Biomedical subjects

Silvia Miano

Publications and source records attributed to Silvia Miano.

14 recordsLinked to original sources

PubMed2026

One in three patients with positional obstructive sleep apnea does not benefit from positional therapy: Insights from a home-based trial.

PURPOSE: Positional obstructive sleep apnea (POSA) is the most common phenotype of obstructive sleep apnea, yet patient selection for positional therapy (PT) remains suboptimal. With this analysis we aimed to clarify how many patients with POSA may not require PT because they do not habitually sleep supine at home, and how many fail vibrotactile PT despite appropriate indication. METHODS: We conducted a retrospective observational study of consecutive adults with POSA evaluated at a tertiary sleep center between 2021 and 2024. All patients underwent a home-based trial with a neck-based vibrotactile positional therapy device (Night Shift™), consisting of monitoring mode followed by therapy mode. Outcomes included the proportion of non-supine sleepers at home, failure rate of vibrotactile PT, device compliance and differences in supine sleep time between diagnostic testing and home monitoring. RESULTS: Of 92 screened patients, 74 met inclusion criteria (mean age 60.3 ± 13.2 years; mean AHI 22.9 ± 13.3 events/h). Fifteen percent (11/74) did not habitually sleep supine at home, indicating no clinical need for PT, and an additional 14.8% (11/74) failed vibrotactile PT. Overall, 30% of patients were either unlikely to benefit from PT or failed therapy. Non-response was frequently associated with psychotropic or sedative medication use and neurological or sleep-related comorbidities. CONCLUSION: A substantial proportion of patients diagnosed with POSA either do not require or fail vibrotactile treatment in real-world conditions. Incorporating a brief home monitoring and therapy trial into routine clinical practice may optimize patient selection, reduce unnecessary costs, and improve personalized management of POSA.

Humans↗

PubMed2006

The time structure of the cyclic alternating pattern during sleep.

STUDY OBJECTIVES: To analyze the intervals between A phases of the cyclic alternating pattern (CAP) and to describe their time structure. This might represent an additional aspect to be studied in sleep pathologies that are accompanied by CAP changes. METHODS: Sleep stages and CAP A phases were identified in polysomnographic night recordings of normal adults and children. Intervals between consecutive CAP A phases were measured, counted, and used to draw individual normalized distribution graphs. The intervals during light sleep (stages 1 and 2) were analyzed separately from those occurring during slow-wave sleep (SWS). Subsequently, we performed a Markovian analysis of intervals, in order to describe in detail their time structure. SETTING: N/A. PARTICIPANTS: Twenty-four adults and 28 children. MEASUREMENTS AND RESULTS: In adults, a preponderance of intervals shorter than 60 seconds during SWS was found; light sleep showed a higher number of intervals longer than 60 seconds. A less clear-cut difference between stages was found in children, who showed a shift of the peak in their SWS histogram toward intervals shorter than in adults. Interval sequences were not determined by a random process in both groups. The Markovian analysis showed statistically significant lower values of entropy and higher values of time dependency, mostly in adults during SWS. CONCLUSIONS: The different CAP components of sleep occur in a non-random ordered fashion, and their time structure is characterized by first-order relationships. SIGNIFICANCE: We postulate that CAP components are the expression of a timely ordered process that exhibits specific sleep stage-related features and undergoes age-related modifications.

Child↗

PubMed2006

NREM sleep instability is reduced in children with attention-deficit/hyperactivity disorder.

STUDY OBJECTIVES: To evaluate non-rapid eye movement sleep instability (NREM), as measured by the cyclic alternating pattern (CAP), in a cohort of children with attention-deficit/hyperactivity disorder (ADHD) and normal controls. DESIGN: Prospective study. SETTINGS: Sleep laboratory. PARTICIPANTS: Twenty consecutive outpatients with ADHD (18 boys and 2 girls; age range 6-13 years, mean age 9.3 years) and 20 normal children matched for age and socioeconomic status underwent polysomnographic recordings for 2 consecutive nights in a standard laboratory setting. Sleep was visually scored for sleep macrostructure and CAP, according to standard criteria. MEASUREMENTS AND RESULTS: Children with ADHD showed significantly reduced sleep duration and increased rate of stage shifts. All children with ADHD had an apnea-hypopnea index less than 1. Those with ADHD presented lower total CAP rates and lower CAP rates during sleep stage 2 than did normal controls. Moreover, in children with ADHD, we found a lower number of CAP sequences and a reduced total A1 index, mainly in light sleep (sleep stages 1 and 2). We did not find differences in A subtype percentages, but there was a longer duration of A1 subtypes in children with ADHD. CONCLUSIONS: Children with ADHD showed a lower CAP rate and a lower number of CAP sequences; this supports the hypothesis of the existence of a hypoarousal state in these patients.

