Incidence and risk of post-COVID-19 thromboembolic disease and the impact of aspirin prescription; nationwide observational cohort at the US Department of Veteran Affairs.

INTRODUCTION: COVID-19 triggers prothrombotic and proinflammatory changes, with thrombotic disease prevalent in up to 30% SARS-CoV-2 infected patients. Early work suggests that aspirin could prevent COVID-19 related thromboembolic disorders in some studies but not others. This study leverages data from the largest integrated healthcare system in the United States to better understand this association. Our objective was to evaluate the incidence and risk of COVID-19 associated acute thromboembolic disorders and the potential impact of aspirin. METHODS: This retrospective, observational study utilized national electronic health record data from the Veterans Health Administration. 334,374 Veterans who tested positive for COVID-19 from March 2, 2020, to June 13, 2022, were included, 81,830 of whom had preexisting aspirin prescription prior to their COVID-19 diagnosis. Patients with and without aspirin prescriptions were matched and the odds of post-COVID acute thromboembolic disorders were assessed. RESULTS: 10.1% of Veterans had a documented thromboembolic disorder within 12 months following their COVID-19 diagnosis. Those with specific comorbidities were at greatest risk. Preexisting aspirin prescription was associated with a significant decrease risk of post-COVID-19 thromboembolic disorders, including pulmonary embolism (OR [95% CI]: 0.69 [0.65, 0.74]) and deep vein thrombosis (OR [95% CI]: 0.76 [0.69, 0.83], but an increased risk of acute arterial diseases, including ischemic stroke (OR [95% CI]: 1.54 [1.46, 1.60]) and acute ischemic heart disease (1.33 [1.26, 1.39]). CONCLUSIONS: Findings demonstrated that preexisting aspirin prescription prior to COVID-19 diagnosis was associated with significantly decreased risk of venous thromboembolism and pulmonary embolism but increased risk of acute arterial disease. The risk of arterial disease may be associated with increased COVID-19 prothrombotic effects superimposed on preexisting chronic cardiovascular disease for which aspirin was already prescribed. Prospective clinical trials may help to further assess the efficacy of aspirin use prior to COVID-19 diagnosis for the prevention of post-COVID-19 thromboembolic disorders.

Improving postsurgical fall detection for older Americans using LLM-driven analysis of clinical narratives.

Postsurgical falls have significant patient and societal implications but remain challenging to identify and track. Detecting postsurgical falls is crucial to improve patient care for older adults and reduce healthcare costs. Large language models (LLMs) offer a promising solution for reliable and automated fall detection using unstructured data in clinical notes. We tested several LLM prompting approaches to postsurgical fall detection in two different healthcare systems with three open-source LLMs. The Mixtral-8×7B zero-shot had the best performance at Stanford Health Care (PPV = 0.81, recall = 0.67) and the Veterans Health Administration (PPV = 0.93, recall = 0.94). These results demonstrate that LLMs can detect falls with little to no guidance and lay groundwork for applications of LLMs in fall prediction and prevention across many different settings.

National rollout of a medication safety dashboard to improve testing for latent infections among biologic and targeted synthetic disease-modifying agent users within the Veterans Health Administration.

OBJECTIVE: To develop, deploy, and evaluate a national, electronic health record (EHR)-based dashboard to support safe prescribing of biologic and targeted synthetic disease-modifying agents (b/tsDMARDs) in the United States Veterans Affairs Healthcare System (VA). DATA SOURCES AND STUDY SETTING: We extracted and displayed hepatitis B (HBV), hepatitis C (HCV), and tuberculosis (TB) screening data from the EHR for users of b/tsDMARDs using PowerBI (Microsoft) and deployed the dashboard to VA facilities across the United States in 2022; we observed facilities for 44 weeks post-deployment. STUDY DESIGN: We examined the association between dashboard engagement by healthcare personnel and the percentage of patients with all screenings complete (HBV, HCV, and TB) at the facility level using an interrupted time series. Based on frequency of sessions, facilities were grouped into high- and low/none-engagement categories. We modeled changes in complete screening pre- and post-deployment of the dashboard. DATA COLLECTION METHODS: All VA facilities were eligible for inclusion; excluded facilities participated in design of the dashboard or had <20 patients receiving b/tsDMARDs. Session counts from facility personnel were captured using PowerBI audit log data. Outcomes were assessed weekly based on EHR data extracted via the dashboard itself. PRINCIPAL FINDINGS: Totally 117 facilities (serving a total of 41,224 Veterans prescribed b/tsDMARDs) were included. Before dashboard deployment, across all facilities, 61.5% of patients had all screenings complete, which improved to 66.3% over the course of the study period. The largest improvement (15 percentage points, 60.3%-75.3%) occurred among facilities with high engagement (post-intervention difference in outcome between high and low/none-engagement groups was 0.17 percentage points (pp) per week, 95% confidence interval (0.04 pp, 0.30 pp); p = 0.01). CONCLUSIONS: We observed significant improvements in screening for latent infections among facilities with high engagement with the dashboard, compared with those with fewer sessions.

Automated Electronic Health Record Score to Predict Mortality Risk at the US Department of Veterans Affairs.

