Restless sleep in children: A systematic review

DelRosso, Lourdes M.; Picchietti, Daniel L.; Spruyt, Karen; Bruni, Oliviero; Garcı́a-Borreguero, Diego; Kotagal, Suresh; Owens, Judith; Simakajornboon, Narong; Ferri, Raffaele

doi:10.1016/j.smrv.2020.101406

Cited by 50 publications

(31 citation statements)

References 90 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The subjects of our sample showed sleep disorders and disordered sleep both in acute and chronic phase of the disease, which may be linked to the new entity of restless sleep disorder described by DelRosso et al 18 In particular, PLMD and RSWA were largely represented. Notably, among the 19/23 patients diagnosed with Tic Disorder/Tourette Disorder, 10/19 (52.6%) had a condition of RSWA and 8/19 (42.1%) had a condition of PLMD.…”

Section: Discussionsupporting

confidence: 53%

“…The polysomnographic evaluated parameters were Total Sleep Time (TST), Sleep Efficiency (SE), Sleep Latency (SL), REM Latency, N1% TST, N2% TST, N3% TST, REM% TST, Wake After Sleep Onset % (WASO%), Awakenings, Periodic Limb Movement Index (PLMI), RSWA (REM Sleep Without Atonia), and the presence of Frequent change position as index of restless sleep. 18 The parameter “Ineffective Sleep” has been defined by values of Sleep Efficiency <88%; the parameter “Fragmented Sleep” has been defined by values of WASO > 10% and the diagnosis of Periodic Limb Movement Disorder (PLMD) has been formulated if the PLMI was ≥5.0 events/hr in presence of a clinical sleep disturbance or daytime impairment. The diagnosis of pediatric obstructive sleep apnea syndrome (OSAS) was defined by an AHI >1/hr and the presence of snoring or effortful, paradoxical, or obstructed breathing during the child’ sleep, or in presence of sleepiness, hyperactivity, behavioral problems, or learning problems, according to ICSD-3 criteria for pediatric obstructive sleep apnea.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Neural Networks Analysis of polysomnographic and clinical features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): from sleep alteration to “Brain Fog”

Gagliano¹,

Puligheddu²,

Ronzano³

et al. 2021

NSS

View full text Add to dashboard Cite

Study Objectives PANS (pediatric acute onset neuropsychiatric syndrome) is thought to be the result of several mechanisms and multiple etiologies, ranging from endocrine/metabolic causes to postinfectious autoimmune and neuroinflammatory disorders. Sleep disorders represent one of the most frequent manifestations of PANS, involving around 80% of patients. The present study describes the clinical and polysomnographic features in a group of PANS children identifying the relationships between sleep disorders and other PANS symptoms. Methods All participants underwent a clinical evaluation including comprehensive sleep history, polysomnography, cognitive assessment and blood chemistry examination. A data mining approach with fourth-generation artiﬁcial neural networks has been used in order to discover subtle trends and associations among variables. Results Polysomnography showed abnormality in 17 out of 23 recruited subjects (73.9%). In particular, 8/17 children (47%) had ineffective sleep, 10/17 (58.8%) fragmented sleep, 8/17 (47.1%) periodic limb movement disorder (PLMD) and 11/17 (64.7%) REM-sleep without atonia (RSWA). Most subjects presented more than one sleep disturbances. Notably, among the 19/23 patients diagnosed with Tic/Tourette disorder, 8/19 (42.1%) show PLMD and 10/19 (52.6%) RSWA. Artificial neural network methodology and the auto-contractive map exploited the links among the full spectrum of variables revealing the simultaneous connections among them, facing the complexity of PANS phenotype. Conclusion Disordered sleep represents, for prevalence and impact on quality of life, a cardinal symptom in patients with PANS. Thus, considering the weight of sleep disturbances on diagnosis and prognosis of PANS, we could consider the possibility of including them among the major diagnostic criteria.

show abstract

Section: Discussionsupporting

confidence: 53%

Section: Methodsmentioning

confidence: 99%

Artificial Neural Networks Analysis of polysomnographic and clinical features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): from sleep alteration to “Brain Fog”

Gagliano¹,

Puligheddu²,

Ronzano³

et al. 2021

NSS

View full text Add to dashboard Cite

show abstract

“…The Study Quality Assessment Tools of the National Institutes of Health (NIH) [ 24 ] applicable to several study designs were used for scoring study quality [ 25 , 26 ].…”

