Memorial Hermann Memorial City Medical Center

For patients with atrial fibrillation, the use of oral anticoagulant therapy to prevent stroke is limited by the risk of bleeding. Left atrial appendage closure is considered for patients who are unsuitable candidates for long-term anticoagulation, but its role in patients who are eligible for anticoagulants has not been established. In this ongoing, prospective, international, randomized trial involving patients with atrial fibrillation who were suitable candidates for anticoagulation, we randomly assigned patients in a 1:1 ratio to receive either device-based left atrial appendage closure (device group) or non-vitamin K antagonist oral anticoagulant (NOAC) therapy (anticoagulation group). The primary efficacy end point - a composite of death from cardiovascular causes, stroke, or systemic embolism - was tested for noninferiority (noninferiority margin, 4.8 percentage points) after 3 years of follow-up. The primary safety end point, non-procedure-relatedbleeding, was tested for superiority. Of the 3000 patients who underwent randomization, 1499 were assigned to the device group and 1501 to the anticoagulation group. The mean (±SD) age of the patients was 71.7±7.5 years, 31.9% of the patients were women, and the mean CHA2DS2-VASc score was 3.5±1.3. At 3 years, a primary efficacy end-point event had occurred in 81 patients (Kaplan-Meier estimate, 5.7%) in the device group and in 65 patients (Kaplan-Meier estimate, 4.8%) in the anticoagulation group (difference, 0.9 percentage points; 95% confidence interval [CI], -0.8 to 2.6; P<0.001 for noninferiority). Non-procedure-related bleeding occurred in 154 patients (Kaplan-Meier estimate, 10.9%) in the device group and in 260 patients (Kaplan-Meier estimate, 19.0%) in the anticoagulation group (hazard ratio, 0.55; 95% CI, 0.45 to 0.67; P<0.001 for superiority). Among patients with atrial fibrillation who were candidates for anticoagulation, device-based left atrial appendage closure was noninferior to NOAC therapy with respect to a composite of death from cardiovascular causes, stroke, or systemic embolism and was superior to NOAC therapy for non-procedure-related bleeding at 3 years. (Funded by Boston Scientific; CHAMPION-AF ClinicalTrials.gov number, NCT04394546.).

The discrepancy between the supply and demand of RNs creates pressure on nursing leaders to find innovative solutions to strengthen the nursing workforce and reduce new graduate nurses' time in orientation. In response, Memorial Hermann Health System leaders developed the Tiered Academic Partnership Model (TAPM). The model provides a strategic framework to align academic partnerships with health system nursing workforce priorities. The TAPM supports strategic, outcomes-driven partnerships between health systems and academic partners. TAPM categorizes partnerships into 3 tiers to optimize clinical placements, improve new graduate nurse readiness, and enhance conversion-to-hire rates. This scalable model fosters intentional collaboration, operational efficiency, and stronger workforce development.

High-throughput microscopy necessitates 3D image storage, visualization, and analysis in terabyte to petabyte scales. Centralized high-performance computing (HPC) infrastructure provides the resources, but interfacing software is limited. We developed an extensible platform with a scalable image storage format (SISF) and content delivery network (CDN) to enable fast, random access to compressed data. Additionally, we built a cloud-based nTracer2 software to annotate neuron morphology from SISF images in a web browser.

Traumatic brain injury (TBI) presents complex management scenarios, particularly in patients requiring anticoagulation for concurrent conditions such as venous thromboembolism (VTE) or atrial fibrillation (AF). A systematic search of PubMed/MEDLINE, Embase, and the Cochrane Library databases was conducted to identify relevant studies. Inclusion criteria encompassed studies assessing the effects of anticoagulation therapy on outcomes such as re-hemorrhage, hematoma expansion, thrombotic events, and hemorrhagic events in TBI patients with subdural hematomas (SDH). This systematic review critically addresses two key questions: the optimal timing for initiating anticoagulation therapy and the differential impact of this timing based on the type of intracranial bleed, with a specific focus on subdural hematomas (SDH) compared to other types. Initially screening 508 articles, 7 studies met inclusion criteria, which varied in design and quality, precluding meta-analysis. The review highlights a significant knowledge gap, underscoring the lack of consensus on when to initiate anticoagulation therapy in TBI patients, exacerbated by the need for anticoagulation in the presence of VTE or AF. Early anticoagulation, particularly in patients with SDH, may elevate the risk of re-hemorrhage, posing a clinical dilemma. Evidence on whether the type of intracranial hemorrhage influences outcomes with early anticoagulation remains inconclusive, indicating a need for further research to tailor management strategies effectively. This review underscores the scarcity of high-quality evidence regarding anticoagulation therapy in TBI patients with concurrent conditions, emphasizing the necessity for well-designed prospective studies to elucidate optimal management strategies for this complex patient population.