BACKGROUND: Terminally ill patients benefit from earlier engagement in palliative care. However, this does not always occur. This project assessed if an already available risk score, the Care Assessment Needs (CAN) score, would be able to identify patients at greatest risk for mortality within 30 days of hospital admission within the Veterans Health Administration (VHA). METHODS: The cohort of this retrospective analysis included all VA acute are patients over 18 years of age with a recent CAN score. The CAN score is an automatically calculated VA risk score that was repurposed to determine if it could predict risk of mortality after acute care admission. Univariate logistic regression was performed to obtain the probability of mortality within 30 days of admission, based on their CAN score. RESULTS: 298,467 patient records were assessed from January 1, 2019, to December 31, 2019. There was 6% mortality after 30 days of admissions, and 17% mortality within 1-year post-admission. Mean CAN score was 65 (SD: 29). On average, each incremental increase in the CAN score increased the probability of mortality by 7%. Patients with a CAN score of 90 had a 10% probability of 30-day post-admission mortality. CONCLUSION: A readily available risk score, automatically calculated from EHR data, was able to identify patients at high risk for 30-day mortality in the acute care setting. Next steps will be to assess how the CAN score can be utilized to in improve end of life care for high-risk hospitalized Veterans.

Impact of Risk Factors on COVID-19 Outcomes in Unvaccinated People With Rheumatic Diseases: A Comparative Analysis of Pandemic Epochs Using the COVID-19 Global Rheumatology Alliance Registry.

OBJECTIVE: Approximately one third of individuals worldwide have not received a COVID-19 vaccine. Although studies have investigated risk factors linked to severe COVID-19 among unvaccinated people with rheumatic diseases (RDs), we know less about whether these factors changed as the pandemic progressed. We aimed to identify risk factors associated with severe COVID-19 in unvaccinated individuals in different pandemic epochs corresponding to major variants of concern. METHODS: Patients with RDs and COVID-19 were entered into the COVID-19 Global Rheumatology Alliance Registry between March 2020 and June 2022. An ordinal logistic regression model (not hospitalized, hospitalized, and death) was used with date of COVID-19 diagnosis, age, sex, race and/or ethnicity, comorbidities, RD activity, medications, and the human development index (HDI) as covariates. The main analysis included all unvaccinated patients across COVID-19 pandemic epochs; subanalyses stratified patients according to RD types. RESULTS: Among 19,256 unvaccinated people with RDs and COVID-19, those who were older, male, had more comorbidities, used glucocorticoids, had higher disease activity, or lived in lower HDI regions had worse outcomes across epochs. For those with rheumatoid arthritis, sulfasalazine and B-cell-depleting therapy were associated with worse outcomes, and tumor necrosis factor inhibitors were associated with improved outcomes. In those with connective tissue disease or vasculitis, B-cell-depleting therapy was associated with worse outcomes. CONCLUSION: Risk factors for severe COVID-19 outcomes were similar throughout pandemic epochs in unvaccinated people with RDs. Ongoing efforts, including vaccination, are needed to reduce COVID-19 severity in this population, particularly in those with medical and social vulnerabilities identified in this study.

Proteasomal pathway inhibition as a potential therapy for NF2-associated meningioma and schwannoma.

BACKGROUND: Neurofibromatosis 2 (NF2) is an inherited disorder caused by bi-allelic inactivation of the NF2 tumor suppressor gene. NF2-associated tumors, including schwannoma and meningioma, are resistant to chemotherapy, often recurring despite surgery and/or radiation, and have generally shown cytostatic response to signal transduction pathway inhibitors, highlighting the need for improved cytotoxic therapies. METHODS: Leveraging data from our previous high-throughput drug screening in NF2 preclinical models, we identified a class of compounds targeting the ubiquitin-proteasome pathway (UPP), and undertook studies using candidate UPP inhibitors, ixazomib/MLN9708, pevonedistat/MLN4924, and TAK-243/MLN7243. Employing human primary and immortalized meningioma (MN) cell lines, CRISPR-modified Schwann cells (SCs), and mouse Nf2-/- SCs, we performed dose response testing, flow cytometry-based Annexin V and cell cycle analyses, and RNA-sequencing to identify potential underlying mechanisms of apoptosis. In vivo efficacy was also assessed in orthotopic NF2-deficient meningioma and schwannoma tumor models. RESULTS: Testing of three UPP inhibitors demonstrated potent reduction in cell viability and induction of apoptosis for ixazomib or TAK-243, but not pevonedistat. In vitro analyses revealed that ixazomib or TAK-243 downregulates expression of c-KIT and PDGFRα, as well as the E3 ubiquitin ligase SKP2 while upregulating genes associated with endoplasmic reticulum stress-mediated activation of the unfolded protein response (UPR). In vivo treatment of mouse models revealed delayed tumor growth, suggesting a therapeutic potential. CONCLUSIONS: This study demonstrates the efficacy of proteasomal pathway inhibitors in meningioma and schwannoma preclinical models and lays the groundwork for use of these drugs as a promising novel treatment strategy for NF2 patients.

