@article{3083720, title = "Acute pyelonephritis in adults - Prediction of mortality and failure of treatment", author = "Efstathiou, SP and Pefanis, AV and Tsioulos, DI and Zacharos, ID and and Tsiakou, AG and Mitromaras, AG and Mastorantonakis, SE and Kanavaki, SN and and Mountokalakis, TD", journal = "Archives of Internal Medicine", year = "2003", volume = "163", number = "10", pages = "1206-1212", publisher = "AMER MEDICAL ASSOC", issn = "0003-9926, 1538-3679", doi = "10.1001/archinte.163.10.1206", abstract = "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." }