Add BrightSurf on Google Email

Predictive model accurately diagnoses sinusitis

07.10.17 | American Academy of Family Physicians
Apple iPhone 17 Pro

Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.

A new series of clinical decision rules integrating signs, symptoms, and C-reactive protein diagnose acute rhinosinusitis and acute bacterial rhinosinusitis with good accuracy. Researchers developed a point score and algorithm for each of 3 reference standards: abnormal CT scan, abnormal antral puncture, or positive bacterial culture. They conclude that the most appropriate reference standard is positive bacterial culture of antral puncture fluid. The point score using this reference standard successfully identified groups with a low (16 percent), moderate (49 percent) and high (73 percent) likelihood of acute bacterial rhinosinusitis. By identifying patients at low risk for a bacterial infection, this clinical decision rule can lead to more conservative use of antibiotics and help reduce inappropriate antibiotic prescribing. According to the authors, prospective validation of the findings and an assessment of their effect on clinical and process outcomes are important next steps.

###

Proposed Clinical Decision Rules to Diagnose Acute Rhinosinusitis Among Adults in Primary Care
Mark H. Ebell, MD, MS, University of Georgia
Jens Georg Hansen, MD, DMSc, Aarhus University Hospital, Denmark

The Annals of Family Medicine

Keywords

Article Information

Contact Information

Janelle Davis
jdavis@aafp.org

How to Cite This Article

APA:
American Academy of Family Physicians. (2017, July 10). Predictive model accurately diagnoses sinusitis. Brightsurf News. https://www.brightsurf.com/news/LM2W5P5L/predictive-model-accurately-diagnoses-sinusitis.html
MLA:
"Predictive model accurately diagnoses sinusitis." Brightsurf News, Jul. 10 2017, https://www.brightsurf.com/news/LM2W5P5L/predictive-model-accurately-diagnoses-sinusitis.html.