BACKGROUND: Chronic rhinosinusitis (CRS) is a common disease diagnosed based on a combination of symptoms, imaging, and/or endoscopy. Computed tomography (CT) is the gold standard in diagnosis of CRS due to inherent low sensitivity of endoscopy. We sought to assess the correlation between symptoms, endoscopy, and imaging in order to reduce the number of CTs without decreasing diagnostic accuracy. METHODS: Retrospective review of a single practitioner's patients from 2008 to 2010 who presented for evaluation of CRS. Data on demographics, symptoms, and endoscopic and CT findings were collected and analyzed. Exclusion criteria included patients with prior surgery, no imaging, and those that failed to meet the 2007 CRS Task Force symptom criteria. RESULTS: A total of 244 patients met the Task Force symptom criteria. Using CT as the gold standard, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of endoscopy alone was 36%, 95%, 89%, and 55%, respectively. The number of symptoms (NOS) strongly correlated with the absence or presence of disease (p < 0.01). Incorporating NOS into a CRS diagnostic algorithm improved sensitivity and NPV of nasal endoscopy to 82% and 79% while maintaining its specificity and PPV at 82% and 84%, respectively. Applying our algorithm retrospectively would have resulted in a reduction in the number of CTs by 69%, resulting in an acceptable 10% (n = 24/244) false negative rate and 8% (n = 20/244) false positive rate. CONCLUSION: Incorporating number of symptoms in a CRS diagnostic algorithm may drastically reduce the number of CTs needed. Clinical diagnostic accuracy is enhanced with this new algorithm while significantly reducing the cost and radiation burden of CTs.
BACKGROUND:Chronic rhinosinusitis (CRS) is a common disease diagnosed based on a combination of symptoms, imaging, and/or endoscopy. Computed tomography (CT) is the gold standard in diagnosis of CRS due to inherent low sensitivity of endoscopy. We sought to assess the correlation between symptoms, endoscopy, and imaging in order to reduce the number of CTs without decreasing diagnostic accuracy. METHODS: Retrospective review of a single practitioner's patients from 2008 to 2010 who presented for evaluation of CRS. Data on demographics, symptoms, and endoscopic and CT findings were collected and analyzed. Exclusion criteria included patients with prior surgery, no imaging, and those that failed to meet the 2007 CRS Task Force symptom criteria. RESULTS: A total of 244 patients met the Task Force symptom criteria. Using CT as the gold standard, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of endoscopy alone was 36%, 95%, 89%, and 55%, respectively. The number of symptoms (NOS) strongly correlated with the absence or presence of disease (p < 0.01). Incorporating NOS into a CRS diagnostic algorithm improved sensitivity and NPV of nasal endoscopy to 82% and 79% while maintaining its specificity and PPV at 82% and 84%, respectively. Applying our algorithm retrospectively would have resulted in a reduction in the number of CTs by 69%, resulting in an acceptable 10% (n = 24/244) false negative rate and 8% (n = 20/244) false positive rate. CONCLUSION: Incorporating number of symptoms in a CRS diagnostic algorithm may drastically reduce the number of CTs needed. Clinical diagnostic accuracy is enhanced with this new algorithm while significantly reducing the cost and radiation burden of CTs.
Authors: Opeyemi O Daramola; Alcina K Lidder; Ramiza Ramli; Rakesh K Chandra; Stephanie Shintani-Smith; David B Conley; Robert C Kern; Bruce K Tan Journal: Laryngoscope Date: 2014-10-24 Impact factor: 3.325
Authors: Marek L Kowalski; Ignacio Ansotegui; Werner Aberer; Mona Al-Ahmad; Mubeccel Akdis; Barbara K Ballmer-Weber; Kirsten Beyer; Miguel Blanca; Simon Brown; Chaweewan Bunnag; Arnaldo Capriles Hulett; Mariana Castells; Hiok Hee Chng; Frederic De Blay; Motohiro Ebisawa; Stanley Fineman; David B K Golden; Tari Haahtela; Michael Kaliner; Connie Katelaris; Bee Wah Lee; Joanna Makowska; Ulrich Muller; Joaquim Mullol; John Oppenheimer; Hae-Sim Park; James Parkerson; Giovanni Passalacqua; Ruby Pawankar; Harald Renz; Franziska Rueff; Mario Sanchez-Borges; Joaquin Sastre; Glenis Scadding; Scott Sicherer; Pongsakorn Tantilipikorn; James Tracy; Vera van Kempen; Barbara Bohle; G Walter Canonica; Luis Caraballo; Maximiliano Gomez; Komei Ito; Erika Jensen-Jarolim; Mark Larche; Giovanni Melioli; Lars K Poulsen; Rudolf Valenta; Torsten Zuberbier Journal: World Allergy Organ J Date: 2016-10-12 Impact factor: 4.084