Current Search: Lima, Clelia (x)
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Title
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IDENTIFYING PATIENTS AT RISK FOR OBSTRUCTIVE SLEEP APNEA IN PRIMARY HEALTH CARE: CAN OBESITY IN COMBINATION WITH OTHER HIGH-RISK DIAGNOSES BE USED FOR SCREENING PURPOSES?.
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Creator
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Lima, Clelia, Norris, Anne, University of Central Florida
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Abstract / Description
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Obstructive sleep apnea (OSA) affects about 15 million adults in the United States, and is an independent risk factor for all-cause mortality. The under-diagnosing of OSA has been linked to the inadequate screening by primary care practitioners (PCPs). Existing screening tools are not widely used by PCPs possibly due to time constraints they experience as providers. This study demonstrates how common high-risk diagnoses (obesity, hypertension, diabetes mellitus type 2, dyslipidemia,...
Show moreObstructive sleep apnea (OSA) affects about 15 million adults in the United States, and is an independent risk factor for all-cause mortality. The under-diagnosing of OSA has been linked to the inadequate screening by primary care practitioners (PCPs). Existing screening tools are not widely used by PCPs possibly due to time constraints they experience as providers. This study demonstrates how common high-risk diagnoses (obesity, hypertension, diabetes mellitus type 2, dyslipidemia, arrhythmia, and coronary artery disease) can be used to help PCPs identify adult patients at risk for OSA. Unlike other screening tools, these diagnoses are easy to identify in a routine visit. This study was a retrospective chart review that used a random sample of 220 electronic health records. Seventy percent of the sample was positive for OSA, 69% had obesity, and 33% had two or more high-risk diagnoses. The setting of this study was six sleep centers located in five cities in Central Florida. Logistic regression was used to analyze the data to determine interaction among variables and odds ratios. The variables "obesity" and "two or more high-risk diagnoses" had significant effects on the likelihood of being diagnosed with OSA independently of each other (odds ratio of 4.2 and 4.3 respectively; p<.001). However, there was no significant interaction between these two variables (p=.56). The predictive value for an OSA diagnosis using "obesity" was 83%, and it was 88% using "two or more high-risk diagnoses." These findings argue for the use of high-risk diagnoses to identify patients at risk for OSA. PCPs are in an ideal position to increase the number of patients screened and treated for OSA because they routinely see patients with these diagnoses in their practices. Proper diagnosis and treatment of OSA has the potential to improve patients' outcomes and their quality of life.
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Date Issued
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2011
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Identifier
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CFE0003620, ucf:48863
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0003620
