Diagnostic accuracy of a two-stage model for detecting obstructive sleep apnoea in chronic tetraplegia Academic Article uri icon


  • BACKGROUND:Obstructive sleep apnoea (OSA) is highly prevalent in people with spinal cord injury (SCI). Polysomnography (PSG) is the gold-standard diagnostic test for OSA, however PSG is expensive and frequently inaccessible, especially in SCI. A two-stage model, incorporating a questionnaire followed by oximetry, has been found to accurately detect moderate to severe OSA (MS-OSA) in a non-disabled primary care population. This study investigated the accuracy of the two-stage model in chronic tetraplegia using both the original model and a modified version for tetraplegia. METHODS:An existing data set of 78 people with tetraplegia was used to modify the original two-stage model. Multivariable analysis identified significant risk factors for inclusion in a new tetraplegia-specific questionnaire. Receiver operating characteristic (ROC) curve analyses of the questionnaires and oximetry established thresholds for diagnosing MS-OSA. The accuracy of both models in diagnosing MS-OSA was prospectively evaluated in 100 participants with chronic tetraplegia across four international SCI units. RESULTS:Injury completeness, sleepiness, self-reported snoring and apnoeas were included in the modified questionnaire, which was highly predictive of MS-OSA (ROC area under the curve 0.87 (95% CI 0.79 to 0.95)). The 3% oxygen desaturation index was also highly predictive (0.93 (0.87-0.98)). The two-stage model with modified questionnaire had a sensitivity and specificity of 83% (66-93) and 88% (75-94) in the development group, and 77% (65-87) and 81% (68-90) in the validation group. Similar results were demonstrated with the original model. CONCLUSION:Implementation of this simple alternative to full PSG could substantially increase the detection of OSA in patients with tetraplegia and improve access to treatments. TRIAL REGISTRATION NUMBER:Results, ACTRN12615000896572 (The Australian and New Zealand Clinical Trials Registry) and pre-results, NCT02176928 (clinicaltrials.gov).


  • Graco, Marnie
  • Schembri, Rachel
  • Cross, Susan
  • Thiyagarajan, Chinnaya
  • Shafazand, Shirin
  • Ayas, Najib T
  • Nash, Mark S
  • Vu, Viet H
  • Ruehland, Warren R
  • Chai-Coetzer, Ching Li
  • Rochford, Peter
  • Churchward, Thomas
  • Green, Sally E
  • Berlowitz, David J

publication date

  • 2018

published in