Adolescent↗

PubMed2005

NREM sleep alterations in narcolepsy/cataplexy.

OBJECTIVE: NREM sleep patterns of narcoleptic patients with cataplexy were studied, focusing on their sleep 'microstructure', by analyzing the cyclic alternating pattern (CAP). METHODS: Forty-nine HLA DQB1*0602-positive patients with narcolepsy/cataplexy (32 men and 17 women, aged 18-46 years) were included together with 37 age-matched normal controls. Each subject underwent one polysomnographic night recording after an adaptation night. Sleep stages were scored following standard criteria and CAP A phases were detected and classified into 3 subtypes (A1, A2, and A3). Power spectra for frequencies between 0.5 and 25 Hz were obtained for each CAP condition, separately in sleep stage 2 and SWS. RESULTS: Narcoleptic patients displayed reduced total CAP rate. A selective reduction in the number of A1 subtypes/hour and a reduced A3 index were found in narcoleptics who had also a smaller average number of CAP sequences. Narcoleptic patients had higher power spectra for fast frequencies mostly during SWS, while REM sleep power spectra showed significantly higher power density for frequency bins 0.5-1.5, 8.5-9.5, and 17.5-25 Hz. Similarly, CAP A1 subtypes and NCAP epochs during SWS displayed significantly higher power density for fast frequency bins. CONCLUSIONS: The main finding of this study is that the occurrence of the A1 CAP subtypes is impaired during NREM sleep in narcoleptic patients. Thus, narcolepsy seems to be accompanied not only by alterations of REM but also NREM sleep which is subtly but significantly impaired, as reflected by CAP and the corresponding EEG spectral analysis. SIGNIFICANCE: Our findings might indicate that in narcolepsy very-slow oscillation processes less effective than normal might be present, with a subtly impaired capability of grouping the other sleep EEG activities; this aspect deserves further insight in order to obtain a better understanding of its functional meaning.

Adult↗

PubMed2005

Sleep breathing and periodic leg movement pattern in Angelman Syndrome: a polysomnographic study.

OBJECTIVE: The aim of this study was to evaluate the sleep breathing patterns and to detect the eventual presence of periodic leg movements (PLMs) in patients affected by Angelman syndrome (AS). METHODS: Ten children with AS were recruited to participate in the study; the clinical diagnosis was confirmed by the genetic analysis (maternal 15q deletion, uniparental paternal disomy, or mutation of the UBE3A gene). All patients but two had presented epileptic seizures. Two age-matched groups of patients with mental retardation (MR) associated (MRE+) or not (MRE-) to epilepsy were used as control groups. All subjects underwent one polysomnographic recording, after one adaptation night. Sleep stages were scored according to standard criteria slightly modified in order to take into account the specific EEG patterns of AS, also the apnea/hypopnea index (AHI) was quantified; PLMs were identified and the PLM index (PLMI) was computed. The statistical analysis was carried out by means of the one-way ANOVA, followed by the Fisher LSD post-hoc test, when appropriate, and by means of the linear correlation coefficient between AHI and PLMI. RESULTS: Sleep macrostructure showed only few significant differences between children with AS and the other two groups of subjects: AS patients showed higher percentage of wakefulness after sleep onset and sleep onset latency; moreover, the percentage of REM sleep was reduced in AS and in MRE+ subjects. A tendency for AS subjects to present a higher PLMI than the other two groups was also found. AHI >5 was found in 30% of AS subjects, in 30.8% of MRE+, and only in 20% of MRE- patients (chi(2) = 2.359, NS); 70% of AS patients, 38.5% of MRE+, and 46.7% of MRE- subjects had PLMI >5 (chi(2) = 3.088, NS). CONCLUSIONS: These results confirm our previous questionnaire-based findings of a high prevalence of sleep breathing disorder and important PLMs in AS and allow us to hypothesize that epilepsy, rather than mental retardation, might exacerbate these sleep disorders. SIGNIFICANCE: Sleep breathing disorder and PLMs might contribute to the cognitive impairment and to the worsening of life quality of subjects with AS and with MR (mostly those with epilepsy). Therefore, our findings suggest the need to explore these sleep disorders in children affected by MR and to set up a correct treatment.

Adolescent↗

PubMed2005

Computer-assisted detection of nocturnal leg motor activity in patients with restless legs syndrome and periodic leg movements during sleep.

