Fast Time Research Articles

Is it beneficial to use lateral protective crossing K-wires during medial open wedge high tibial osteotomy? A retrospective comparative study

BackgroundAn iatrogenic lateral hinge fracture is a common intraoperative problem that may occur during medial open wedge high tibial osteotomy (MOWHTO). This study aims to assess the significance of using additional crossing lateral K-wires and their advantage in protecting the lateral hinge during MOWHTO procedures.MethodsThe data of patients fulfilling the inclusion criteria who underwent MOWHTO between May 2021 and August 2022 were retrospectively evaluated. One group had additional lateral hinge crossing K-wires (+ MOWHTO group), while the other did not (-MOWHTO group). Both groups were assessed for rate of intraoperative lateral hinge fractures, knee injury and osteoarthritis outcome score − 12 (KOOS-12), medial proximal tibial angle (MPTA), time of union, and time to return to work. The outcomes were compared using the independent T-test for continuous variables and the Fisher Exact test for nominal variables. A p-value of < 0.05 was considered statistically significant for both tests.ResultsThe study included forty-eight patients; twenty-four in each treatment group. The mean follow-up durations were 30.5 ± 3.6 months for + MOWHTO and 31.6 ± 3.2 months for –MOWHTO (p = 0.26). There was no statistically significant difference regarding mean age, sex, KOOS-12, MPTA, and time of surgery between both groups. The + MOWHTO group had a faster time of union (p = 0.001), an earlier return to work (p = 0.002), and a lower rate of intraoperative lateral hinge fractures (p = 0.04).ConclusionThis study demonstrated that using additional crossing lateral K-wires during MOWHTO had a beneficial effect on reducing the rate of iatrogenic lateral hinge fractures, with a faster time of union, and an early return to work. The KOOS-12, MPTA, and mean operative time did not reveal significant differences between treatment groups.Level of evidenceretrospective cohort comparative study; level III.

Impact of religious fasting on ocular dryness: objective and subjective assessment

BackgroundCertain religions require long hours of fasting, abstaining from fluid intake for durations extending up to 16 h. Lack of fluid intake may alter multiple physiological parameters, which can influence the ocular system. In this prospective study, we evaluated the effect of prolonged fasting on dry eye disease using both objective and subjective measures.MethodsWe included patients who fasted for at least 12 h a day for at least 2 weeks, including the testing day, and retested them at least 1 week after the fasting period had ended with no fasting on the testing day. At each visit, Non-Invasive Keratograph Break up time (NIKBUT) and Tear meniscus height (TM) were measured using the Oculus Keratograph 5 M. Ocular Surface Disease Index (OSDI) was evaluated at each timepoint to assess dryness symptoms subjectively.ResultsThis study included a total of 40 patients. NIKBUT values during the fasting times were higher than during the non-fasting times; however, the difference was statistically non-significant. There were no significant differences in TM and OSDI measurements between non-fasting and fasting periods (p &amp;gt; 0.05). Lubricating eyedrop use was significantly lower in fasting patients.ConclusionOur study showed that prolonged fasting, including complete abstinence from fluid intake, did not lead to significant dryness, neither subjectively nor objectively. During fasting, patients used significantly fewer lubricating drops compared to non-fasting periods.

A cohort study reveals shared and distinct serum metabolic biomarkers for major adverse cardiovascular events in middle-aged and older adults.

