype was not distinguishable from that expected from a human scorer. However, the computer-assisted analysis provided a number of false positives and false negatives significantly higher than that of the visual scoring of CAP. CONCLUSIONS: CAP scoring shows good inter-rater reliability and might be compared in different laboratories the results of which might also be pooled together; however, caution should always be taken because of the variability which can be expected in the classical sleep staging. The computer-assisted detection of CAP can be used with some supervision and correction in large studies when only general parameters such as CAP rate are considered; more editing is necessary for the correct use of the other results. SIGNIFICANCE: This article describes the first attempt in the literature to evaluate in a detailed way the inter-rater reliability in scoring CAP parameters of normal sleep and the performances of a human-supervised computerized automatic detection system.

Adult↗
PubMed2004

Is insomnia a neurophysiological disorder? The role of sleep EEG microstructure.

Unlike other sleep disorders, such as sleep-related breathing disorders and periodic limb movement (PLM), the nature and severity of which are quantified by specific respiratory and motor indexes, no apparent organ dysfunction underlies several cases of insomnia (in particular primary insomnia), which can be objectively diagnosed only through the structural alterations of sleep. Polysomnography (PSG) investigation indicates that insomnia is the outcome of a neurophysiological disturbance that impairs the regulatory mechanisms of sleep control, including sleep duration, intensity, continuity and stability. In particular, analysis of sleep microstructure has permitted to establish that etiologic factors of different nature (including depressive disorders) exert a common destabilizing action on sleep, which is reflected in an increase of cyclic alternating pattern (CAP) rate. These premises allow us to attribute a more objective identity to insomnia, which risks otherwise to be considered as an unexplainable mental complaint. In conclusion, PSG remains the "gold standard" for measuring sleep, and especially insomnia.

Antidepressive Agents↗
PubMed2004

Quantitative analysis of sleep EEG microstructure in the time-frequency domain.

A number of phasic events influence sleep quality and sleep macrostructure. The detection of arousals and the analysis of cyclic alternating patterns (CAP) support the evaluation of sleep fragmentation and instability. Sixteen polygraphic overnight recordings were visually inspected for conventional Rechtscaffen and Kales scoring, while arousals were detected following the criteria of the American Sleep Disorders Association (ASDA). Three electroencephalograph (EEG) segments were associated to each event, corresponding to background activity, pre-arousal period and arousal. The study was supplemented by the analysis of time-frequency distribution of EEG within each subtype of phase A in the CAP. The arousals were characterized by the increase of alpha and beta power with regard to background. Within NREM sleep most of the arousals were preceded by a transient increase of delta power. The time-frequency evolution of the phase A of the CAP sequence showed a strong prevalence of delta activity during the whole A1, but high amplitude delta waves were found also in the first 2/3 s of A2 and A3, followed by desynchronization. Our results underline the strict relationship between the ASDA arousals, and the subtype A2 and A3 within the CAP: in both the association between a short sequence of transient slow waves and the successive increase of frequency and decrease of amplitude characterizes the arousal response.

Adult↗
PubMed2003

CAP variables and arousals as sleep electroencephalogram markers for primary insomnia.

OBJECTIVE: Polysomnographic (PSG) measures consistently reflect poor sleep quality and effective treatment in insomniac patients. METHODS: The PSG findings of 47 patients (18 M and 29 F, 42.5+/-10 years) meeting the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for a diagnosis of primary insomnia were compared with those of 25 age- and gender-balanced healthy subjects (controls) without sleep complaints. After one adaptation night to the sleep lab, each patient underwent two randomized double-blind PSG recordings. Twenty-four patients followed a placebo-drug sequence and 23 a drug-placebo succession. Active treatment consisted of widely used hypnotic drugs, i.e. zolpidem, triazolam, zopiclone, brotizolam. Conventional PSG measures, electroencephalogram (EEG) arousals and CAP variables (including phase A subtypes) were quantified and statistically analyzed. RESULTS: Compared to controls, insomniac patients under placebo showed a significant increase of CAP rate, subtypes A1 and A2, EEG arousals, nocturnal wakefulness and stage 1, associated with reduced values of total sleep time and slow wave sleep (stages 3 and 4). In insomniac patients, sleep quality was significantly improved by hypnotic treatment. Compared to placebo, active medication significantly reduced CAP rate, subtypes A1 and A2, but had only marginal effects on subtypes A3 and on EEG arousals. Under hypnotic treatment total sleep time, nocturnal awakenings, stage 1 and slow wave sleep recuperated normal values. The most significant correlation between sleep quality and PSG variables was found for CAP rate (P<0.0001). CONCLUSIONS: PSG investigation extended to CAP variables and EEG arousals can be an important procedure for the diagnosis of primary insomnia and evaluation of treatment efficacy.

Adult↗
PubMed2003

New drugs for insomnia: comparative tolerability of zopiclone, zolpidem and zaleplon.