Objective and Design:The purpose of this study was to evaluate the diagnostic value of methicillin-resistant Staphylococcus aureus (MRSA) nasal screening utilizing polymerase chain reaction (PCR) assays in patients with osteomyelitis.Setting:A multisite, retrospective adult chart review from March 2021 to June 2022 was conducted, with no interventions performed. Patients treated with anti-MRSA therapy for osteomyelitis, MRSA nares PCR collected within 48 hours of antibiotic initiation, and related cultures were evaluated.Patients:Adults with associated cultures were assessed for concordance with MRSA nares PCR screening results. The primary outcome was the diagnostic value of MRSA nares PCR assay screening for predicting MRSA osteomyelitis. An assessment of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) was performed. Key secondary outcomes included length of hospital stay and duration of anti-MRSA therapy.Results:One hundred seven patients with MRSA nares PCR sensitivities were included in this assessment. The PPV and NPV were determined to be 25% CI (10.08–49.79%) and 94.7% CI (91.29–96.87%), respectively. Median and interquartile range durations of anti-MRSA therapy were decreased in the MRSA PCR negative group at 5 (3–8) versus 6.5 (6–9.75) days (p = 0.03752).Conclusion:This research showed a high NPV (94.7%) and a low PPV (25%) that aligned with other studies evaluating MRSA nares PCR utilization in osteomyelitis. Additionally, despite no active intervention on the results, early de-escalation of inappropriate antibiotic therapy was observed.

Abstract Background Several new β-lactam antibiotics were recently developed for treatment of serious infections due to gram-negative bacteria (GNB) with difficult-to-treat resistance (DTR). This multicenter retrospective cohort study examined temporal trends in prevalence of GNB with DTR and the use of new β-lactams in the southeastern United States. Methods The prevalence of GNB with DTR, including Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter species was determined in 9 hospitals geographically spread within the Southeastern Research Group Endeavor (SERGE-45) between 2015 to 2020. Antibiotic use (AU) of new β-lactams was also obtained from the 9 hospitals during the study period. New β-lactams included ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, imipenem/cilastatin/relebactam, and cefiderocol. Logistic regression analysis was utilized to examine temporal trends in prevalence of GNB with DTR and cumulative AU of new β-lactams. Results The overall prevalence of GNB with DTR in the 9 hospitals was 0.78% with a numerical increase from 0.67% to 0.97% between 2015 and 2020 (p=0.067) [Figure]. DTR was more prevalent among Acinetobacter spp., followed by P. aeruginosa, and Enterobacterales (11.8%, 3.5%, and 0.2%, respectively). There was a significant increase in the prevalence of DTR isolates among Acinetobacter spp. from 2.7% to 20.7% (p&amp;lt; 0.001) and Enterobacterales from 0.07% to 2.6% (p=0.025), but not P. aeruginosa (p=0.46) between 2015 and 2020. The cumulative AU of new β-lactams in the 9 hospitals was 2 days of therapy per 1000 patient-days. There was numerical increase in AU of these agents from 0.03 to 2.22 days of therapy per 1000 patient days during the 6-year study period (p=0.096) [Figure]. Conclusion The overall prevalence of GNB with DTR and cumulative use of new β-lactams remain relatively low in the southeastern United States. However, the upward trend in prevalence of DTR isolates, particularly among Acinetobacter spp. and Enterobacterales, is concerning and may drive future increased use of β-lactams. Additional efforts to benchmark the use and appropriateness of new β-lactams are crucial to preserve their efficacy against bacteria with DTR. Disclosures P. Brandon Bookstaver, PharmD, Spero Therapeutics: Advisor/Consultant Julie Ann Justo, PharmD, MS, FIDSA, BCPS-AQ ID, bioMerieux: Honoraria|bioMerieux: Honoraria|Entasis Therapeutics: Advisor/Consultant|Entasis Therapeutics: Advisor/Consultant|Gilead Sciences: Advisor/Consultant|Gilead Sciences: Advisor/Consultant|Merck &amp; Co: Advisor/Consultant|Merck &amp; Co: Advisor/Consultant|Shionogi: Advisor/Consultant|Shionogi Inc.: Advisor/Consultant|Spero Therapeutics: Honoraria|Spero Therapeutics: Honoraria|Vaxart: Stocks/Bonds Julie Ann Justo, PharmD, MS, FIDSA, BCPS-AQ ID, bioMerieux: Honoraria|bioMerieux: Honoraria|Entasis Therapeutics: Advisor/Consultant|Entasis Therapeutics: Advisor/Consultant|Gilead Sciences: Advisor/Consultant|Gilead Sciences: Advisor/Consultant|Merck &amp; Co: Advisor/Consultant|Merck &amp; Co: Advisor/Consultant|Shionogi: Advisor/Consultant|Shionogi Inc.: Advisor/Consultant|Spero Therapeutics: Honoraria|Spero Therapeutics: Honoraria|Vaxart: Stocks/Bonds Bruce M. Jones, Pharm.D., FIDSA, BCPS, AbbVie: Advisor/Consultant|AbbVie: Honoraria|La Jolla: Honoraria|Melinta: Advisor/Consultant|Paratek: Honoraria|Regeneron: Honoraria.