We assessed the association of serum metabolites with the occurrence of major adverse cardiovascular events (MACE) in middle-aged and elderly individuals, explored the value of metabolomics in predicting MACE, and compared the distinctions in MACE risk-related metabolic biomarkers between middle-aged and elderly groups. Among the participants of the UK Biobank who underwent baseline assessment through nuclear magnetic resonance (NMR)-based metabolomic profiling of 168 serum metabolites and had complete covariates and clinical lipid parameters, we included those without a previous diagnosis of ischemic heart disease, cerebrovascular disease, heart failure, or cardiac arrest and not on lipid-lowering medications. Relevant covariates included sociodemographic characteristics, lifestyle factors, clinical information, and fasting time. Cox regression gave adjusted hazard ratios for metabolites, including the concentrations of various lipoprotein particles, compositional profiles of different lipoproteins, ketone bodies, amino acids, fatty acids, and additional low-molecular-weight metabolic biomarkers. The least absolute shrinkage and selection operator (LASSO) regression was applied to these metabolites to screen characteristic metabolic variables. Selected feature metabolic biomarkers were added to the established model for predicting MACE risk; risk differentiation (C-statistic) and reclassification (continuous net reclassification improvement [NRI], integrated differentiation index [IDI]) were evaluated. This study included 54,561 UK Biobank participants (34,797 middle-aged adults and 19,764 elderly adults) and was followed for a median of more than 12 years. Of these, there are 1799 middle-aged individuals and 2527 elderly individuals incident of MACE (ischemic heart disease, stroke, and cardiovascular deaths). After adjusting for relevant covariates, Cox regression yielded metabolic biomarkers associated with the occurrence of MACE in the population (false discovery rate controlled P < 0.05). In the elderly, the metabolites associated with increased MACE risk were notably diminished compared to the middle-aged; and the elderly group underscored the protective function of medium and small HDL and their constituents, docosahexaenoic acid, and glycine. The more comprehensive model, which additionally includes the feature metabolic biomarkers, demonstrated enhanced discriminatory power and predictive accuracy for MACE occurrence among middle-aged individuals, evidenced by improved C-statistics (from 0.711 [95% CI 0.699-0.722] to 0.723 [0.711-0.734]), a continuous NRI of 0.247 [0.207-0.315], and an absolute IDI of 0.005 [0.004-0.008]. Its evaluation value is superior to that in the elderly. Our study explored the association of circulating metabolites with MACE risk in middle-aged and elderly adults and made comparisons. Metabolomic insights have revealed biomarkers associated with new-onset MACE in different age populations, highlighting the value of protective metabolites in the elderly. This provides instrumental information to possibly implement precision medicine for preventing MACE.

Deep Learning and Single-Molecule Localization Microscopy Reveal Nanoscopic Dynamics of DNA Entanglement Loci.

Understanding molecular dynamics at the nanoscale remains challenging due to limitations in the temporal resolution of current imaging techniques. Deep learning integrated with Single-Molecule Localization Microscopy (SMLM) offers opportunities to probe these dynamics. Here, we leverage this integration to reveal entangled polymer dynamics at a fast time scale, which is relatively poorly understood at the single-molecule level. We used Lambda DNA as a model system and modeled their entanglement using the self-avoiding wormlike chain model, generated simulated localizations along the contours, and trained the deep learning algorithm on these simulated images to predict chain contours from sparse localization data. We found that the localizations are heterogeneously distributed along the contours. Our assessments indicated that chain entanglement creates local diffusion barriers for switching buffer molecules, affecting the photoswitching kinetics of fluorescent dyes conjugated to the DNA molecules at discrete DNA segments. Tracking these segments demonstrated stochastic and subdiffusive migration of the entanglement loci. Our approach provides direct visualization of nanoscale polymer dynamics and local molecular environments previously inaccessible to conventional imaging techniques. In addition, our results suggest that the switching kinetics of the fluorophores in SMLM can be used to characterize nanoscopic local environments.

Relationship Between Preoperative Fasting Duration and Anxiety Levels With Postoperative Pain, Nausea-Vomiting, and Sleep Quality in Orthopedic Surgical Patients: A Cross-Sectional Study.

This study is a cross-sectional study aimed to determine the association between preoperative fasting time and anxiety level and early postoperative pain intensity, nausea-vomiting severity, and sleep quality in patients undergoing orthopedic surgery. The study was conducted between March and June 2024 and completed with 188 patients. In the study, patient information form, Amsterdam Preoperative Anxiety and Information Scale, and Richards-Campbell Sleep Questionnaire were used. Correlation analysis indicated a significant negative correlation between postoperative sleep quality and pain intensity. There was a significant positive correlation between preoperative anxiety level and preoperative solid food fasting and fluid fasting times. According to the multiple linear regression model, preoperative anxiety level was found to have a significant effect on pain severity, and pain severity at the postoperative 24th hour significantly affected postoperative sleep quality. Adjusting patients' fasting durations prior to surgical interventions according to evidence-based guideline recommendations and monitoring anxiety closely are simple, practical, and safe measures that could alleviate postoperative pain and nausea-vomiting and improve sleep quality, potentially enhancing outcomes, comfort, and the quality of care.

Exploring LDoS Attack Detection in SDNs using Machine Learning Techniques

This study investigates the application of machine learning algorithms for detecting Low-Rate Denial-of-Service (LDoS) attacks within Software-Defined Networks (SDNs). LDoS attacks are challenging to detect due to their similarity to normal network behavior. This study evaluates the performance of algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), and BIRCH clustering in this challenge. The results show that the LR and BIRCH algorithms outperformed other approaches, achieving a detection accuracy of 99.96% with minimal false positive and negative rates. The models demonstrated a fast detection time of 0.03 seconds, highlighting the potential of machine learning to improve SDN security. The study recommends future work to validate these findings in real-world environments to strengthen security systems.