STUDY OBJECTIVES: To assess the performance of a new method for automatic detection of periodic leg movements during sleep. METHODS: Leg movements during sleep were visually detected in the tibialis anterior muscles recordings of 15 patients with restless legs syndrome and 15 normal controls. Leg movements were detected automatically by means of a new computer method with which electromyogram signals are first digitally band-pass filtered and then rectified; subsequently, the detection of leg movements is performed by using 2 thresholds: one for the starting point and another to detect the end point of each leg movement. Sensitivity and false-positive rate were obtained; the American Sleep Disorders Association parameters were also computed, and the results analyzed by means of the Kendall W coefficient, the linear correlation coefficient and the Bland-Altman plots. SETTING: N/A. PARTICIPANTS: Fifteen patients with restless legs syndrome and periodic leg movements and 15 controls. MEASUREMENTS AND RESULTS: High values of the Kendall W coefficient of concordance between automatic and visual analysis were found with values close to 1 and the linear correlation coefficient for leg movements index and total leg movements index was > 0.950 (p < .000001). The Bland-Altman plots provided the limits of agreement between visual and computer detection, which were -9.01 and +9.89 for the periodic leg movement index. None of the normal controls was found to have periodic leg movement indexes >5 after automatic analysis. CONCLUSIONS: Our method can be applied to the clinical evaluation of periodic leg movements during sleep, with some caution in patients with a low periodic leg movement indexes. Large-scale research application is possible and can be considered as reliable.

Adult↗

PubMed2005

All-night EEG power spectral analysis of the cyclic alternating pattern components in young adult subjects.

OBJECTIVE: To analyze in detail the frequency content of the different EEG components of the Cyclic Alternating Pattern (CAP), taking into account the ongoing EEG background and the nonCAP (NCAP) periods in the whole night polysomnographic recordings of normal young adults. METHODS: Sixteen normal healthy subjects were included in this study. Each subject underwent one polysomnographic night recording; sleep stages were scored following standard criteria. Subsequently, each CAP A phase was detected in all recordings, during NREM sleep, and classified into 3 subtypes (A1, A2, and A3). The same channel used for the detection of CAP A phases (C3/A2 or C4/A1) was subdivided into 2-s mini-epochs. For each mini-epoch, the corresponding CAP condition was determined and power spectra calculated in the frequency range 0.5-25 Hz. Average spectra were obtained for each CAP condition, separately in sleep stage 2 and SWS, for each subject. Finally, the first 6h of sleep were subdivided into 4 periods of 90 min each and the same spectral analysis was performed for each period. RESULTS: During sleep stage 2, CAP A subtypes differed from NCAP periods for all frequency bins between 0.5 and 25 Hz; this difference was most evident for the lowest frequencies. The B phase following A1 subtypes had a power spectrum significantly higher than that of NCAP, for frequencies between 1 and 11 Hz. The B phase after A2 only differed from NCAP for a small but significant reduction in the sigma band power; this was evident also after A3 subtypes. During SWS, we found similar results. The comparison between the different CAP subtypes also disclosed significant differences related to the stage in which they occurred. Finally, a significant effect of the different sleep periods was found on the different CAP subtypes during sleep stage 2 and on NCAP in both sleep stage 2 and SWS. CONCLUSIONS: CAP subtypes are characterized by clearly different spectra and also the same subtype shows a different power spectrum, during sleep stage 2 or SWS. This finding underlines a probable different functional meaning of the same CAP subtype during different sleep stages. We also found 3 clear peaks of difference between CAP subtypes and NCAP in the delta, alpha, and beta frequency ranges which might indicate the presence of 3 frequency components characterizing CAP subtypes, in different proportion in each of them. The B component of CAP differs from NCAP because of a decrease in power in the sigma frequency range. SIGNIFICANCE: This study shows that A components of CAP might correspond to periods in which the very-slow delta activity of sleep groups a range of different EEG activities, including the sigma and beta bands, while the B phase of CAP might correspond to a period in which this activity is quiescent or inhibited.

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↗

PubMed2004

Topographic mapping of the spectral components of the cyclic alternating pattern (CAP).

