TY - CHAP T1 - Diagnosis of uncomplicated cystitis (UC) T2 - Urogenital Infections and Inflammations AU - Schmiemann, Guido AU - Gebhardt, Klaus ED - Naber, Kurt G. AD - PD Dr. med Guido Schmiemann MPH, Institut für Public Health und Pflegeforschung, Universität Bremen, Abteilung Versorgungsforschung, Bremen, Deutschland, E-mail: schmiema@uni-bremen.de N2 - Urinary tract infections are among the most common bacterial infections and are responsible for 25% of antibiotic prescriptions in primary care. This chapter presents current evidence from a systematic literature search with a focus on systematic reviews and recent guidelines on diagnosing uncomplicated cystitis (UC). Starting with a general approach on the diagnostic process in suspected UC the pros and cons of different diagnostic strategies are discussed. Due to the high prevalence of UC the value of typical risk factors (like sexual intercourse) in increasing the pre-test probability is limited. In contrast the clinical presentation and the presence of typical symptoms are a cornerstone in diagnosing UC and differentiating it from complicated infections needing another diagnostic approach. The impact of typical symptoms like dysuria, frequency and hematuria based on their ability to increase the post-test probability are presented. In recent years diagnostic algorithms have been developed to increase the diagnostic accuracy of patients' history alone or in combination with point of care tests. According to a diagnostic study the combination of three questions "Does the patient think she has a UTI?" "Is there at least considerable pain on micturition?" and "Is there vaginal irritation?" has the highest accuracy. When followed by dipstick testing (nitrite and blood) accuracy can be increased further. Other point of care tests including dipslide and microscopy are discussed as well. The ongoing debate about the most appropriate technique to obtain a urine sample is discussed based on a recent systematic review and a clinical trial. Management strategies using telephone-based algorithms or based on patients self-diagnosis have proven their clinical effectiveness. Nevertheless, their study design allows only limited conclusions regarding the diagnostic accuracy.   PY - 2017 DA - 2017/11/22 DO - 10.5680/lhuii000004 LA - en L1 - https://books.publisso.de/de/system/getFile/136 UR - https://dx.doi.org/10.5680/lhuii000004 L2 - https://dx.doi.org/10.5680/lhuii000004 PB - German Medical Science GMS Publishing House CY - Duesseldorf ER -