Carbon Quantum Dot Nanoparticles Enhance the Efficacy of Spodoptera littoralis Nucleopolyhedrovirus Suspoemulsion.

This study evaluates the efficacy of Spodoptera littoralis nucleopolyhedrovirus (SpliNPV) and laboratory-synthesized carbon quantum dot nanoparticles (CQDNPs) against the second instar Spodoptera littoralis larvae under laboratory and greenhouse conditions. Individually, both SpliNPV and CQDNPs exhibited substantial lethality (91.6% and 83.3% at 1 × 108 OBs/ml and 700 mg/ml, respectively) (p < 0.05). The LC50 values were 1.88 × 105 OB/ml and 434.2 mg/mL, and the LT50 values were 8.9 and 9.8 days, respectively. Four LC-based combined treatments demonstrated significant additive effects, with the SpliNPV (LC50) + CQDNPs (LC25) combination achieving the optimum effect with a mortality rate of 86.3% and an LT50 value of 6.6 days, leading to its selection for the suspoemulsion nanoparticle (SENP) formulation. The SENP formulation displayed superior performance, achieving the highest mortality rates and fastest killing times across all environments: 89.0% in laboratory conditions, 83.3% on eggplant plants, and 76.6% on pepper plants. In contrast, the suspoemulsion (SE) and unformulated (UF) formulations showed lower efficacy, emphasizing the importance of formulation in enhancing the biological activity of SpliNPV. The LT50 values further supported these findings, with the SENP formulation demonstrating the shortest LT50 values, indicating faster lethality. A significant decrease in CHS-B, IIM2, PER3, REPAT14, and CDA1 expression was observed, particularly in the combined CQDNPs + SpliNPV treatment, while API expression increased significantly. These findings highlight the potential of nanoparticle-enhanced formulations like SENP, and integrating CQDNPs with SpliNPV can significantly enhance pest control efficacy.

Measurement of scattering azimuthal distribution of polarized gamma-rays in compton scattering using GAGG(Ce) scintillator

Abstract Recently, the measurement of gamma-rays polarization has increasingly become important for applications in various fields such as astrophysics and bioimaging. Accordingly, there is a growing need for high-performance polarimeters to meet these requirements. In this study, we fabricated the gamma-rays polarization detector using Gd3(Ga,Al)5O12(Ce) scintillator, which has high energy resolution, high amount of luminescence, and fast decay time. This detector mainly consists of scatterer and absorber, each of which use pixelated GAGG array. By using this detector, the gamma-rays polarization was measured in MeV range (6.6 MeV), and the performance as polarimeter was assessed.

Cascaded AC-DC parallel boost-flyback converter for power factor correction

A two-stage power factor correction (PFC) topology achieves a higher power factor quality and lower harmonic distortion than a single-stage converter. This paper introduces a two-stage PFC topology using a parallel boost and flyback converter which is employed as a voltage regulator The main boost converter is used for PFC and the other is the active filter circuit. The filter is implemented to improve the quality of phase-current and eliminate the switching loss. Furthermore, a reaction curve of Ziegler-Nichol’s method determines the controller parameter for cascaded PFC converter circuit. Simulated and experimental results are presented to validate the proposed method. The total harmonic distortion (THD) value decreases significantly from 83.35% become 0.98% in the simulation. In addition, experimental results show that the current response has good performances, including less harmonics, higher power factor, and lower THD value compared to without a PFC circuit. The PF increased from 0.43 become 0.96, the THD value decreased from 49.4% become 16.2%, and contains a small number of harmonics. The proposed controller method has better responses than the conventional one, including small steady-state error, fast rise time and settling time. A microcontroller (MCU), type STM32F407VG, produced by STMicroelectronics is used to execute the proposed control in both converters.

Enhanced plasma wave excitation in a tapered plasma channel through chirped laser beatwaves

The excitation of plasma waves by the beatwave of two-color laser beams within a tapered plasma channel has been investigated both analytically and through particle-in-cell (PIC) simulations. This study presents a promising approach for beatwave accelerators. The design aims to achieve a more stable and enhanced plasma wave amplitude, even under non-resonant conditions, compared to untapered channels. For the analytical description, we solved the plasma wave equation generated by two beating laser beams propagating through a tapered channel with a linear radial density profile. The study further validates its results by comparing the analytical predictions with PIC simulations of the beatwave phenomenon in the tapered channel. The findings confirm that this design significantly enhances plasma wave amplitude compared to untapered channels. In addition, we demonstrated that employing a chirped laser pulse with a fast rise time can significantly increase the strength of the plasma wave.

