title: A prediction tool for nosocomial multi-drug Resistant Gram-Negative Bacilli infections in critically ill patients - prospective observational study.
abstract: BACKGROUND
  The widespread use of empiric broad spectrum antibiotics has contributed to the global increase of Resistant Gram-Negative Bacilli (RGNB) infections in intensive care units (ICU). The aim of this study was to develop a tool to predict nosocomial RGNB infections among ICU patients for targeted therapy.
  
  
  METHODS
  We conducted a prospective observational study from August'07 to December'11. All adult patients who were admitted and stayed for more than 24 hours at the medical and surgical ICU's were included. All patients who developed nosocomial RGNB infections 48 hours after ICU admission were identified. A prediction score was formulated by using independent risk factors obtained from logistic regression analysis. This was prospectively validated with a subsequent cohort of patients admitted to the ICUs during the following time period of January-September 2012.
  
  
  RESULTS
  Seventy-six patients with nosocomial RGNB Infection (31bacteremia) were compared with 1398 patients with Systemic Inflammatory Response Syndrome (SIRS) without any gram negative bacterial infection/colonization admitted to the ICUs during the study period. The following independent risk factors were obtained by a multivariable logistic regression analysis - prior isolation of Gram negative organism (coeff: 1.1, 95% CI 0.5-1.7); Surgery during current admission (coeff: 0.69, 95% CI 0.2-1.2); prior Dialysis with end stage renal disease (coeff: 0.7, 95% CI 0.1-1.1); prior use of Carbapenems (coeff: 1.3, 95% CI 0.3-2.3) and Stay in the ICU for more than 5 days (coeff: 2.4, 95% CI 1.6-3.2). It was validated prospectively in a subsequent cohort (n = 408) and the area-under-the-curve (AUC) of the GSDCS score for predicting nosocomial ICU acquired RGNB infection and bacteremia was 0.77 (95% CI 0.68-0.89 and 0.78 (95% CI 0.69-0.89) respectively. The GSDCS (0-4.3) score clearly differentiated the low (0-1.3), medium (1.4-2.3) and high (2.4-4.3) risk patients, both for RGNB infection (p:0.003) and bacteremia (p:0.009).
  
  
  CONCLUSIONS
  GSDCS is a simple bedside clinical score which predicts RGNB infection and bacteremia with high predictive value and differentiates low versus high risk patients. This score will help clinicians to choose appropriate, timely targeted antibiotic therapy and avoid exposure to unnecessary treatment for patients at low risk of nosocomial RGNB infection. This will reduce the selection pressure and help to contain antibiotic resistance in ICUs.
authors.forename: Anupama
authors.initials: A
authors.lastname: Vasudevan
authors.forename: Amartya
authors.initials: A
authors.lastname: Mukhopadhyay
authors.forename: Jialiang
authors.initials: J
authors.lastname: Li
authors.forename: Eugene Goh Yu
authors.initials: EG
authors.lastname: Yuen
authors.forename: Paul Ananth
authors.initials: PA
authors.lastname: Tambyah
mesh_terms: D000151:Acinetobacter Infections / Q000453:epidemiology / Q000382:microbiology; D040981:Acinetobacter baumannii / Q000502:physiology; D000328:Adult; D000368:Aged; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D016470:Bacteremia / Q000453:epidemiology / Q000382:microbiology; D015780:Carbapenems / Q000627:therapeutic use; D015331:Cohort Studies; D016638:Critical Illness / Q000453:epidemiology*; D003428:Cross Infection / Q000453:epidemiology / Q000382:microbiology; D003661:Decision Support Techniques; D024901:Drug Resistance, Multiple, Bacterial / Q000502:physiology*; D004926:Escherichia coli / Q000502:physiology; D004927:Escherichia coli Infections / Q000453:epidemiology / Q000382:microbiology; D005260:Female; D006090:Gram-Negative Bacteria / Q000502:physiology*; D016905:Gram-Negative Bacterial Infections / Q000453:epidemiology* / Q000382:microbiology; D006801:Humans; D007362:Intensive Care Units; D007676:Kidney Failure, Chronic / Q000453:epidemiology / Q000628:therapy; D007710:Klebsiella Infections / Q000453:epidemiology / Q000382:microbiology; D007711:Klebsiella pneumoniae / Q000502:physiology; D007902:Length of Stay / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D018410:Pneumonia, Bacterial / Q000453:epidemiology / Q000382:microbiology; D011446:Prospective Studies; D011552:Pseudomonas Infections / Q000453:epidemiology / Q000382:microbiology; D011550:Pseudomonas aeruginosa / Q000502:physiology; D006435:Renal Dialysis / Q000706:statistics & numerical data*; D012307:Risk Factors; D013514:Surgical Procedures, Operative / Q000706:statistics & numerical data*; D018746:Systemic Inflammatory Response Syndrome / Q000453:epidemiology; D014552:Urinary Tract Infections / Q000453:epidemiology / Q000382:microbiology
chemical_list: D000900:Anti-Bacterial Agents; D015780:Carbapenems