0464 Prevalence Of Sleep-disordered Breathing After Stroke And Transitory Ischemic Attack: A Meta-analysis

Introduction To date, continuous positive airway pressure (CPAP) remains the cornerstone of obstructive sleep apnoea treatment. CPAP data describing residual sleep-disordered breathing events (ie, the CPAP-measured apnoea–hypopnoea indices (AHI-CPAPflow)) is difficult to interpret because it is an entirely different metric than the polysomnography (PSG) measured AHI gold standard (AHI-PSGgold). Moreover, manufacturer definitions for apnoea and hypopnoea are not only different from those recommended for PSG scoring, but also different between manufacturers. In the context of CPAP initiation and widespread telemedicine at home to facilitate sleep apnoea care, there is a need for concrete evidence that AHI-CPAPflow can be used as a surrogate for AHI-PSGgold. Methods and analysis No published systematic review and meta-analysis (SRMA) has compared the accuracy of AHI-CPAPflow against AHI-PSGgold and the primary objective of this study is therefore to do so using published data. The secondary objectives are to similarly evaluate other sleep disordered breathing indices and to perform subgroup analyses focusing on the inclusion/exclusion of central apnoea patients, body mass index levels, CPAP device brands, pressure titration modes, use of a predetermined and fixed pressure level or not, and the impact of a 4% PSG desaturation criteria versus 3% PSG on accuracy. The Preferred Reporting Items for SRMA protocols statement guided study design. Randomised controlled trials and observational studies of adult patients (≥18 years old) treated by a CPAP device will be included. The CPAP intervention and PSG comparator must be performed synchronously. PSGs must be scored manually and follow the American Academy of Sleep Medicine guidelines (2007 AASM criteria or more recent). To assess the risk of bias in each study, the Quality Assessment of Diagnostic Accuracy Studies 2 tool will be used. Ethics and dissemination This protocol received ethics committee approval on 16 July 2020 (IRB_MTP_2020_07_2020000404) and results will be disseminated via peer-reviewed publications. PROSPERO/Trial registration numbers CRD42020159914/NCT04526366; Pre-results

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Abstract P107: Are Sleep Disturbances Associated with the Development of Gestational Diabetes? A Systematic Review and Meta-analysis.

Circulation ◽

10.1161/circ.129.suppl_1.p107 ◽

2014 ◽

Vol 129 (suppl_1) ◽

Author(s):

Michelle A Miller ◽

Ponnusamy Saravanan ◽

Manu Vatish ◽

Francesco P Cappuccio

Keyword(s):

Gestational Diabetes ◽

Publication Bias ◽

Sleep Disturbances ◽

Sleep Disordered Breathing ◽

Meta Analysis ◽

Cochrane Library ◽

Short Sleep ◽

Increased Risk ◽

In Pregnancy ◽

Disordered Breathing

Introduction and objectives: Physiological and hormonal changes occurring in pregnancy increase the risk of sleep disordered breathing (SDB), which, along with short sleep (SS) duration, may be associated with an increased risk of gestational diabetes mellitus (GDM). Exposure to GDM in the mother increases her lifetime risk of type-2 diabetes (T2D) as well as the risk of obesity, metabolic syndrome and, in later life, T2D of her children. The aim of this study was to systematically review the collective published evidence of associations between snoring/sleep-disordered breathing or sleep duration and increased risk of GDM. Hypothesis: We assessed the hypotheses that sleep disturbances, and/or short sleep during pregnancy may be associated with an increased risk of GDM. Materials and Methods: We performed systematic searches using MEDLINE, EMBASE, the Cochrane library and PsycINFO to assess the effect of snoring/sleep disordered breathing (SDB) or short sleep (SS) on the development of gestational diabetes (GDM) and impaired glucose tolerance in pregnancy. Prospective studies with measures of sleep disturbances at baseline and outcome measures of GDM or levels of glucose 1hr post GCT were included in a meta-analysis. We extracted odds ratios (OR) or relative risks (RR) and 95% confidence intervals (CI) and pooled them using a random effect model. Results: Overall, 7 studies met the inclusion criteria. They included 4,292 participants with 311 cases of GDM. In the pooled analysis, snoring/SDB and SS were both associated with a greater risk of GDM (RR: 2·27; 95% CI 1·65 to 3·12; P < 0· 00001) and (3·19 [1·56 to 6·54]; P < 0·002), respectively. There was no evidence of heterogeneity but there was evidence of publication bias and not all studies adjusted for obesity. Sensitivity analyses did not influence the pooled risk estimates. Conclusions: In conclusion, sleep disturbances may represent a risk factor for the development of GDM. Further studies are required to address the issues of publication bias and potential confounding, and to extend these observations to high-risk groups like women of ethnic minority groups whose risk of GDM is the greatest. Prevention, detection and treatment strategies need to be explored.

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