A novel physical vapor deposition setup applying high-frequency currents: Deposition of Cu thin films

A pioneering laboratory apparatus of physical vapor deposition (PVD) for thin film fabrication is herein introduced. This innovative setup harnesses high-frequency currents (Eddy currents) and a Zero-Voltage Switching (ZVS) heater to sublimate the sacrificial material. The as-fabricated system offers low energy consumption and fast deposition time, leading to the formation and growth of thin films in various thicknesses. To reveal its effectiveness, Cu thin films were deposited on Si wafers. Morphological, structural, and surface profile characterizations confirmed the growth of thin films consisting of Cu nanoparticles. Also, a parametric study of deposition time was conducted to determine the optimum conditions for the thin film fabrication.

Biotinylation-based lateral flow assays for pathogenic and total bacteria detection.

It is highly desirable to concurrently evaluate both pathogenic and total bacteria in water and food environments. As a point-of-care platform for biochemical tests, lateral flow assay (LFA) has been widely used for pathogenic bacteria due to its portability and fast time of outcome. However, traditional LFA was unable to detect total bacteria due to the lack of a universal antibody that could bind all the bacteria. Here, we used sulfo-NHS-biotin to label nonspecifically the lipoprotein of bacterial surface. Meanwhile, streptavidin was used for both AuNP modification and membrane coating to prepare Str-AuNP reporter and test line, respectively. Thus, a biotinylation-based LFA was established for total bacteria detection. The conditions for preparing biotinylated bacteria and Str-AuNP were optimized. Under the optimal condition, all the bacteria could be successfully biatinylated and further be semi quantified by using the test strips with color band. Good practicability of the as-developed LFA in detecting total bacteria from pond and wastewater was demonstrated. Combined with biotin-antibody for specific biotinylation, the as-developed FLA was also successfully used for pathogenic bacteria detection with good selectivity and without the de novo preparation of the test strips. For the first time, the nonspecific biotinylation of bacteria was integrated into the LFA to address the inherent challenges in LFA for total bacteria detection. Taking the advantage of the universal recognition reaction between the biotin and streptavidin, we established biotinylation-based LFAs for both pathogenic and total bacteria detection without the de novo preparation of the test strips. It would have practical applications in the rapid bacterial detection for water quality management and control.

Preoperative Fluid Fasting Time and Delirium: The Importance of the Safe Brain Initiative -A new approach for brain ERAS

Preoperative Fluid Fasting Time and Delirium: The Importance of the Safe Brain Initiative -A new approach for brain ERAS

Abstract 35: Impact of Artificial Intelligence Imaging Decision Support Software on Treatment of Acute Ischemic Stroke in England

Introduction: AI imaging decision support software is recommended by UK and USA stroke guidelines to facilitate identification and transfer of stroke patients eligible for endovascular therapy (EVT) but the impact on thrombectomy delivery is unclear. This prospective observational study evaluated the impact of Brainomix 360 Stroke software in four stroke networks (28 hospitals) in England’s National Health Service (NHS). The primary outcome was percentage of acute stroke patients receiving EVT (the EVT rate); door-in door-out (DIDO) times were assessed as a secondary outcome. Methods: Data were collected prospectively from the Sentinel Stroke National Audit Programme. The impact of Brainomix 360 Stroke software was assessed in two ways: comparison of EVT rates at the 28 evaluation sites and non-evaluation NHS sites before and after implementation (pre-implementation: Jan 2019-Feb 2020; post- : Jan 2022-Feb 2023); comparison of EVT rates and DIDO times at evaluation sites after implementation in patients for whom AI software was used and in those it was not. Multivariate regressions were used to evaluate whether AI use was a predictor of EVT or DIDO time, accounting for other clinical variables (e.g., age, NIHSS, day of week, time of day, time since onset). Results: The dataset included 71,327 patients from 28 evaluation hospitals. Figure 1 shows the change in EVT rates over time in evaluation (blue) and non-evaluation sites (yellow). EVT rate at evaluation sites increased from 2.3% pre-implementation to 4.6% post-implementation (p&lt;.0001). By contrast, EVT rate at non-evaluation sites changed from 1.6% to 2.6% (p&lt;.0001). After implementation, cases that were reviewed with AI software support were more likely to receive EVT (5.9% vs 3.6%; OR=1.6 [95% CI:1.3-1.9, p&lt;.0001). When limiting the analysis to cases admitted to primary stroke centres, the EVT rate was twice as high in cases reviewed with AI software (4.7% vs 2.2%; OR=2.3 [1.8-3.1], p&lt;.0001). DIDO times were shorter for cases reviewed with AI software (median 127 vs. 192 minutes; p&lt;.0001). Conclusions: This prospective study showed that use of AI imaging software was associated with a higher rate of EVT, both by comparing pre- vs. post-implementation data, as well as by comparing cases for whom AI software was versus was not used. Use of AI software was also associated with faster time to transfer. The results support guideline recommendations for AI software to be used in clinical practice.

