scholarly journals 533. Protocol for and Efficacy of Monoclonal Antibody (mAb) Treatment of SARS-CoV-2 at a VA Medical Center

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S367-S368
Author(s):  
Phuong Khanh Nguyen ◽  
Thomas D Dieringer ◽  
Adela Greeley ◽  
Suny Kun ◽  
Feliza Calub ◽  
...  
Keyword(s):  
Relative Risk ◽  
Los Angeles ◽  
Healthcare System ◽  
Medical Center ◽  
Risk Estimation ◽  
Severe Disease ◽  
Rapid Identification ◽  
Estimation Model ◽  
Binomial Regression ◽  
Timely Administration

Abstract Background Bamlanivimab and casirivimab/imdevimab were the first monoclonal antibodies (mAb) developed against SARS-CoV-2 and proved beneficial early in the course of infection. However, real-world administration of these therapies presents logistical challenges. We present our experience implementing mAb treatment at a large VA Medical Center and review the efficacy of therapy in preventing hospitalization from COVID-19 in a closed healthcare system. Methods All positive outpatient COVID tests performed at VA Greater Los Angeles Healthcare System (GLA) were reviewed by the Emergency Medicine (EM) and Infectious Diseases (ID) Sections for mAb eligibility beginning 12/2/2020. Due to limited supply, treatment was prioritized for patients at highest risk of developing severe disease, as determined by EM/ID with input from a machine learning ensemble risk estimation model produced by VA National Artificial Intelligence Institute (Figure 1). If a patient declined or did not reply, treatment was offered to the next patient on a ranked eligibility list. Those who declined or were eligible but not treated were included in the analysis. Patients were excluded if they were hospitalized before treatment was offered. We collected data on age, comorbidities, date of diagnosis, and admission at 30 days after diagnosis. A multivariate log binomial regression was performed to determine the relative risk of admission within 30 days of diagnosis for those who received mAb therapy as compared to those who did not, adjusting for age and comorbidity. All analysis was done in R (version 4.0.5). Results 139 patients met inclusion criteria. 45 (32%) received mAb therapy, 48 (35%) declined mAb therapy, and the remaining 46 (33%) either did not respond or were not offered mAb therapy. Hospitalizations following diagnosis in each group are illustrated in Figure 2. There was a trend towards reduced absolute and relative risk of hospitalization (Table 1). There were no anaphylactic events in patients who received mAb therapy. Conclusion At our facility, a system for rapid identification of candidates and a coordinated distribution plan was essential in ensuring timely administration of mAb therapy to eligible patients. Administration of mAb showed a trend towards decreased risk of hospitalization due to SARS-CoV-2. Disclosures Adela Greeley, MD, Kite (Other Financial or Material Support, My spouse is an employee) Matthew B. Goetz, MD, Nothing to disclose

scholarly journals COVID-19 in obstetrics 2020: the experience at a New York City medical center

2020 ◽  
Vol 48 (9) ◽  
pp. 892-899
Author(s):  
Ashlesha K. Dayal ◽  
Armin S. Razavi ◽  
Amir K. Jaffer ◽  
Nishant Prasad ◽  
Daniel W. Skupski
Keyword(s):  
New York ◽  
Medical Center ◽  
Severe Disease ◽  
Infection Rates ◽  
Health Crisis ◽  
The Public ◽  
Public Health Crisis ◽  
Asymptomatic Carriage ◽  
Global Spread ◽  
Workforce Flexibility

AbstractThe global spread of the SARS-CoV-2 virus during the early months of 2020 was rapid and exposed vulnerabilities in health systems throughout the world. Obstetric SARS-CoV-2 disease was discovered to be largely asymptomatic carriage but included a small rate of severe disease with rapid decompensation in otherwise healthy women. Higher rates of hospitalization, Intensive Care Unit (ICU) admission and intubation, along with higher infection rates in minority and disadvantaged populations have been documented across regions. The operational gymnastics that occurred daily during the Covid-19 emergency needed to be translated to the obstetrics realm, both inpatient and ambulatory. Resources for adaptation to the public health crisis included workforce flexibility, frequent communication of operational and protocol changes for evaluation and management, and application of innovative ideas to meet the demand.

scholarly journals Impact of COVID-19 infection among cancer patients treated at the Los Angeles County Medical Center