USP13 promotes development and metastasis of high-grade serous ovarian carcinoma in a novel mouse model.

Epithelial ovarian cancer is the most lethal gynecologic malignancy and one of the most common causes of cancer mortality among women worldwide. Ubiquitin-Specific Peptidase 13 (USP13) gene copy is strongly amplified in human epithelial ovarian cancer, and high USP13 expression is correlated with poor survival outcomes. Yet, its pathological contribution to ovarian tumorigenesis remains unknown. We crossed a conditional Usp13 overexpressing knock-in mouse with a conditional knockout of Trp53 and Pten mouse and generated a novel ovarian cancer genetically engineered mouse model (GEMM), which closely recapitulates the genetic changes driving ovarian cancer in humans. Overexpression of USP13 with deletion of Trp53 and Pten in murine ovarian surface epithelium accelerated ovarian tumorigenesis and led to decreased survival in mice. Notably, USP13 greatly enhanced peritoneal metastasis of ovarian tumors with frequent development of hemorrhagic ascites. The primary and metastatic tumors exhibited morphology and clinical behavior similar to human high-grade serous ovarian cancer. Co-inhibition of USP13 and AKT significantly decreased the viability of the primary murine ovarian cancer cells isolated from the GEMM. USP13 also increased the tumorigenic and metastatic abilities of primary murine ovarian cancer cells in a syngeneic mouse study. These findings suggest a critical role of USP13 in ovarian cancer development and reveal USP13 as a potential therapeutic target for ovarian cancer.

Continuous theta-burst stimulation modulates language-related inhibitory processes in bilinguals: evidence from event-related potentials.

The dorsolateral prefrontal cortex (DLPFC) is activated when bilinguals switch between languages. Language switching can also elicit the N2 event-related potential (ERP). This ERP component appears to capture the cognitive control processes related to conflict monitoring, response selection and response inhibition. In the present study, continuous theta-burst stimulation (cTBS) was used to examine the role of the left DLPFC in bilingual language switching, using a picture-naming task. Participants in the study were 17 Afrikaans-English bilinguals. The picture-naming task consisted of non-switch and switch trials. On non-switch trials, participants named two consecutive pictures in the same language. On switch trials, participants named consecutive pictures in different languages (e.g., Afrikaans and then English). The participants completed three testing sessions. In each session, participants received either cTBS to the left DLPFC or the vertex, or sham stimulation, and then completed the picture-naming task. The results showed that following DLPFC stimulation, the N2 ERP was attenuated on switch trials compared to non-switch trials. Vertex or sham stimulation did not modulate the N2 ERP. cTBS did not affect language switching at the behavioural level. These results provide support for the role of the left DLPFC in the cognitive control processes underlying bilingual language switching. Furthermore, the study demonstrates that these processes can be modulated via non-invasive brain stimulation and the effects detected at the neural level.

Salt concentration modulates the DNA target search strategy of NdeI.

DNA target search is a key step in cellular transactions that access genomic information. How DNA binding proteins combine 3D diffusion, sliding and hopping into an overall search strategy remains poorly understood. Here we report the use of a single molecule DNA tethering method to characterize the target search kinetics of the type II restriction endonuclease NdeI. The measured search rate depends strongly on DNA length as well as salt concentration. Using roadblocks, we show that there are significant changes in the DNA sliding length over the salt concentrations in our study. To explain our results, we propose a model including cycles of 3D and 1D search in which salt concentration modulates the strategy by varying the length of DNA probed per 1D scan. At low salt NdeI makes a single non-specific encounter with DNA followed by an effective and complete 1D scan. At higher salt, NdeI must execute multiple cycles of target search due to the reduced efficacy of 1D search.

Meta-Analysis Reveals a Bilingual Advantage That Is Dependent on Task and Age.

Debate continues on whether a bilingual advantage exists with respect to executive functioning. This report synthesized the results of 170 studies to test whether the bilingual advantage is dependent on the task used to assess executive functioning and the age of the participants. The results of the meta-analyses indicated that the bilingual advantage was both task- and age-specific. Bilinguals were significantly faster than monolinguals (Hedges' g values ranged from 0.23 to 0.34), and significantly more accurate than monolinguals (Hedges' g values ranged between 0.18 and 0.49) on four out of seven tasks. Also, an effect of age was found whereby the bilingual advantage was larger for studies comprising samples aged 50-years and over (Hedges' g = 0.49), compared to those undertaken with participants aged between 18 and 29 years (Hedges' g = 0.12). The extent to which the bilingual advantage might be due to publication bias was assessed using multiple methods. These were Egger's Test of Asymmetry, Duval and Tweedie's Trim and Fill, Classic Fail-Safe N, and PET-PEESE. Publication bias was only found when using Egger's Test of Asymmetry and PET-PEESE method, but not when using the other methods. This review indicates that if bilingualism does enhance executive functioning, the effects are modulated by task and age. This may arise because using multiple languages has a highly specific effect on executive functioning which is only observable in older, relative to younger, adults. The finding that publication bias was not uniformly detected across the different methods raises questions about the impact that unpublished (or undetected) studies have on meta-analyses of this literature.