Long-term survival in patients included in a randomized controlled trial of TREAT, a decision support system for antibiotic treatment.

OBJECTIVES: TREAT is a computerized decision support system for antibiotic treatment. In a randomized controlled trial it improved significantly the percentage of appropriate empirical antibiotic treatment and shortened hospital stay, while the usage of broad-spectrum antibiotics was reduced. The trial was not powered to show significance for the difference in 1 month mortality rate. In the present analysis we looked at 6 month survival in one of the hospitals (Beilinson Hospital) that participated in the trial. METHODS: We plotted the Kaplan-Meier survival function for all patients [intention to treat (ITT)] and for patients treated according to the TREAT advice [per protocol (PP)]. The analysis was repeated for patients with clinically or bacteriologically documented bacterial infections. RESULTS: At Beilinson Hospital 1683 patients were included in the study, 860 in the intervention arm and 823 in the control arm. In the ITT analysis 180 day survival in control patients was 71% versus 74% in the intervention patients (P = 0.2). In the PP analysis the survival percentages were 71% and 77%, respectively (P = 0.04). In patients with bacterial infections, in the ITT analysis 180 day survival in the control group was 68% versus 71% in the intervention patients (P = 0.1). In the PP analysis the survival percentages were 68% versus 74% (P = 0.04). CONCLUSIONS: The present data support an effect of the TREAT decision support system on 6 month survival, mainly because of its benefit in patients with documented bacterial infections.

A model for diagnosis of pulmonary infections in solid-organ transplant recipients.

BACKGROUND: Opportunistic pulmonary infections are a major cause of morbidity and mortality among solid organ transplant recipients. The diagnosis of these infections is challenging because of the broad spectrum of bacteria, fungi and viruses affecting these patients and the lack of specific signs and symptoms. Treatment directed at the offending organism started as soon as possible improves survival. OBJECTIVE: To develop a decision support system for the diagnosis of pulmonary infections in solid-organ transplant recipients. The model's goal is to improve the accuracy of the diagnosis and thus the appropriateness of empirical treatment. DESIGN: The model is built using a Bayesian network (also known as causal probabilistic network). The network is based on pathogen segments which are the main building blocks of the model. Segments share common risk factors, such as time after transplantation, latent infections of donor/recipient and organ transplanted. The segments are linked at symptoms, signs and diagnostic tests common to all pathogens. The outputs of the model are predicted probabilities of infectious pathogens. To populate the model with data we have mainly abstracted data from the literature, using a systematic approach. The structure of the model and its adaptation for decision support will be presented. EVALUATION: The first evaluation phase assessed the model's diagnosis in a series of 20 representative cases of opportunistic infections. A match between the case's diagnosis and the model's prediction was achieved in 17/20 of cases. The next evaluation phase will consist of a prospective observational study comparing the accuracy of the model's diagnosis vs. that of the physician within 24h of episode onset, as compared with a gold-standard diagnosis ascribed to the patients at the end of the infectious episode by two independent experts. Data for this phase are currently collected prospectively.

Importance of appropriate empirical antibiotic therapy for methicillin-resistant Staphylococcus aureus bacteraemia.

OBJECTIVES: To document the effects of appropriate and inappropriate empirical antibiotic therapy on mortality in a cohort of patients with bacteraemia due to methicillin-resistant Staphylococcus aureus (MRSA) and to summarize effects with previous studies. METHODS: In the retrospective cohort study, episodes of clinically significant MRSA bacteraemia during a 15 year period were included. Polymicrobial episodes were excluded unless MRSA was isolated in more than one bottle and co-pathogens were given appropriate empirical antibiotic treatment. Appropriate empirical treatment was defined as matching in vitro susceptibility and started within 48 h of blood-culture taking, except for single aminoglycosides or rifampicin. We assessed univariate and multivariate associations between appropriate empirical therapy and 30 day all-cause mortality. Multivariable analysis was conducted using backward stepwise logistic regression. We reviewed all studies assessing the effects of appropriate empirical antibiotic treatment on mortality for MRSA infections and compiled adjusted odds ratios (ORs) using a random effects meta-analysis. RESULTS: Five hundred and ten episodes of MRSA bacteraemia were included. There were no cases of community-acquired infection. The 30 day mortality was 43.9% (224/510) and was stable throughout the study period. Mortality was significantly higher among patients receiving inappropriate (168/342, 49.1%) compared with those receiving appropriate (56/168, 33.3%) empirical antibiotic treatment, P = 0.001. In the adjusted analysis the OR was 2.15 [95% confidence interval (CI) 1.34-3.46]. Pooling of six studies using adequate methodology for the adjusted analysis resulted in an OR of 1.98 (95% CI 1.62-2.44). CONCLUSIONS: Appropriate empirical antibiotic treatment has a significant survival benefit in MRSA bacteraemia. Treatment guidelines should consider this benefit.

Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis.

Quantifying the benefit of early antibiotic treatment is crucial for decision making and can be assessed only in observational studies. We performed a systematic review of prospective studies reporting the effect of appropriate empirical antibiotic treatment on all-cause mortality among adult inpatients with sepsis. Two reviewers independently extracted data. Risk of bias was assessed using the Newcastle-Ottawa score. We calculated unadjusted odds ratios (ORs) with 95% confidence intervals for each study and extracted adjusted ORs, with variance, methods, and covariates being used for adjustment. ORs were pooled using random-effects meta-analysis. We examined the effects of methodological and clinical confounders on results through subgroup analysis or mixed-effect meta-regression. Seventy studies were included, of which 48 provided an adjusted OR for inappropriate empirical antibiotic treatment. Inappropriate empirical antibiotic treatment was associated with significantly higher mortality in the unadjusted and adjusted comparisons, with considerable heterogeneity occurring in both analyses (I(2) > 70%). Study design, time of mortality assessment, the reporting methods of the multivariable models, and the covariates used for adjustment were significantly associated with effect size. Septic shock was the only clinical variable significantly affecting results (it was associated with higher ORs). Studies adjusting for background conditions and sepsis severity reported a pooled adjusted OR of 1.60 (95% confidence interval = 1.37 to 1.86; 26 studies; number needed to treat to prevent one fatal outcome, 10 patients [95% confidence interval = 8 to 15]; I(2) = 46.3%) given 34% mortality with inappropriate empirical treatment. Appropriate empirical antibiotic treatment is associated with a significant reduction in all-cause mortality. However, the methods used in the observational studies significantly affect the effect size reported. Methods of observational studies assessing the effects of antibiotic treatment should be improved and standardized.

Antiviral prophylaxis in haematological patients: systematic review and meta-analysis.

PURPOSE: Antiviral prophylaxis is commonly prescribed to haematological cancer patients. We conducted a systematic review and meta-analysis to quantify its overall benefit in specific clinical scenarios. METHODS: Randomised controlled trials assessing antiviral prophylaxis versus placebo, no treatment, pre-emptive treatment or another antiviral drug were included. Patients undergoing haematopoietic stem cell transplantation (HSCT) or intensive chemotherapy for acute leukaemia or high-grade lymphoma were included. No restrictions on language, year or publication status were applied. Overall mortality, herpes simplex virus (HSV) and cytomegalovirus (CMV) diseases were assessed as primary outcomes. Pooled relative risks (RRs) and numbers needed to treat (NNT) with 95% confidence intervals (CI) are reported. RESULTS: HSCT was the condition assessed in 22 trials and intensive chemotherapy in 5 trials. In the pre-engraftment setting of autologous or allogeneic HSCT, antiviral prophylaxis (mainly acyclovir for HSV seropositive recipients) significantly reduced HSV (NNT 2, 2-2, control event rate (CER) 61.9%) and CMV disease, with no effect on overall mortality. In the allogeneic post-engraftment setting (mainly CMV-seropositive recipients/donors), antiviral prophylaxis resulted in a significant reduction in overall mortality, RR 0.79 (0.65-0.95), NNT 12 (7-50, CER 39.4%) and all viral-related outcomes. In this setting, acyclovir significantly reduced overall mortality (RR 0.71, 0.53-0.96, 4 trials) and ganciclovir/maribavir significantly reduced CMV disease (RR 0.26, 0.14-0.48, 5 trials). During chemotherapy, acyclovir significantly decreased HSV disease (NNT 3, 2-4, CER 37.4%) and infection rates, with no effect on mortality. CONCLUSIONS: Antiviral prophylaxis reduced mortality with a small NNT in the post-engraftment setting of allogeneic HSCT. In the pre-engraftment phase and during chemotherapy only viral-related morbidity was reduced.