A new statistical approach to predict bacteremia using electronic medical records

Scandinavian Journal of Infectious Diseases

Volumn 45, Issue 9, 2013, Pages 672-680

  Jin, Sung Joon ^a   Kim, Mingoo ^a   Yoon, Ji Hyun ^a   Song, Young Goo ^a  

^a Yonsei University College of Medicine   (South Korea)

Author keywords

Bacteremia; Bayesian prediction; Clinical prediction rule; Electronic medical records

Indexed keywords

ACCURACY; ADULT; ARTICLE; BACTEREMIA; BAYES THEOREM; COHORT ANALYSIS; COMPARATIVE STUDY; ELECTRONIC MEDICAL RECORD; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MALE; MORTALITY; PREDICTIVE VALUE; PREVALENCE; PROSPECTIVE STUDY; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY; RISK ASSESSMENT; VALIDATION PROCESS;

ADULT; AGED; BACTEREMIA; BAYES THEOREM; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, STATISTICAL; PROSPECTIVE STUDIES; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; RISK FACTORS; ROC CURVE;

EID: 84882368833     PISSN: 00365548     EISSN: 16511980     Source Type: Journal    
DOI: 10.3109/00365548.2013.799287     Document Type: Article

References (13)

1. Leibovici L, Greenshtain S, Cohen O, Mor F, Wysenbeek AJ. Bacteremia in febrile patients . Aclinical model for diagnosis. Arch Intern Med 1991; 151: 1801-6
2. Peduzzi P, Shatney C, Sheagren J, Sprung C . Predictors of bacteremia and Gram-negative bacteremia in patients with sepsis . The Veterans Affairs Systemic Sepsis Cooperative Study Group. Arch Intern Med 1992; 152: 529-35
3. Mozes B, Milatiner D, Block C, Blumstein Z, Halkin H. Inconsistency of a model aimed at predicting bacteremia in hospitalized patients . JClin Epidemiol 1993; 46: 1035-40 (Pubitemid 23258902)
4. Bates DW, Sands K, Miller E, Lanken PN, Hibberd PL, Graman PS, et al . Predicting bacteremia in patients with sepsis syndrome . Academic Medical Center Consortium Sepsis Project Working Group. J Infect Dis 1997; 176: 1538-51
5. Jaimes F, Arango C, Ruiz G, Cuervo J, Botero J, Velez G, et al . Predicting bacteremia at the bedside . Clin Infect Dis 2004; 38: 357-62 (Pubitemid 38200111)
6. Shapiro NI, Wolfe R E, Wright SB, Moore R, Bates DW . Who needs a blood culture? A prospectively derived and validated prediction rule. J Emerg Med 2008; 35: 255-64
7. Falguera M, Trujillano J, Caro S, Menendez R, Carratala J, Ruiz-Gonzalez A, et al . Aprediction rule for estimating the risk of bacteremia in patients with community-acquired pneumonia . Clin Infect Dis 2009; 49: 409-16
8. Allison JJ, Centor RM . Why models predicting bacteremia in general medical patients do not work . JGen Intern Med 1996; 11: 132-4
9. M ylotte J M, Pisano M A, Ram S, Nakasato S, Rotella D. Validation of a bacteremia prediction model . Infect Control Hosp Epidemiol 1995; 16: 203-9
10. Yehezkelli Y, Subah S, Elhanan G, Raz R, Porter A, Regev A, et al . Two rules for early prediction of bacteremia: Testing in a university and a community hospital . JGen Intern Med 1996; 11: 98-103 (Pubitemid 26088068)
11. Goodman SN . Toward evidence-based medical statistics. 2: The Bayes factor . Ann Intern Med 1999; 130: 1005-13 (Pubitemid 29283992)
12. Schurink C A, Lucas P J, Hoepelman I M, Bonten M J. Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units. Lancet Infect Dis 2005; 5: 305-12 (Pubitemid 40602250)
13. Paul M, Andreassen S, Nielsen AD, Tacconelli E, Almanasreh N, Fraser A, et al . Prediction of bacteremia using TREAT, acomputerized decision-support system . Clin Infect Dis 2006; 42: 1274-82