BACKGROUND AND PURPOSE: The aim of this study was to define quantitatively the spectrum content of the sleep pattern termed 'cyclic alternating pattern' (CAP) A phases, their scalp topography and their probable cortical generators, by using data from sleep polygraphic recordings that included a large number of scalp EEG channels. PATIENTS AND METHODS: Polysomnographic recording that include 19 EEG channels were obtained from 5 normal healthy young controls. After sleep staging, for each subject, 5 different CAP A phase subtype epochs were selected, which served for subsequent analysis. Following the analysis of power spectra calculated on the C4 channel by means of the fast Fourier transform, two different frequency bands were detected: 0.25-2.5 and 7-12Hz, representing the frequency peak in the profiles of the different CAP subtypes. All the subsequent analyses were performed on these two bands. Scalp topographic color mapping was carried out using the data from all the 19 EEG channels recorded, and by means of the 4-nearest neighbor algorithm. Individual average maps were obtained for both frequency bands. Finally, we used the low resolution brain electromagnetic tomography (LORETA) functional imaging for the source analysis of the two EEG frequency components of CAP A phases. RESULTS: The quantitative spectral analysis of the different A phase subtypes shows the existence of two distinct spectral components characterizing CAP subtypes A1 (0.25-2.5Hz) and A3 (7-12Hz). These two components coexist in CAP A2 subtypes. The topography of these two components shows a clear prevalence over the anterior frontal regions for the 0.25-2.5Hz band and over the parietal-occipital areas for the 7-12Hz band. Finally, the generators of the low-frequency component of CAP seemed to be localized mostly over the frontal midline cortex; on the contrary, those of the high-frequency band involved both midline and hemispheric areas within the parietal and occipital areas. CONCLUSIONS: The results of this study confirm the presence of two fundamentally distinct frequency bands which are expressed individually (A1 and A3) or in association (A2) in the different CAP A phase subtypes. The analysis of scalp distribution maps indicates that the two frequency components recognized are distributed over clearly different areas of the scalp. Moreover, the LORETA analysis indicates that also the probable cortical generators of these two frequency bands are different and well separated and distinct.

Adult↗

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

L -5-Hydroxytryptophan treatment of sleep terrors in children.

UNLABELLED: To test the hypothesis that the administration of L -5-hydroxytryptophan (L -5-HTP) might exert beneficial effects on sleep terrors, we carried out an open pharmacological trial in a group of children with sleep terrors compared to a group of children with the same disorder but without L -5-HTP treatment. Participants in the trial were 45 children (34 males and 11 females; age range 3.2-10.6 years), referred to the Sleep Centre of the Department of Developmental Neurology and Psychiatry of the University of Rome "La Sapienza", affected by sleep terrors. All subjects underwent: (1) complete medical and sleep history; (2) complete neurological examination and EEG recording whilst awake and sleeping, (3) a structured sleep diary for 2 months, (4) after 1 month, all subjects were examined again from the clinical and EEG points of view and (5) after 6 months, a structured interview in order to evaluate the clinical outcome. After the first visit, L -5-HTP was administered (2 mg/kg per day) at bedtime to 31 randomly selected patients for a single period of 20 consecutive days. After 1 month of treatment, 29/31 (93.5%) of patients showed a positive response. In the comparison group without drug therapy, after 1 month, the episodes disappeared only in four children (28.6%) while ten children (71.4%) showed the persistence of episodes with the same frequency as before. After 6 months, 26/31 (83.9%) of children treated with L -5HTP were sleep terror-free, while in five children (16.1%) sleep terror episodes persisted. Of the children in the comparison group, ten (71.4%) continued to show sleep terrors at 6-month follow-up. CONCLUSION: to our knowledge, this is the first study demonstrating the efficacy of a new drug treatment for sleep terrors. These results confirm our initial hypothesis and represent evidence that treatment with L -5-hydroxytryptophan is able to modulate the arousal level in children and to induce a long-term improvement of sleep terrors.

5-Hydroxytryptophan↗

PubMed2004

Sleep polygraphy in Angelman syndrome.