Section: Methodsmentioning

confidence: 99%

Literature Cases Summarized Based on Their Polysomnographic Findings in Rett Syndrome

Zhang

Spruyt

2022

IJERPH

Self Cite

View full text Add to dashboard Cite

Rett syndrome (RTT) is a severe and rare neurodevelopmental disorder affecting mostly girls. In RTT, an impaired sleep pattern is a supportive criterion for the diagnosis, yet little is known regarding the sleep structure and sleep respiratory events. Aiming to delineate sleep by aggregating RTT case (series) data from published polysomnographic studies, seventy-four RTT cases were collected from eleven studies up until 6 February 2022 (PROSPERO: CRD 42020198099). We compared the polysomnographic data within RTT stratifications and to a typically developing population. MECP2 cases demonstrated shortened total sleep time (TST) with increased stage N3 and decreased REM sleep. In cases with CDKL5 mutations, TST was longer and they spent more time in stage N1 but less in stage N3 than those cases affected by MECP2 mutations and a typically developing population. Sleep-disordered breathing was confirmed by the abnormal apnea/hypopnea index of 11.92 ± 23.67/h TST in these aggregated cases. No association of sleep structure with chronological age was found. In RTT, the sleep macrostructure of MECP2 versus CDKL5 cases showed differences, particularly regarding sleep stage N3. A severe REM sleep propensity reduction was found. Aberrant sleep cycling, possibly characterized by a poor REM ‘on switch’ and preponderance in slow and high-voltage sleep, is proposed.

show abstract

“…To consider the regenerative aspect of sleep, recordings were divided into restful and restless phases (for details see the Materials and Methods section). Whereas restful sleep corresponds to untroubled sleep, restless sleep has little restorative potential, and is often related to sleep disorders [21]. Thus, relative differences between phases of restful and restless sleep may provide relevant information in the context of this study.…”

Section: Introductionmentioning

confidence: 99%

“…Young children's sleep may be affected by various factors, such as inefficient bedtime routines [20], family background [18], health status [21], and perhaps digital media use [16][17][18][19]. Sleep is crucial for infants and toddlers, as it is vital for many developmental processes (for an overview see [22]).…”

Section: Introductionmentioning

confidence: 99%

Effects of Touchscreen Media Use on Toddlers’ Sleep: Insights from Longtime ECG Monitoring

Hackl-Wimmer

Eglmaier

Eichen

et al. 2021

Sensors

View full text Add to dashboard Cite

Wearable biomedical sensor technology enables reliable monitoring of physiological data, even in very young children. The purpose of the present study was to develop algorithms for gaining valid physiological indicators of sleep quality in toddlers, using data from an undisturbing and easy-to-use wearable device. The study further reports the application of this technique to the investigation of potential impacts of early touchscreen media use. Toddlers’ touchscreen media use is of strong interest for parents, educators, and researchers. Mostly, negative effects of media use are assumed, among them, disturbances of sleep and impairments of learning and development. In 55 toddlers (32 girls, 23 boys; 27.4 ± 4.9 months; range: 16–37 months), ECG monitoring was conducted for a period of 30 (±3) h. Parents were asked about their children’s touchscreen media use and they rated their children’s sleep quality. The use of touchscreen media predicted the physiologically determined quality of sleep but not parent-reported sleep quality (such as sleep onset latency). Greater heart rate differences between restless sleep phases and restful sleep indicated poorer nighttime recovery in children with more frequent use of touchscreen media. The study demonstrates that the expert analysis of the ECG during sleep is a potent tool for the estimation of sleep quality in toddlers.

show abstract

Restless sleep in children: A systematic review

Cited by 50 publications

References 90 publications

Artificial Neural Networks Analysis of polysomnographic and clinical features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): from sleep alteration to “Brain Fog”

Artificial Neural Networks Analysis of polysomnographic and clinical features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): from sleep alteration to “Brain Fog”

Literature Cases Summarized Based on Their Polysomnographic Findings in Rett Syndrome

Effects of Touchscreen Media Use on Toddlers’ Sleep: Insights from Longtime ECG Monitoring

Contact Info

Product

Resources

About