Solid Organ Transplantation (SOT) and Data Mining: Bloodstream Infections (BSI) Have a Significant Impact on One-Year Survival, and qSOFA ≥ 2 Predicts 30-Day Mortality. (4th October 2017)

• Record Type: Journal Article
• Authors: Liu, Terrence; Xie, Donglu; Adams-Huet, Beverley; Le, Jade; Yek, Christina; Ranganathan, Dipti; Haley, Robert W; Greenberg, David; Hoz, Ricardo La
• Is Part Of: Open forum infectious diseases. Volume 4(2017)Supplement 1
• Page Start: S10
• Page End: S10
• Publication Date: 2017-10-04
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofx162.025
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: We created a retrospective and prospective database of SOT recipients using innovative data mining tools. This study describing the epidemiology of BSI in SOT serves as a proof of concept of such techniques in clinical research. Methods: The design of the study was a retrospective, single-center, cohort study. Data mining tools were used to extract information from the electronic medical record and merged it with data from the SRTR (Figure 1). First SOT from January 1, 2010 to December 31, 2015 were included. Charts of subjects with positive blood cultures were manually reviewed and adjudicated using CDC/NHSN and SCCM/ESICM criteria. The 1-year cumulative incidence was calculated using the Kaplan–Meier method. Cox proportional hazards models were used to identify risk factors for BSI and 1-year mortality. BSI was analyzed as a time-dependent covariate in the mortality model. Fisher's exact test and chi-square were used to identify risk factors for 30-day mortality and MDRO. Results: A total of 917 SOT recipients met inclusion criteria. Seventy-five patients experienced at least one BSI. The cumulative incidence was 8.4% (95% CI 6.8–10.4) (Figure 2). The onset of the first BSI episode was: 30 episodes (40%) <1 month, 33 (44%) 1–6 months, and 12 (16%) >6 months. The most common pathogens were Klebsiella sp. (16%), Vancomycin-resistant E. faecium (12%), E. coli (12%), CoNS (12%), and Candida sp. (9.3%). Nineteen isolates (25%) were identified as MDRO; the risk of MDRO was highest <1 month compared with 1–6 and >6 months (44.8 vs. 12.1 vs. 16.7; P = 0.01). The most common source of BSI was CLABSI (29%) (Figure 3). In multivariable analysis, the risk of BSI was associated with organ type (HR [95% CI] = Multiorgan 3.5 [1.1–11.6], liver 2.5 [1.1–5.4], heart 2.4 [1.1–5.1]) and acquisition of a BSI was associated with a higher 1-year mortality (HR = 8.7 [5.1–14.7]). In univariable analysis, a polymicrobial BSI (14.7 vs. 57.1%; P = 0.02), qSOFA ≥ 2 (0.0 vs. 25.5%; P = 0.02) and septic shock (3.9 vs. 52.2%; P < 0.001) were associated with an increased risk of death at 30 days. Conclusion: A BSI significantly affects the 1-year survival of SOT recipients. A qSOFA ≥ 2 can be used to identify patients at risk for death. Additionally, this study illustrates the potential of data mining tools to study infectious complications. Disclosures: All authors: No reported disclosures.