Abstract Cancer research, including that of breast cancer, has increasingly relied on molecular profiling based on advances in genomic technology. Although these techniques have permitted scientists to unravel the process by which cancer develops, scientists still struggle to effectively translate the vast amounts of patient data into clinically meaningful results. As a result, tasks such as predicting the human response to differing treatments remains a major challenge in cancer treatment.There have been many studies attempting to determine the survival indicators of breast cancer patients. However, most of these analyses were predominantly performed using traditional statistical methods, which are imperfect and inadequate in tackling vast amounts of data or unstructured data on human breast cancer. With the exponential progress in computing power and artificial intelligence approaches, we believe that there is an opportunity for machine learning to supersede our current capabilities in fully understanding the correlations between geneset alterations, drug responses, and the prognosis of breast cancer patients. This information would greatly benefit scientists and physicians in developing clinical therapeutic strategies, such as performing personalized treatment.This machine learning project employs multiple machine learning approaches, including a novel deep learning algorithm, in building models for the detection and visualization of significant prognostic indicators of breast cancer patient survival rate. The clinical and genomic data of 1,980 primary breast cancer samples used in this project were obtained from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database of cBioPortal. The data was preprocessed and then split to train eight classical machine learning models and the aforementioned deep learning Convolutional Neural Network (CNN) model.These models were evaluated using the recall scores, the accuracy scores, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) on the training dataset and confirmed using the rest of the data of the dataset. Both the deep learning and machine learning methods produced desirable prediction accuracies. However, the deep learning model noticeably outperformed all other classifiers and achieved the highest accuracy (AUC = 0.900). This project was constructed in the Google Colab environment based on python and its programming libraries with data visualization, Tensorflow, and Keras.The CNN model demonstrates a powerful ability to be used as a systematic framework for real time prediction by end users. A web application for the breast cancer survival rate prediction was designed and developed using streamlit, Tensorflow, Keras and python libraries to allow end-users to interact with the model with ease and obtain quick and accurate prediction.

Purpose We report a probable case of morbilliform drug eruption secondary to fidaxomicin in a patient with Clostridioides difficile infection (CDI). Summary: A 62-year-old female presented to our institution’s emergency department (ED) with symptoms consistent with Clostridioides difficile infection. The patient was prescribed 2 weeks of oral vancomycin for CDI prior to presentation. Given insufficient response to vancomycin, the patient was started on fidaxomicin with a planned 10-day course. After 2 doses of fidaxomicin, the patient developed a rash on her back that spread within 24 hours. The patient did not experience relief upon administration of a variety of medications for allergic reaction. Improvement was noted upon discontinuation of fidaxomicin. The Food and Drug Administration reports that < 2% of adults treated with fidaxomicin experience a rash as an adverse effect. Conclusion: Fidaxomicin was a probable cause of morbilliform drug eruption in our patient with CDI. The patient improved upon discontinuation of fidaxomicin.