653. Direct Identification of Microorganisms in Positive Blood Cultures by the BioFire® FilmArray® Blood Culture Identification Panel Leads to Faster Optimal Antibiotic Therapy: A Before–After Study

Abstract Background Rapid pathogen identification from positive blood cultures may help optimize empiric antibiotic therapy quickly by reducing unnecessary broad spectrum antibiotic use and may improve patient outcomes. The BioFire® FilmArray® Blood Culture Identification Panel 1 (BF-FA-BCIP) identifies 24 pathogens directly from positive blood cultures without subculture. 3 resistance genes are included. We aimed to compare the time to optimal antibiotic therapy between BF-FA-BCIP and conventional identification. Methods We performed a single-center retrospective case-control before-after study of 386 cases (November 2018 to October 2019) with BF-FA-BCIP compared to 414 controls (August 2017 to July 2018) with conventional identification. The primary study endpoint was the time from blood sampling to implementation of optimal antimicrobial therapy. Secondary endpoints were time to effective therapy, length of hospital stay, and in-hospital and 30-day mortality. Outcomes were assessed using cause-specific Cox Proportional Hazard models and logistic regressions. Results We included 800 patients with comparable baseline characteristics. Main sources of blood stream infection (BSI) were urinary tract infection and intra-abdominal infection (19.2% vs. 22.0% and 16.8% vs. 15.7% for case and control groups, respectively). Overall, 212 positive blood cultures were considered as contaminations. Identification results were available after a median of 21.9 hours by the BF-FA-BCIP and 44.3 hours by the conventional method. Patients with BF-FA-BCIP received the optimal therapy after a median of 25.5 hours (95%CI 21.0 - 31.2) as compared to 45.7 hours (95%CI 37.7 - 51.2) in the control group (Figure 1). We found no effect of the identification method on secondary outcomes. Kaplan-Meier curve representing the probability of implementing the optimal therapy at any given time according to the identification method (Standard vs. BF-FA-BCIP). Shaded ribbons represent the 95 % confidence interval (CI). The vertical dashes represent censored data. The vertical dotted lines represent the median time, i.e. the time at which 50 % of the patients obtained the optimal therapy, for the two methods. Median (95 % CI) time to optimal therapy is 45.7 (37.7 - 51.4) hours with the Standard method and 25.5 (21.0- 31.2) hours with Biofire. The tables below the curves present the numbers expecting optimal therapy according to the bacteria identification method, as well as the number of censored data in parenthesis. Panel A shows data from 0 to 900 hours. Panel B shows the data from 0 to 90 hours to better visualize how the probability to implement optimal therapy varies in the first 72 hours. Conclusion In conclusion, rapid pathogen identification by BF-FA-BCIP was associated with an almost 24h earlier initiation of the optimal antibiotic therapy in BSI. However, the overall benefit for individual patients seems to be limited. Future studies should assess the cost-effectiveness and impact on the prevention of antibiotic resistance using this diagnostic approach. Disclosures All Authors: No reported disclosures

between the results of the QFT-Plus and T-SPOT.TB was substantial (kappa=0.644, p＜0.001). The area under the ROC curve of the QFT-Plus and T-SPOT.TB for diagnosing ATB was 0.759 (95%CI 0.689-0.829) vs 0.810 (95%CI 0.742-0.877), respectively, and there was no significant difference (p=0.303). the sensitivity of the QFT-Plus and T-SPOT.TB was 85.2% vs 89.5%, while the specificity was 61.7% vs 52.2%, respectively. In 33 Patients with pathologically confirmed ATB, the sensitivity of QFT-Plus and T-SPOT.TB was 87.9% vs 93.9% (p=0.669), respectively. In 78 patients (36.1%) who received glucocorticoid / immunosuppressive / biological agents, the positive rate of QFT-Plus was 35.9% (28/78), which was significantly lower than that of those who did not receive these agents (77 / 138pm,55.8%) (p=0.005), but there was no significant difference in the positive rate of T-SPOT.TB between the two groups (52.6% vs. 62.3%, p=0.162). The positive rate for both tests was independent of the peripheral blood lymphocyte count (p=0.675 for QFT-Plus vs. P=0.138 for T-SPOT.TB).

