Publications by authors named "Yashar Talebi"

Background: Understanding the distinct immunologic responses to SARS-CoV-2 infection among pediatric populations is pivotal in navigating the COVID-19 pandemic and informing future public health strategies. This study aimed to identify factors associated with heightened antibody responses in children and adolescents to identify potential unique immune dynamics in this population.

Methods: Data collected between July and December 2023 from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a statewide prospective population-based antibody survey among 1-to-19-year-old participants, were analyzed.

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Background: Cognitive impairment (CI) and stroke are diseases with significant disparities in race and geography. Post stroke cognitive impairment (PSCI) can be as high as 15-70 % but few studies have utilized large administrative or electronic health records (EHR) to evaluate trends in PSCI. We utilized an EHR database to evaluate for disparities in PSCI in a large sample of patients after first recorded stroke to evaluate for disparities in race.

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Introduction: Studies indicate that individuals with chronic conditions and specific baseline characteristics may not mount a robust humoral antibody response to SARS-CoV-2 vaccines. In this paper, we used data from the Texas Coronavirus Antibody REsponse Survey (Texas CARES), a longitudinal state-wide seroprevalence program that has enrolled more than 90,000 participants, to evaluate the role of chronic diseases as the potential risk factors of non-response to SARS-CoV-2 vaccines in a large epidemiologic cohort.

Methods: A participant needed to complete an online survey and a blood draw to test for SARS-CoV-2 circulating plasma antibodies at four-time points spaced at least three months apart.

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Background: This analysis examined the durability of antibodies present after SARS-CoV-2 infection and vaccination in children and adolescents.

Methods: Data were collected over 4 time points between October 2020-November 2022 as part of a prospective population-based cohort aged 5-to-19 years (N = 810). Results of the (1) Roche Elecsys® Anti-SARS-CoV-2 Immunoassay for detection of antibodies to the SARS-CoV-2 nucleocapsid protein (Roche N-test); and (2) qualitative and semi-quantitative detection of antibodies to the SARS CoV-2 spike protein receptor binding domain (Roche S-test); and (3) self-reported antigen/PCR COVID-19 test results, vaccination and symptom status were analyzed.

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Objective: To describe COVID-19 illness characteristics, risk factors, and SARS-CoV-2 serostatus by variant time period in a large community-based pediatric sample.

Design: Data were collected prospectively over four timepoints between October 2020 and November 2022 from a population-based cohort ages 5 to 19 years old.

Setting: State of Texas, USA.

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Background: Perinatal stroke occurs in approximately 1 in 1100 live births. Large electronic health record (EHR) data can provide information on exposures associated with perinatal stroke in a larger number of patients than is achievable through traditional clinical studies. The objective of this study is to assess prevalence and odds ratios of known and theorized comorbidities with perinatal ischemic and hemorrhagic stroke.

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Background: Breakthrough infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are well documented. The current study estimates breakthrough incidence across pandemic waves, and evaluates predictors of breakthrough and severe breakthrough infections (defined as those requiring hospitalization).

Methods: In total, 89 762 participants underwent longitudinal antibody surveillance.

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Accurate estimates of natural and/or vaccine-induced antibodies to SARS-CoV-2 are difficult to obtain. Although model-based estimates of seroprevalence have been proposed, they require inputting unknown parameters including viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach, the current study presents a data-driven detailed statistical procedure for estimating total seroprevalence (defined as antibodies from natural infection or from full vaccination) in a region using prospectively collected serological data and state-level vaccination data.

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Background: The prevalence of long-term symptoms of coronavirus disease 2019 (COVID-19) in nonhospitalized pediatric populations in the United States is not well described. The objective of this analysis was to examine the presence of persistent COVID symptoms in children by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody status.

Methods: Data were collected between October 2020 and May 2022 from the Texas Coronavirus Antibody REsponse Survey, a statewide prospective population-based survey among 5-90 years old.

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Understanding the duration of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody Response Survey (Texas CARES) with at least 1 nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n = 4553) with 1 to 3 antibody tests over 11 months (1 October 2020 to 16 September 2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days postinfection, and predicts individuals may remain antibody positive from natural infection beyond 500 days depending on age, body mass index, smoking or vaping use, and disease severity (hospitalized or not; symptomatic or not).

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Objective: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course would provide valuable information for healthcare providers, patients, and families. This study aims to utilize electronic health record (EHR) data and machine learning approaches to predict the adverse outcome for nontraumatic SAH adult patients.

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Objective: Subarachnoid hemorrhage (SAH) is a devastating cerebrovascular condition, not only due to the effect of initial hemorrhage, but also due to the complication of delayed cerebral ischemia (DCI). While hypertension facilitated by vasopressors is often initiated to prevent DCI, which vasopressor is most effective in improving outcomes is not known. The objective of this study was to determine associations between initial vasopressor choice and mortality in patients with nontraumatic SAH.

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Introduction: Esophageal carcinoma is the scourge of human beings. Pulmonary complications in patients who have undergone operation are common (20-30% of cases) and there are no suitable tools and ways to predict these complications.

Methods: During a period of 10 years, from March 1998 to February 2007, 200 patients (150 male and 50 female) underwent Esophagectomy due to esophageal carcinoma in thoracic surgery ward retrospectively.

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Background: Doppler flow velocity waveform analysis of fetal vessels is one of the main methods for evaluating fetus health before labor. Doppler waves of middle cerebral artery (MCA) can predict most of the at risk fetuses in high risk pregnancies. In this study, we tried to obtain normal values and their nomograms during pregnancy for Doppler flow velocity indices of MCA in 20-40 weeks of normal pregnancies in Iranian population and compare their pattern with other countries' nomograms.

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