Features that may predict hospital admission following outpatient therapeutic ERCP.
BACKGROUND
Some patients are admitted following outpatient therapeutic ERCP because of adverse events. This study aimed to identify factors that may predict such admissions.


METHODS
We prospectively studied admissions for post-ERCP adverse events in 415 consecutive patients undergoing outpatient therapeutic ERCP. Potentially relevant predictors of admission were assessed by univariate analysis and in case of significance included in a multivariate analysis.


RESULTS
Admission was necessary in 41 patients (9.9%) because of complications and in 63 (15.2%) for observation of adverse events that did not progress to definable complications. Potential predictors of admission were evaluated comparing patients who required more than an overnight admission (n = 63) with those who did not (n = 352). Multivariate analysis identified three factors that were significant: pain during the procedure (odds ratio 3.8: 95% CI [1.8, 7.9]), history of pancreatitis (odds ratio 2.3: 95% CI [1.1, 4.7]) and performance of sphincterotomy (odds ratio 2.2: 95% CI [1.1, 4.3]). The presence of all these features was associated with a 66.7% likelihood of admission, whereas the absence of pain during the procedure, history of pancreatitis and performance of sphincterotomy made admission likely in only 11.0%, 9.8% and 10.7%, respectively, of the cases.


CONCLUSIONS
The occurrence of pain during the procedure, a history of pancreatitis and the performance of sphincterotomy were independent predictors of admission following outpatient therapeutic ERCP.
Ho
K Y
KY
Division of Gastroenterology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Montes
H
H
Sossenheimer
M J
MJ
Tham
T C
TC
Ruymann
F
F
Van Dam
J
J
Carr-Locke
D L
DL
D000328:Adult; D000368:Aged; D002760:Cholangiopancreatography, Endoscopic Retrograde / Q000009:adverse effects* / Q000379:methods / Q000706:statistics & numerical data; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010343:Patient Admission / Q000706:statistics & numerical data*; D011379:Prognosis; D011446:Prospective Studies; D012307:Risk Factors; D018709:Statistics, Nonparametric; D014481:United States