Predicting the Number of Passengers in Public Transportation Areas Using the Deep Learning Model LSTM

Accurate predictions of the number of public transport passengers on buses in each region are crucial for operations. They are required by the planning and management authority for bus public transport. A deep learning-based LSTM prediction model is proposed to predict the number of passengers in 4 bus public transportation areas (central, north, south, and west), evaluated by MSLE, MAPE, and SMAPE with dropout, neuron, and train-test variations. The CSV dataset obtained from Auckland Transport(AT) New Zealand metro patronage report on bus performance(1/01/2019-31/07/2023) is used for evaluation. The best prediction model was obtained from the lowest evaluation value and relatively fast time with a dropout of 0.2, 32 neurons, and train-test 80-20. The prediction model on training and testing data improves with the suitability of tuning for four predictions for the next 12 months with mutual fluctuations. The strong negative correlation is central-south, while the strong positive correlation is north-west. Predictions are less closely interconnected and dependent, namely central-south. With its potential to significantly impact policy-making, this prediction model can increase public transport mobility in each region, leading to a more efficient and accessible public transport system and ultimately enhancing the public's daily lives. This research has practical implications for public transport authorities, as it can guide them in making informed decisions about service planning and resource allocation.

Hypercapnic warm-up and re-warm-up-A novel experimental approach in swimming sprint.

The purpose of this study was to determine the effective warm-up protocol using an added respiratory dead space (ARDS) 1200 ml volume mask to determine hypercapnic conditions, on the swimming velocity of the 50 m time trial front crawl. Eight male members of the university swimming team, aged 19-25, performed three different warm-up protocols: 1) standardized warm-up in water (WUCON); 2) hypercapnic warm-up in water (WUARDS); 3) hypercapnic a 20-minute transition phase on land, between warm-up in water and swimming test (RE-WUARDS). The three warm-up protocols were implemented in random order every 7th day. After each protocol, the 50 m time trial front crawl swimming (swimming test) was performed. The fastest time trial swimming of 50 m front crawl was achieved after the hypercapnic transition phase (RE-WUARDS) protocol and was 27.5 ± 1.6 seconds, 1.2% faster than hypercapnic warm-up protocol (p = 0.01). This result was confirmed by a higher swimming average speed of the exercise test after RE-WUARDS compared to WUARDS (p = 0.01). The use of ARDS provoked a state of tolerable hypercapnia (obtaining carbon dioxide concentration in arterialized blood pCO2 > 45 mmHg) achieving a post-warm-up of WUARDS value 49.7 ± 5.9 mmHg (compared to the control condition which was a statistically significant difference p = 0.02) and before time trial RE-WUARDS 45.7 ± 2.1 mmHg (p = 0.01 compared to WUCON). After breathing through the 1200 ml ARDS mask during the 20-minute re-warm-up phase, there was a trend of faster time trial among participants compared to the control condition, and statistically significantly faster times compared to WUARDS, indicating that further study is appropriate to verify the efficacy of the proposed method to improve swimming efficiency.

Causes of Stability in Dynamic Coalition Formation

We study the formation of stable outcomes via simple dynamics in cardinal hedonic games, where the valuations of agents change over time depending on the history of the coalition formation process. Specifically, we analyze situations where members of a coalition decrease their valuation for a leaving agent ( resentment ) or increase their valuation for a joining agent ( appreciation ). We show a series of convergence results for dynamics for resentful or appreciative agents which do not hold for classic dynamics. In particular, resentment turns out to be a strong stability-driving force. We complement our theoretical analysis with simulations that shed some light on the average running time of the dynamics and on the structure of the produced outcomes. From an algorithmic perspective, we obtain general hardness results for determining the fastest convergence time, results which also carry over to classic dynamics under static valuation functions. Finally, we explore a related model for preference updates where resentment is expressed by the deviator. We find a more nuanced picture, but still a broad possibility of convergence.

