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Chamara V. Senaratna

Researcher at University of Sri Jayewardenepura

Publications -  18
Citations -  1704

Chamara V. Senaratna is an academic researcher from University of Sri Jayewardenepura. The author has contributed to research in topics: Population & Sleep apnea. The author has an hindex of 8, co-authored 13 publications receiving 1016 citations. Previous affiliations of Chamara V. Senaratna include University of Melbourne.

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Validity of the Berlin questionnaire in detecting obstructive sleep apnea: A systematic review and meta-analysis

TL;DR: It is concluded that the Berlin questionnaire is useful as a clinical screening test and epidemiological tool in the sleep clinic population and likely has potential clinical and research utility in other populations.
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Current evidence on prevalence and clinical outcomes of co-morbid obstructive sleep apnea and chronic obstructive pulmonary disease: A systematic review

TL;DR: The objective of this systematic review is to synthesize the evidence on prevalence, polysomnographic findings and clinical outcomes of co-morbid obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) - known as the "overlap syndrome", and highlight the limitations and knowledge gaps.
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Sleep apnoea in Australian men: disease burden, co-morbidities, and correlates from the Australian longitudinal study on male health.

TL;DR: Prevalence of self-reported health professional-diagnosed sleep apnoea is relatively common, particularly in older males, and as men are especially vulnerable to sleep apNoea as well as some of its chronic co-morbidities, they are potentially a priority group for health interventions.
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The effect of surgical weight loss on obstructive sleep apnoea: A systematic review and meta-analysis

TL;DR: Overall, surgical weight loss resulted in reduction of BMI and AHI, however, OSA persisted at follow-up in the majority of subjects, and there was high between-study heterogeneity which was largely attributable to baseline AHI and duration of follow- up when analysed using meta-regression.