2021 ◽  
Vol 26 ◽  
pp. 100273
Author(s):  
Lauren Antrim ◽  
Stephen Capone ◽  
Stephen Dong ◽  
David Chung ◽  
Sonia Lin ◽  
...  
Keyword(s):  
Los Angeles ◽  
Cancer Patients ◽  
Los Angeles County ◽  
Medical Center

scholarly journals Impact of the COVID-19 Vaccine on Asymptomatic Infection Among Patients Undergoing Pre-Procedural COVID-19 Molecular Screening

2021 ◽  
Author(s):  
Aaron J Tande ◽  
Benjamin D Pollock ◽  
Nilay D Shah ◽  
Gianrico Farrugia ◽  
Abinash Virk ◽  
...  
Keyword(s):  
United States ◽  
Relative Risk ◽  
Healthcare System ◽  
The United States ◽  
Asymptomatic Infection ◽  
Screening Tests ◽  
Molecular Screening ◽  
Molecular Tests ◽  
Asymptomatic Individuals ◽  
The Impact

Abstract Background Several vaccines are now clinically available under emergency use authorization in the United States and have demonstrated efficacy against symptomatic COVID-19. The impact of vaccines on asymptomatic SARS-CoV-2 infection is largely unknown. Methods We conducted a retrospective cohort study of consecutive, asymptomatic adult patients (n = 39,156) within a large United States healthcare system who underwent 48,333 pre-procedural SARS-CoV-2 molecular screening tests between December 17, 2020 and February 8, 2021. The primary exposure of interest was vaccination with at least one dose of an mRNA COVID-19 vaccine. The primary outcome was relative risk of a positive SARS-CoV-2 molecular test among those asymptomatic persons who had received at least one dose of vaccine, as compared to persons who had not received vaccine during the same time period. Relative risk was adjusted for age, sex, race/ethnicity, patient residence relative to the hospital (local vs. non-local), healthcare system regions, and repeated screenings among patients using mixed effects log-binomial regression. Results Positive molecular tests in asymptomatic individuals were reported in 42 (1.4%) of 3,006 tests performed on vaccinated patients and 1,436 (3.2%) of 45,327 tests performed on unvaccinated patients (RR=0.44 95% CI: 0.33-0.60; p<.0001). Compared to unvaccinated patients, the risk of asymptomatic SARS-CoV-2 infection was lower among those >10 days after 1 st dose (RR=0.21; 95% CI: 0.12-0.37; p<.0001) and >0 days after 2 nd dose (RR=0.20; 95% CI: 0.09-0.44; p<.0001) in the adjusted analysis. Conclusions COVID-19 vaccination with an mRNA-based vaccine showed a significant association with a reduced risk of asymptomatic SARS-CoV-2 infection as measured during pre-procedural molecular screening. The results of this study demonstrate the impact of the vaccines on reduction in asymptomatic infections supplementing the randomized trial results on symptomatic patients.

scholarly journals An Estimation of Ship Collision Risk Based on Relevance Vector Machine

2021 ◽  
Vol 9 (5) ◽  
pp. 538
Author(s):  
Jinwan Park ◽  
Jung-Sik Jeong
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Risk Estimation ◽  
Good Method ◽  
Relevance Vector Machine ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Collision Risk ◽  
Estimation Model ◽  
Ship Collision

According to the statistics of maritime collision accidents over the last five years (2016–2020), 95% of the total maritime collision accidents are caused by human factors. Machine learning algorithms are an emerging approach in judging the risk of collision among vessels and supporting reliable decision-making prior to any behaviors for collision avoidance. As the result, it can be a good method to reduce errors caused by navigators’ carelessness. This article aims to propose an enhanced machine learning method to estimate ship collision risk and to support more reliable decision-making for ship collision risk. In order to estimate the ship collision risk, the conventional support vector machine (SVM) was applied. Regardless of the advantage of the SVM to resolve the uncertainty problem by using the collected ships’ parameters, it has inherent weak points. In this study, the relevance vector machine (RVM), which can present reliable probabilistic results based on Bayesian theory, was applied to estimate the collision risk. The proposed method was compared with the results of applying the SVM. It showed that the estimation model using RVM is more accurate and efficient than the model using SVM. We expect to support the reasonable decision-making of the navigator through more accurate risk estimation, thus allowing early evasive actions.

scholarly journals Association of CYP3A7*1C and Serum Dehydroepiandrosterone Sulfate Levels in Women with Polycystic Ovary Syndrome

