Use of electronic data and existing screening tools to identify clinically significant obstructive sleep apnea

  • Severson C
  • Pendharkar S
  • Ronksley P
 et al. 
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Abstract

OBJECTIVES: To assess the ability of electronic health data and existing screening tools to identify clinically significant obstructive sleep apnea (OSA), as defined by symptomatic or severe OSA. METHODS: The present retrospective cohort study of 1041 patients referred for sleep diagnostic testing was undertaken at a tertiary sleep centre in Calgary, Alberta. A diagnosis of clinically significant OSA or an alternative sleep diagnosis was assigned to each patient through blinded independent chart review by two sleep physicians. Predictive variables were identified from online questionnaire data, and diagnostic algorithms were developed. The performance of electronically derived algorithms for identifying patients with clinically significant OSA was determined. Diagnostic performance of these algorithms was compared with versions of the STOP-Bang questionnaire and adjusted neck circumference score (ANC) derived from electronic data. RESULTS: Electronic questionnaire data were highly sensitive (>95%) at identifying clinically significant OSA, but not specific. Sleep diagnostic testing-determined respiratory disturbance index was very specific (specificity >/=95%) for clinically relevant disease, but not sensitive (

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Authors

  • C A Severson

  • S R Pendharkar

  • P E Ronksley

  • W H Tsai

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