Conclusion.
There was no significant difference between the QFT-Plus and T-SPOT.TB in the diagnosis of ATB. QFT-plus might be prone to indeterminate results and influenced by the immunosuppressive status. The results need to be verified by a prospective cohort study with large sample. Background. Rapid pathogen identification from positive blood cultures may help optimize empiric antibiotic therapy quickly by reducing unnecessary broad spectrum antibiotic use and may improve patient outcomes. The BioFire® FilmArray® Blood Culture Identification Panel 1 (BF-FA-BCIP) identifies 24 pathogens directly from positive blood cultures without subculture. 3 resistance genes are included. We aimed to compare the time to optimal antibiotic therapy between BF-FA-BCIP and conventional identification.

Disclosures. All Authors
Methods. We performed a single-center retrospective case-control before-after study of 386 cases (November 2018 to October 2019) with BF-FA-BCIP compared to 414 controls (August 2017 to July 2018) with conventional identification. The primary study endpoint was the time from blood sampling to implementation of optimal antimicrobial therapy. Secondary endpoints were time to effective therapy, length of hospital stay, and in-hospital and 30-day mortality. Outcomes were assessed using cause-specific Cox Proportional Hazard models and logistic regressions.
Results. We included 800 patients with comparable baseline characteristics. Main sources of blood stream infection (BSI) were urinary tract infection and intra-abdominal infection (19.2% vs. 22.0% and 16.8% vs. 15.7% for case and control groups, respectively). Overall, 212 positive blood cultures were considered as contaminations. Identification results were available after a median of 21.9 hours by the BF-FA-BCIP and 44.3 hours by the conventional method. Patients with BF-FA-BCIP received the optimal therapy after a median of 25.5 hours (95%CI 21.0 -31.2) as compared to 45.7 hours (95%CI 37.7 -51.2) in the control group (Figure 1). We found no effect of the identification method on secondary outcomes.
Kaplan-Meier curve representing the probability of implementing the optimal therapy at any given time according to the identification method (Standard vs. BF-FA-BCIP).
Shaded ribbons represent the 95 % confidence interval (CI). The vertical dashes represent censored data. The vertical dotted lines represent the median time, i.e. the time at which 50 % of the patients obtained the optimal therapy, for the two methods. Median (95 % CI) time to optimal therapy is 45.7 (37.7 -51.4) hours with the Standard method and 25.5 (21.0-31.2) hours with Biofire. The tables below the curves present the numbers expecting optimal therapy according to the bacteria identification method, as well as the number of censored data in parenthesis. Panel A shows data from 0 to 900 hours. Panel B shows the data from 0 to 90 hours to better visualize how the probability to implement optimal therapy varies in the first 72 hours.
Conclusion. In conclusion, rapid pathogen identification by BF-FA-BCIP was associated with an almost 24h earlier initiation of the optimal antibiotic therapy in BSI. However, the overall benefit for individual patients seems to be limited. Future studies should assess the cost-effectiveness and impact on the prevention of antibiotic resistance using this diagnostic approach.
Disclosures. Background. Appropriate antibiotic (Ab) therapy of bloodstream infections (BSI) is often delayed by time to blood culture (BC) positivity, species (sp) identification and Ab sensitivity (sensi). The T2Resistance (T2R) Panel is a direct-from-blood (culture-independent) diagnostic that detects 13 genetic markers associated with methicillin-resistant S. aureus (MRSA), vancomycin-resistant Enterococcus (VRE), ESBL-and carbapenemase-producing Enterobacteriaceae (E). We assessed T2R performance in detecting these resistant bacteria in whole blood (WB) and analyzed possible impact on time to appropriate Ab.
Methods. We performed T2R using WB samples obtained from patients (pts) on the same day as BCs from July 2019-2020. Receipt of appropriate Ab was assessed at time of empiric, Gram stain-directed, MALDI-directed (sp identification) and sensi-directed therapy. T2R results were not available to care teams. Teams were notified of positive BCs. Stewardship optimized Abs based on sensi.

Conclusion.
There was a significant delay in appropriate Ab therapy of BSIs, especially in pts infected with VRE and ESBL/KPC-E. T2R rapidly and accurately detected BSI caused by VRE and ESBL/KPC-E, and has the potential to significantly shorten time to appropriate Ab.