Publications by authors named "Lawrence Weinstein"

We report on pregnancy management and outcomes in a 27-year-old female patient with ornithine transcarbamylase (OTC) deficiency, the most common inherited enzyme deficiency in the urea cycle. Our patient was diagnosed during childhood after hyperammonemia associated with surgery and steroid treatment and was well-controlled with nitrogen scavenger treatment, low-protein diet, and L-citrulline supplementation. gene sequencing identified a variant of unknown significance that has more recently been classified as likely pathogenic.

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In 2019, a novel coronavirus called the severe acute respiratory syndrome coronavirus 2 led to the outbreak of the coronavirus disease 2019, which was deemed a pandemic by the World Health Organization in March 2020. Owing to the accelerated rate of mortality and utilization of hospital resources, health care systems had to adapt to these major changes. This affected patient care across all disciplines and specifically within the perioperative services.

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We present the case of a windblown beach umbrella inflicting fatal penetrating blunt force to the chest of a 55-year-old female beachgoer. A postmortem examination and detailed case history review were performed which revealed left ventricular trauma, determined to be the cause of death. Using recorded wind speeds from the date of the incident and the weight of the umbrella, we were able to calculate the pressure with which the umbrella struck the victim to be 16,000 PSI.

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Objective: The purpose of this study was to describe the prescribing practices of clinicians for patients with major depressive disorder (MDD).

Methods: This population-based, descriptive study of insured patients (N=54,107) identified people who were 18 years or older, had a claim for MDD, had at least one prescription for an antidepressant medication in 2013, and had continuous insurance coverage during the study period. Prescription claims were evaluated to determine the most commonly prescribed antidepressant medication and most common dose.

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Introduction: This paper explores the use of machine learning and Bayesian classification models to develop broadly applicable risk stratification models to guide disease management of health plan enrollees with substance use disorder (SUD). While the high costs and morbidities associated with SUD are understood by payers, who manage it through utilization review, acute interventions, coverage and cost limitations, and disease management, the literature shows mixed results for these modalities in improving patient outcomes and controlling cost. Our objective is to evaluate the potential of data mining methods to identify novel risk factors for chronic disease and stratification of enrollee utilization, which can be used to develop new methods for targeting disease management services to maximize benefits to both enrollees and payers.

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To estimate correlations for scores on a student anti-intellectualism scale with scores on a measure of political conservatism, 235 students were given a survey containing a student anti-intellectualism scale, a political conservatism scale, and a demographics questionnaire identifying the participants' sex, college classification, ethnicity, political party affiliation, and self-described political ideology. The political conservatism scale contained two factors, Religiosity and Economic Conservatism, both of which were scored separately in addition to an overall Conservatism score. Students' Anti-intellectualism scores were correlated with Political Conservatism scores (r = .

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Experiment 1 attempted to determine if sex was a controlling factor in the production of negative contrast. The Ss were 60 male and female albino rats 68-104 days of age. In an operant conditioning chamber a saccharine solution was reduced in concentration from 1.

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