Insomnia affects 30-35% of people living in developed countries. The impact of insomnia on daytime functioning and its relationship with medical and psychiatric illnesses necessitate early treatment to prevent insomnia becoming persistent and to avoid the development of complications. However, pharmacological strategies must achieve a balance between sedative and adverse effects. In the last 30 years, benzodiazepines have been the preferred drugs for the treatment of insomnia. Benzodiazepines act nonselectively at two central receptor sites, named omega(1) and omega(2), which are located in different areas of the CNS. The sedative action of benzodiazepines is related to omega(1) receptors, whereas omega(2) receptors are responsible for their effects on memory and cognitive functioning. According to their pharmacokinetic profile, benzodiazepines can be classified into three groups: short half-life (<3 hours), medium half-life (8-24 hours) and long half-life (>24 hours). The newer non-benzodiazepine agents zopiclone, zolpidem and zaleplon have a hypnosedative action comparable with that of benzodiazepines, but they display specific pharmacokinetic and pharmacodynamic properties. These three 'Z' agents all share a short plasma half-life and limited duration of action. In addition, these agents are selective compounds that interact preferentially with omega(1) receptors (sedative effect), whereas benzodiazepines also interact with omega(2) receptors (adverse effects on cognitive performance and memory). Zaleplon is characterised by an ultrashort half-life (approximately 1 hour). Zolpidem and zopiclone have longer half-lives (approximately 2.4 and 5 hours, respectively). These properties, together with the low risk of residual effect, may explain the limited negative influences of these agents on daytime performance. Psychomotor tasks and memory capacities appear to be better preserved by non-benzodiazepine agents than by benzodiazepines. When present, cognitive deficits almost exclusively coincide with the peak plasma concentration. In particular, impairment can emerge in the first hours after drug administration, whereas psychomotor and memory tests carried out 7-8 hours later (i.e. in the morning) generally show no relevant alterations. As with benzodiazepines, the three 'Z' non-benzodiazepine agents should be used for a limited period, even in chronic relapsing conditions. Further evaluation is needed of the safety of hypnosedative medications in the long-term management of insomnia.

Acetamides↗
PubMed2002

Non-linear EEG measures during sleep: effects of the different sleep stages and cyclic alternating pattern.

The objective of this work was to study the non-linear aspects of sleep EEG, taking into account the different sleep stages and the peculiar organization of its phasic events in ordered sequences (CAP) by applying a series of new non-linear measures (non-linear cross prediction or NLCP), which appear more reliable for the detection and characterization of non-linear structures in experimental data than the commonly used correlation dimension. Eight healthy subjects aged 18-20 years participated in this study. Polysomnography was performed in all subjects; signals were sampled at 128 Hz and stored on hard disk. The C3 or C4 derivation was used for all the subsequent computational steps, which were performed on EEG epochs (4096 data points) selected from sleep stage 2 (S2) and slow-wave sleep (SWS), in both CAP and non-CAP (NCAP) conditions. Also, epochs from sleep stage 1 (S1), REM and wakefulness preceding sleep were recorded. The dynamic properties of the EEG were assessed by means of the non-linear cross-prediction test, which uses three different 'model' time series in order to predict non-linearly the original data set (Pred, Ama, and Tir). Pred is a measure of the predictability of the time series, and Ama and Tir are measures of asymmetry, indicating non-linear structure. The non-linear measures applied in this study indicate that sleep EEG tends to show non-linear structure only during CAP periods, both during S2 and SWS. Moreover, during CAP periods, non-linearity can only be detected during the phase A1 subtypes (and partially A2) of CAP. The A3 phases show characteristics of non-stationarity and bear some resemblance to wakefulness. Based on the results of this study, sleep might be considered as a dynamically evolving sequence of different states of the EEG, which we could track by detecting non-linearity, mostly in association with CAP. Our results clearly show that detectable non-linearity in the EEG is closely related to the occurrence of the phase A of CAP.

Adolescent↗
PubMed2002

CAP and arousals in the structural development of sleep: an integrative perspective.

OBJECTIVES: It is known that the number of arousals per hour of sleep increases linearly across life, while the amount of cyclic alternating pattern (CAP) undergoes a u-shaped evolution. The present study aimed at investigating the differences, overlaps and age-related distribution of arousals and CAP components, i.e. subtypes A1, A2, A3. The relationship between the phase A subtypes and the structural organization of sleep was also evaluated. METHODS: Forty healthy subjects were examined. Polysomnographic analysis was performed according to the scoring rules for sleep stages, CAP and American Sleep Disorders Association arousals. RESULTS: Arousals occurred more frequently during CAP (40 events per hour) than in total sleep time (18 events per hour), non-rapid eye movement (NREM) sleep (20 events per hour), and rapid eye movement (REM) sleep (12 events per hour). Within CAP, arousals always coincided with a subtype A2 or A3. Both arousals and subtypes A2 and A3 showed a similar evolution with relation to age (linear positive), and to the amounts of light NREM sleep (linear positive) and deep NREM sleep (linear negative). In contrast, subtypes A1 showed a u-shaped profile across the life span and appeared closely related (linear positive) to the time spent in stages 3 and 4. Almost 90% of arousals occurring in NREM sleep were preceded in the previous 3s by a K-complex or a delta burst, indicating a topical involvement of slow electroencephalographic (EEG) components in the arousal build-up. CONCLUSIONS: Arousals show only one side of the multi-faceted activation complexes, whereas the three subtypes of CAP provide a graded picture of arousal features from the strongest A3 subtypes, showing a prevalence of EEG desynchrony, to the weakest A1 phases, which are dominated by EEG synchrony and represent the prevalent components of CAP (60% of all the phase A subtypes).

Journal Article↗