2008 ◽  
Vol 93 (7) ◽  
pp. 2909-2912 ◽  
Author(s):  
Mark O. Goodarzi ◽  
Ning Xu ◽  
Ricardo Azziz
Keyword(s):  
Los Angeles ◽  
Polycystic Ovary Syndrome ◽  
White Women ◽  
Polycystic Ovary ◽  
Medical Center ◽  
Free Testosterone ◽  
Total Testosterone ◽  
Adrenal Androgen ◽  
Androgen Excess ◽  
Ovary Syndrome

Abstract Context: Adrenal androgen excess is common in polycystic ovary syndrome (PCOS) and appears to be heritable. CYP3A7 metabolizes dehydroepiandrosterone and its sulfate (DHEAS). A promoter variant, CYP3A7*1C, which results in persistent expression in adults, was associated with reduced DHEAS levels in a previous study, which led us to consider CYP3A7*1C as a modulator of adrenal androgen excess in patients with PCOS. Objective: The objective was to replicate the association between CYP3A7*1C and reduced DHEAS levels in PCOS patients and assess its possible role in modulating testosterone levels. Design: Women with and without PCOS were genotyped for CYP3A7*1C, and this variant was tested for association with DHEAS and total and free testosterone. Setting: Subjects were recruited from the reproductive endocrinology clinic at the University of Alabama at Birmingham; controls were recruited from the surrounding community. Genotyping took place at Cedars-Sinai Medical Center (Los Angeles, CA). Participants: A total of 287 white women with PCOS and 187 controls were studied. Main Measurements: CYP3A7*1C genotype, PCOS risk, and androgen levels were measured. Results: PCOS subjects who carried the CYP3A7*1C variant had lower levels of serum DHEAS and total testosterone (P = 0.0006 and 0.046, respectively). The variant was not associated with PCOS risk. Conclusion: This study replicated prior work of the association of CYP3A7*1C and decreased DHEAS in a different population of young PCOS women, providing further genetic evidence that CYP3A7 plays a potential role in modulation of DHEAS levels. Adult expression of CYP3A7 may modify the PCOS phenotype by ameliorating adrenal androgen excess.

Development of neurosurgery in Southern California and the Los Angeles County/University of Southern California Medical Center

1993 ◽  
Vol 79 (1) ◽  
pp. 145-148
Author(s):  
John H. Schneider ◽  
Martin H. Weiss ◽  
William T. Couldwell
Keyword(s):  
Los Angeles ◽  
Los Angeles County ◽  
Southern California ◽  
Medical Center ◽  
University Of Southern California ◽  
Content Type ◽  
School Of Medicine ◽  
Integral Role ◽  
Southern California School ◽  
The University

✓ The Los Angeles County General Hospital has played an integral role in the development of medicine and neurosurgery in Southern California. From its fledgling beginnings, the University of Southern California School of Medicine has been closely affiliated with the hospital, providing the predominant source of clinicians to care for and to utilize as a teaching resource the immense and varied patient population it serves.

Sample size estimation for modified Poisson analysis of cluster randomized trials with a binary outcome

2021 ◽  
pp. 096228022199041
Author(s):  
Fan Li ◽  
Guangyu Tong
Keyword(s):  
Relative Risk ◽  
Sample Size ◽  
Poisson Regression ◽  
Cluster Size ◽  
Randomized Trials ◽  
Cluster Randomized Trials ◽  
Binomial Regression ◽  
Size Variability ◽  
Working Correlation ◽  
Cluster Randomized

The modified Poisson regression coupled with a robust sandwich variance has become a viable alternative to log-binomial regression for estimating the marginal relative risk in cluster randomized trials. However, a corresponding sample size formula for relative risk regression via the modified Poisson model is currently not available for cluster randomized trials. Through analytical derivations, we show that there is no loss of asymptotic efficiency for estimating the marginal relative risk via the modified Poisson regression relative to the log-binomial regression. This finding holds both under the independence working correlation and under the exchangeable working correlation provided a simple modification is used to obtain the consistent intraclass correlation coefficient estimate. Therefore, the sample size formulas developed for log-binomial regression naturally apply to the modified Poisson regression in cluster randomized trials. We further extend the sample size formulas to accommodate variable cluster sizes. An extensive Monte Carlo simulation study is carried out to validate the proposed formulas. We find that the proposed formulas have satisfactory performance across a range of cluster size variability, as long as suitable finite-sample corrections are applied to the sandwich variance estimator and the number of clusters is at least 10. Our findings also suggest that the sample size estimate under the exchangeable working correlation is more robust to cluster size variability, and recommend the use of an exchangeable working correlation over an independence working correlation for both design and analysis. The proposed sample size formulas are illustrated using the Stop Colorectal Cancer (STOP CRC) trial.

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