OBJECTIVE: Sleep disturbances are frequent in Angelman syndrome (AS); however, beside the few studies which have investigated sleep disorders in AS by means of questionnaires, to our knowledge, no systematic polysomnographic recordings have been carried out in AS patients. The present study represents the first attempt to study sleep patterns of AS by polysomnography, to evaluate the influences of sleep on the paroxysmal electroencephalogram (EEG) patterns of AS and to assess the eventual age-related changes of sleep architecture and of sleep EEG abnormalities in children and adolescents with AS. METHODS: Fifteen children with AS (7 males and 8 females, mean age 7.2 years, range 3-16 years), attending the Sleep Center of the Department of Child Neurology and Psychiatry of the University of Rome 'La Sapienza' and the Sleep Research Centre of the Oasi Institute (IRCCS) of Troina were included and subdivided into two subgroups by age: subgroup 1, aged 3-5 years, and subgroup 2, aged 9-17 years. Two control groups of age-matched normal subjects were also included: one aged less than 8 years and another aged more than 8 years; additionally, two other groups of age-matched children with epilepsy and mental retardation of different origin, one aged less and one aged more than 9 years were taken into consideration. The statistical comparison between the sleep parameters obtained from the patients and those from the other groups was carried out by means of the non-parametric Kruskal-Wallis ANOVA and the Mann-Whitney U test. RESULTS: The most frequent EEG abnormality found in AS patients appeared to be the 2-3 c/s poorly defined spike/waves complexes. This pattern was influenced by sleep stages; the duration of the runs showed an increasing length with sleep deepening from sleep stage 1 to slow-wave sleep (SWS). Moreover, the 2-3 c/s bursts activity present in sleep stage 2 showed a slowing to 1-2 c/s during SWS. Regarding sleep architecture, in subjects with AS aged <8 year there was a significant reduction in sleep efficiency as compared to normal controls, while the percentage and duration of REM sleep was significantly lower and the percentage of SWS was significantly higher. REM sleep time was reduced in AS subjects aged >8 years than in normal controls. The comparison between AS groups and mental retardation with epilepsy groups did not show significant differences. CONCLUSIONS: Similarly to other types of genetically determined mental retardation syndromes, also subjects with AS seems to show important abnormalities of their sleep polysomnographic patterns. SIGNIFICANCE: This is the first study which reports, in detail, these abnormalities and opens a new path for further insight into the knowledge of additional sleep-related disturbances which are reported in sleep questionnaires by the caregivers of AS subjects.

Adolescent↗

PubMed2004

Sleep disturbances in Angelman syndrome: a questionnaire study.

Only few studies are available on sleep disorders in Angelman syndrome (AS), a neurodevelopmental disorder with several behavior disturbances. The aim of this study was to determine the prevalence of sleep disorders in a relatively large group of AS subjects, compared to that of age-matched controls. Forty-nine consecutive parents of patients with AS (26 males and 23 females aged 2.3-26.2 years) were interviewed and filled out a comprehensive sleep questionnaire. Based on their genetic etiology, four groups were defined: deletion of chromosome 15q11-13 (25 subjects); methylation imprinting mutation (six subjects), UBE3A mutations (seven subjects) and paternal uniparental disomy (five subjects). In the remaining cases genetic testings were negative. A significantly high frequency of disorders of initiating and maintaining sleep, prolonged sleep latency, prolonged wakefulness after sleep onset, high number of night awakenings and reduced total sleep time were found in our AS patients, as compared to age-matched controls. We also found other types of sleep disorders, never reported before, such as enuresis, bruxism, sleep terrors, somnambulism, nocturnal hyperkinesia, and snoring. No differences were found between the four genetic aetiology groups. Moreover, we did not find important improvement of sleep disturbances from pre-pubertal to post-pubertal ages. Our data confirm the significant presence of sleep/wake rhythms fragmentation, peculiar of AS, and also demonstrate the presence of several other types of sleep disturbances in this syndrome.

Adolescent↗

PubMed2002

Sleep cyclic alternating pattern in normal school-age children.

OBJECTIVES: To evaluate cyclic alternating pattern (CAP) in sleep of school-age children in order to obtain a standardized database for CAP parameters in this age range. METHODS: CAP parameters were quantified in 10 normal healthy subjects (6 males and 4 females, mean age 8.3 years; range 6-10 years). All subjects underwent polysomnography recordings for two consecutive nights in a standard laboratory setting. Sleep data were stored on computer using a 16-channel polysomnography digital system. Sleep macrostructure was visually scored according to the criteria by Rechtschaffen and Kales (Brain Information Service/Brain Research Institute, University of California, Los Angeles, 1968); CAP was visually scored following the criteria by Terzano et al. (Sleep Med 2 (2001) 537). RESULTS: CAP rate showed a progressive increase with the deepness of sleep, with high values during slow wave sleep (SWS). CAP time showed its longest duration during non-REM (NREM) sleep stage 2 (S2), followed by SWS and sleep stage 1 (S1). No differences across NREM sleep stages were found for CAP cycle and phase B mean duration; on the contrary, phase A showed longer duration during SWS than in S1 and S2. Phases A1 were the most numerous (84.45%) followed by A3 (9.14%) and by A2 (6.44%). The distribution of phases A subtypes across NREM stages showed significant differences for the A1 subtypes that occurred more frequently during SWS than in S2 and S1 (and during S2 than in S1). Subtypes A3 were more frequent during S1 than SWS while no differences were found for subtype A2. The analysis of A1 interval distribution showed a log-normal-like distribution with a peak around 25 s for the A1 phases and no clear peak for A2-A3 phases. CONCLUSIONS: The analysis of CAP in school-age children is characterized by an increase of CAP rate during SWS and a high percentage of A1 phases. The distribution of interval between consecutive A1 phases showed a peak around 25 s.

Child↗