TY - JOUR
TI - Acute pyelonephritis in adults - Prediction of mortality and failure of
treatment
AU - Efstathiou, SP
AU - Pefanis, AV
AU - Tsioulos, DI
AU - Zacharos, ID and
AU - Tsiakou, AG
AU - Mitromaras, AG
AU - Mastorantonakis, SE
AU - Kanavaki, SN
AU - and Mountokalakis, TD
JO - Archives of Internal Medicine
PY - 2003
VL - 163
TODO - 10
SP - 1206-1212
PB - AMER MEDICAL ASSOC
SN - 0003-9926, 1538-3679
TODO - 10.1001/archinte.163.10.1206
TODO - null
TODO - Background: To formulate a classification tool for early recognition of
patients admitted with acute pyelonephritis (AP) who are at high risk
for failure of treatment or for death.
Methods: A retrospective chart review of 225 patients (102 men) admitted
with AP. We considered 13 potential risk factors in a multivariate
analysis.
Results: Recent hospitalization, previous use of antibiotics, and
immunosuppression were found to be independent correlates of the
prevalence of resistant pathogens in both sexes. Additional predictors
included nephrolithiasis in women and a history of recurrent AP in men.
Prolonged hospitalization should be expected for a man with diabetes and
long-term catheterization who is older than 65 years or for a woman of
any age with the same characteristics, when the initial treatment was
changed according to the results of urine culture. For mortality
prediction, we derived an integer-based scoring system with 6 points for
shock, 4 for bedridden status, 4 for age greater than 65 years, and 3
for previous antibiotic treatment for men and 6 points for shock, 4 for
bedridden status, 4 for age greater than 65 years, and 3 for
immunosuppression for women. Among patients with at least 11 points, the
risk for in-hospital death was 100% for men and 91% for women.
Conclusions: Simple variables available at presentation can be used for
risk stratification of patients with AP. The additional identification
of certain risk factors by means of a carefully obtained history could
contribute to early recognition of patients infected by resistant
bacteria and optimize the selection of antimicrobial agents.
ER -