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Residual fraction as a parameter to predict bladder outlet obstruction in men with lower urinary tract symptoms
Author(s) -
Ku Ja Hyeon,
Cho Sung Yong,
Oh SeungJune
Publication year - 2009
Publication title -
international journal of urology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 67
eISSN - 1442-2042
pISSN - 0919-8172
DOI - 10.1111/j.1442-2042.2009.02354.x
Subject(s) - medicine , bladder outlet obstruction , confidence interval , odds ratio , urology , prostate , diagnostic odds ratio , multivariate analysis , nuclear medicine , cancer
Objectives: To determine whether noninvasive tests including the residual fraction are reliable for the diagnosis of bladder outlet obstruction (BOO). Methods: A total of 212 men (median age 68, range 44–89 years) were included in the present study. The median serum prostate‐specific antigen level and prostate volume were 1.3 ng/mL (range 0.2 to 9.4) and 37.9 mL (range 11.3 to 148.0), respectively. Results: Among the variables analyzed in the multivariate model, the likelihood of BOO varied by the total prostate volume, with a 3.6‐fold higher odds for ≥40 mL than for <40 mL (odds ratio [OR], 3.616; 95% confidence interval [CI], 1.217–10.749; P = 0.021). In the same model, a low maximal flow rate (Qmax) (OR, 2.840; 95% CI, 1.260–6.401; P = 0.012) and high residual fraction (OR, 7.103; 95% CI, 1.924–26.225; P = 0.003) were associated with an increased likelihood of BOO. The sensitivity and specificity for predicting BOO using a total prostate volume of 40 mL or greater were 73.7% and 65.2%, respectively. Using a Qmax cut‐off of 12 mL/s or less for predicting BOO, the sensitivity and specificity were 77.2% and 54.2%, respectively. Prediction of the BOO by the residual fraction only had a sensitivity and specificity, for a residual fraction of less than 20%, of 75.4% and 67.7%, respectively. Conclusions: The presence or absence of BOO might be predicted using non‐invasive methods. The residual fraction may help with patient management by better predicting the likely patient classification from pressure‐flow studies.