A magnetic field compatible readout circuit for enhanced coincidence time resolution in BGO Cherenkov radiation-based TOF-PET detectors.

Developing time-of-flight positron emission tomography/magnetic resonance imaging (TOF-PET/MRI) detectors that exploit prompt Cherenkov photons from bismuth germanate (BGO) crystals for estimating 511keV photon arrival time. To present a low-noise, high-speed electronic readout circuit design for BGO-based TOF-PET detectors that achieves enhanced coincidence time resolution (CTR) in presence of a strong magnetic field. The CTR of a BGO-based TOF-PET test detector employing a high-speed, low-noise electronic readout chain was evaluated in a strong magnetic field produced by a permanent magnet placed directly on top of the circuit. For these experiments, which exploit Cherenkov radiation for precise measurement of annihilation photon time arrival time difference, a point source of 22Na was positioned between a pair of 3×3×15mm3 polished BGO crystals wrapped in Teflon tape and optically coupled to 3×3mm2 ultra-violet (UV)-sensitive silicon photomultipliers (SiPMs). By incorporating both Cherenkov (prompt) and standard (slow) luminescence components, 283±8ps and 275±10ps full-width-half-maximum(FWHM) CTR were achieved without and with the permanent magnet present, respectfully. These values improved to 236±4ps and 216±17ps FWHM when only the Cherenkov components of the timing signal (events with the fastest rise time) were considered. Results indicate we have designed a high-performance readout circuit that achieves significantly the same CTR in BGO with or without a strong magnetic field present. This further demonstrates that UV SiPMs can effectively operate in a strong magnetic field while remaining highly advantageous for detecting Cherenkov radiation, thus highlighting their potential to be used in BGO-based TOF-PET/MRI scanners.

Influence of light intensity, pre-harvest fasting, and storage time on biochemical components in serum and plasma of broilers

Influence of light intensity, pre-harvest fasting, and storage time on biochemical components in serum and plasma of broilers

P-2105. Concordance of Multiplexed Molecular Lower Respiratory Panel with Standard Culture Method and Potential Clinical Impact on Antimicrobial Therapy

Abstract Background Pneumonia is the most common cause of health-care associated infections. The mainstay of diagnosis is respiratory culture, which is limited by up to 72-hour turnaround time and variable sensitivity. An added challenge is the emergence of antimicrobial resistance, which may confound the choice for empirical therapy. Rapid diagnostic tests have been developed to mitigate the challenges of diagnosis and treatment, but the clinical impact is not known. The Unyvero Lower Respiratory Tract Panel (LRT) is a qualitative multiplex nucleic acid test that can detect DNA of 20 microorganisms and 10 resistance genes in respiratory samples, with a 5-hour turnaround time. We hypothesized that use of the LRT on respiratory samples may have an impact on antimicrobial therapy and, consequently, antimicrobial stewardship. Methods The LRT was performed on a random sample of 48 respiratory tract specimens that were obtained inpatient. We assessed concordance of LRT with standard-of-care (SoC) testing. We performed a retrospective chart review for the clinical context in which specimens were obtained (infection suspected versus not) and to determine whether use of LRT would have had an impact on antimicrobial therapy at the time of care. Results Of 48 specimens, 25 (52%) had concordance between LRT and SoC testing and the remaining 23 specimens (48%) had discordance between LRT and SoC testing. Notably, 8 (17%) “discordant” specimens had organisms grow on culture that have no targets on the LRT (Candida species, Klebsiella aerogenes, Burkholderia cepacia complex, Streptococcus anginosus). In 3 cases where a resistance gene (CTX-M, mecA) was identified by LRT, antimicrobial susceptibility testing was compatible. In 7 cases, antibiotic therapy may have been impacted by use of LRT; in 5 cases therapy may have been initiated unnecessarily, and in 2 cases additional therapy may have been warranted. There were no cases where de-escalation of antibiotics would have been warranted. Conclusion The Unyvero LRT panel is an appealing diagnostic tool due to fast turnaround time, but a significant clinical impact due to its use has not yet been demonstrated. Though our study was limited by sample size, we found that LRT may have increased inappropriate use of antibiotics, rather than promoting stewardship. Disclosures Melissa R. Gitman, MD, Biomerieux, Inc: Grant/Research Support