Michael R Le Grande1, Alun C Jackson2, Alison Beauchamp3, Debra Kerr4, Andrea Driscoll5. 1. Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, VIC, 3051, Australia; Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia; Melbourne Centre for Behaviour Change, School of Psychological Sciences, The University of Melbourne, Parkville, VIC, 3052, Australia. Electronic address: mlegrande@deakin.edu.au. 2. Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, VIC, 3051, Australia; Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia; Centre on Behavioural Health, Hong Kong University, Pakfulam, Hong Kong. 3. Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, VIC, 3051, Australia; Department of Medicine - Western Health, The University of Melbourne, VIC, 3052, Australia; Australian Institute for Musculoskeletal Science (AIMSS), St. Albans, VIC, 3021, Australia; School of Rural Health, Monash University, Newborough, VIC, 3825, Australia. 4. Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia. 5. Faculty of Health, Deakin University, Burwood, VIC, 3216, Australia; Centre for Quality and Patient Safety Research, School of Nursing and Midwifery, Deakin University, Geelong, VIC, 3220, Australia.
Abstract
BACKGROUND: A number of clinical guidelines recommend that all cardiac rehabilitation patients should be screened for potential sleep disorders with a validated screening instrument. There is currently no consensus on what specific tools should be used. OBJECTIVE: To identify tools that are practical to use in the clinical environment and have high diagnostic accuracy. METHODS: We systematically searched online databases to identify patient reported outcome instruments that have been used in published research studies to assess the likelihood of obstructive sleep apnoea (OSA) in cardiac patients. In studies that provided diagnostic data, these data were extracted and verified via an evidence-based diagnostic calculator. Where sufficient numbers of studies were available, a meta-analysis was conducted to determine pooled estimates of specificity, sensitivity and diagnostic odds ratios. Selected papers were qualitatively assessed using the Standards for Reporting Diagnostic accuracy studies (STARD). RESULTS: Of the 21 instruments identified, six detected likelihood of OSA, two assessed daytime sleepiness, five assessed insomnia and eight examined sleep quality. A meta-analysis of 14 studies that assessed diagnostic accuracy of moderate OSA, revealed moderate sensitivity for the Berlin Questionnaire, Sens = 0.49 (95% CI 0.45-0.52) and good sensitivity for the Stop-BANG, Sens = 0.93 (95% CI 0.87-0.96) but poor specificity at standard cut-off criteria. CONCLUSION: There are promising practical tools available to screen patients with OSA and other sleep disorders in cardiac rehabilitation settings, but specificity could be improved. Additional assessment of sleep quality may enhance prognostic ability with both OSA and insomnia screening.
BACKGROUND: A number of clinical guidelines recommend that all cardiac rehabilitation patients should be screened for potential sleep disorders with a validated screening instrument. There is currently no consensus on what specific tools should be used. OBJECTIVE: To identify tools that are practical to use in the clinical environment and have high diagnostic accuracy. METHODS: We systematically searched online databases to identify patient reported outcome instruments that have been used in published research studies to assess the likelihood of obstructive sleep apnoea (OSA) in cardiac patients. In studies that provided diagnostic data, these data were extracted and verified via an evidence-based diagnostic calculator. Where sufficient numbers of studies were available, a meta-analysis was conducted to determine pooled estimates of specificity, sensitivity and diagnostic odds ratios. Selected papers were qualitatively assessed using the Standards for Reporting Diagnostic accuracy studies (STARD). RESULTS: Of the 21 instruments identified, six detected likelihood of OSA, two assessed daytime sleepiness, five assessed insomnia and eight examined sleep quality. A meta-analysis of 14 studies that assessed diagnostic accuracy of moderate OSA, revealed moderate sensitivity for the Berlin Questionnaire, Sens = 0.49 (95% CI 0.45-0.52) and good sensitivity for the Stop-BANG, Sens = 0.93 (95% CI 0.87-0.96) but poor specificity at standard cut-off criteria. CONCLUSION: There are promising practical tools available to screen patients with OSA and other sleep disorders in cardiac rehabilitation settings, but specificity could be improved. Additional assessment of sleep quality may enhance prognostic ability with both OSA and insomnia screening.