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    MP01-02 A NOMOGRAM FOR PREDICTING URETERAL STONE PASSAGE
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    You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation I1 Apr 2017MP01-02 A NOMOGRAM FOR PREDICTING URETERAL STONE PASSAGE Vishnu Ganesan, Michael Kattan, Christopher Loftus, Bryan Hinck, Daniel Greene, Yaw Nyame, Sri Sivalingam, and Manoj Monga Vishnu GanesanVishnu Ganesan More articles by this author , Michael KattanMichael Kattan More articles by this author , Christopher LoftusChristopher Loftus More articles by this author , Bryan HinckBryan Hinck More articles by this author , Daniel GreeneDaniel Greene More articles by this author , Yaw NyameYaw Nyame More articles by this author , Sri SivalingamSri Sivalingam More articles by this author , and Manoj MongaManoj Monga More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.077AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Medical expulsive therapy (MET) is frequently used for patients with ureteral stones who present to the emergency department (ED). Our goal was to develop and validate a nomogram to predict the probability stone passage on MET for ureteral stones. METHODS We reviewed ED visits within our health system with an ICD-9 diagnosis of urolithiasis, an associated CT scan, and discharged on MET between 2010-2013. CT's were reviewed to confirm stone size, location, and associated hydronephrosis. The primary outcome was spontaneous stone passage within 90-days of initial ED visit. Patients with no documented follow up in our system were called to collect data on stone passage. A nomogram was developed using variables chosen for clinical and statistical significance and validated internally using a bootstrapping technique. RESULTS 1,424 ED visits met the inclusion criteria and of these, 1,146 (80.4%) had confirmed ureteral stones on CT. Patients lost to follow up and who were unreachable by phone were excluded, leaving 661 patients to build the final model. The median age was 50 years (IQR 38-59) with 419 (63.4%) males and a median stone size of 4.0 mm (IQR 3.0-5.2). A majority of patients, 422 (64%), spontaneously passed their stone while the remaining underwent a procedure. On univariable analysis, patients who passed stones tended to have smaller stones (3.6 mm vs 5.2 mm, p < 0.001), stones in the distal ureter (73% vs. 41%, p < 0.001), and significantly higher WBC counts (9.49 vs. 8.57, p < 0.001). There were no associations between age (49 vs. 50, p = 0.831) or gender (64% male vs. 62% male, p = 0.451) on stone passage. In the multivariable model, stone size (per 1 mm increase; OR 0.49, 95% CI 0.43-0.57, p < 0.001), stone location (p < 0.0001), a prior history of stone passage (OR 1.74, 95% CI 1.04 - 2.93, p = 0.036), and WBC count (per 1k/uL increase, OR 1.12, 95% CI 1.04-1.21, p = 0.001) were significantly associated with spontaneous stone passage. The model was validated internally (bootstrap-adjusted concordance index, 0.80) and demonstrated excellent calibration. CONCLUSIONS For patients presenting with ureteral stones in the ED amenable to observation, we have developed a model to predict the probability of stone passage. Early follow-up or intervention for patients with a low probability of stone passage could improve patient satisfaction and prevent costly ED returns. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e1 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Vishnu Ganesan More articles by this author Michael Kattan More articles by this author Christopher Loftus More articles by this author Bryan Hinck More articles by this author Daniel Greene More articles by this author Yaw Nyame More articles by this author Sri Sivalingam More articles by this author Manoj Monga More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
    Keywords:
    Nomogram
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