Who should have a sleep study for sleep related breathing disorders?

Whiteford, L; Fleming, Peter; Henderson, A. John

doi:10.1136/adc.2003.036178

Cited by 19 publications

(21 citation statements)

References 54 publications

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“…This is not surprising, given that the underlying cause of GF is nearly always attributed to under-nutrition, despite multiple biologically plausible pathways from SDB to GF. For over 20 years, there has been an as yet unheeded call for assessment of SDB in children with growth problems [4,[19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Growth failure and sleep disordered breathing: A review of the literature

Bonuck

Parikh

Bassila

2006

International Journal of Pediatric Otorhinolaryngology

127

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Section: Introductionmentioning

confidence: 99%

Growth failure and sleep disordered breathing: A review of the literature

Bonuck

Parikh

Bassila

2006

International Journal of Pediatric Otorhinolaryngology

127

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“…Paediatric sleep research has explored in‐depth the negative consequences associated with SDB. SDB has been associated with failure to thrive, neurocognitive impairment, learning difficulties, behavioural problems, hyperactivity, decreased school performance and enuresis (Messner & Pelayo 2000, Chervin & Archbold 2001, Gozal & Pope 2001, Whiteford et al. 2004, Gozal et al.…”

Section: Overview Of Sleep Disordered Breathingmentioning

confidence: 99%

“…Sleepiness also has been linked to several neurobehavioural outcomes related to its effect on the prefrontal cortex, such as labile mood, impulsivity, impaired attention and concentration, difficulty converting short‐term memories into long‐term memories and difficulty generating complex and creative thought processes (Kotagal & Pianosi 2006). Physical manifestations of SDB include certain sleep positions, mouth breathing, snoring, adenoid hypertrophy and craniofacial abnormalities including retrognathia, maxillary hypoplasia and macroglossia (Messner & Pelayo 2000, Gozal & Pope 2001, Bao & Guilleminault 2004, Whiteford et al. 2004, Gozal et al.…”

Section: Overview Of Sleep Disordered Breathingmentioning

confidence: 99%

“…Nurses in the primary care setting and primary care providers such as nurse practitioners (NPs) must be equipped to assess children’s risk for SDB, to offer anticipatory guidance to parents regarding sleep and to identify and manage SRBD in their patients. Unfortunately, a lack of familiarity with SRBD among clinicians has resulted in inadequate identification of paediatric patients in need of sleep management (Owens 2001, Whiteford et al. 2004).…”

Section: Overview Of Sleep Disordered Breathingmentioning

confidence: 99%

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Review of upper airway resistance syndrome: nursing and clinical management

Giblin

2009

Journal of Clinical Nursing

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Timely recognition of sleep-disordered breathing is crucial to ensuring that patients receive effective and appropriate treatment. Upper airway resistance syndrome should be a part of the differential diagnosis when assessing a child with a sleep-related breathing disorder. RELEVANCE TO CLINICIAN PRACTICE: Nurses and nurse practitioners should become comfortable and skilled in performing a thorough sleep history and physical examination to help identify when a child should receive a sleep study or referral to a specialist.

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“…Overnight polysomnography (PSG) in a sleep laboratory is considered to be the definitive diagnostic exam for suspected abnormal breathing in children 1 . Polysomnography is the simultaneous recording of a number of physiological variables of a patient over a nights sleep.…”

Section: Motivationmentioning

confidence: 99%

Automated sleep scoring and sleep apnea detection in children

et al. 2005

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This paper investigates the automated detection of a patient's breathing rate and heart rate from their skin conductivity as well as sleep stage scoring and breathing event detection from their EEG. The software developed for these tasks is tested on data sets obtained from the sleep disorders unit at the Adelaide Women's and Children's Hospital. The sleep scoring and breathing event detection tasks used neural networks to achieve signal classification. The Fourier transform and the Higuchi fractal dimension were used to extract features for input to the neural network. The filtered skin conductivity appeared visually to bear a similarity to the breathing and heart rate signal, but a more detailed evaluation showed the relation was not consistent. Sleep stage classification was achieved with and accuracy of around 65% with some stages being accurately scored and others poorly scored. The two breathing events hypopnea and apnea were scored with varying degrees of accuracy with the highest scores being around 75% and 30%.

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Who should have a sleep study for sleep related breathing disorders?

Cited by 19 publications

References 54 publications

Growth failure and sleep disordered breathing: A review of the literature

Growth failure and sleep disordered breathing: A review of the literature

Review of upper airway resistance syndrome: nursing and clinical management

Automated sleep scoring and sleep apnea detection in children

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