Chengxi Zang
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View article: Schizophrenia, Bipolar, or Major Depressive Disorder and Postacute Sequelae of COVID-19
Schizophrenia, Bipolar, or Major Depressive Disorder and Postacute Sequelae of COVID-19 Open
Importance Given the increased vulnerability to COVID-19 among those with a serious mental illness (SMI), it remains unclear whether these individuals face a higher risk of developing postacute sequelae of SARS-CoV-2 (PASC). Understanding …
View article: Machine Learning for Dynamic and Short-term Prediction of Preeclampsia Using Routine Clinical and Laboratory Data
Machine Learning for Dynamic and Short-term Prediction of Preeclampsia Using Routine Clinical and Laboratory Data Open
Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality, yet its unpredictable onset and rapid progression hinder timely management. Existing prediction tools often rely on specialized biomarkers, static asse…
View article: Extracting post-acute sequelae of SARS-CoV-2 infection symptoms from clinical notes via hybrid natural language processing
Extracting post-acute sequelae of SARS-CoV-2 infection symptoms from clinical notes via hybrid natural language processing Open
Accurately and efficiently diagnosing Post-Acute Sequelae of COVID-19 (PASC) remains challenging due to its myriad symptoms that evolve over long- and variable-time intervals. To address this issue, we developed a hybrid natural language p…
View article: Extracting Post-Acute Sequelae of SARS-CoV-2 Infection Symptoms from Clinical Notes via Hybrid Natural Language Processing
Extracting Post-Acute Sequelae of SARS-CoV-2 Infection Symptoms from Clinical Notes via Hybrid Natural Language Processing Open
Accurately and efficiently diagnosing Post-Acute Sequelae of COVID-19 (PASC) remains challenging due to its myriad symptoms that evolve over long- and variable-time intervals. To address this issue, we developed a hybrid natural language p…
View article: Federated target trial emulation using distributed observational data for treatment effect estimation
Federated target trial emulation using distributed observational data for treatment effect estimation Open
View article: Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory
Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory Open
Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, including septic shock, pneumonia and the acute respiratory distress syndrome (ARDS). The risk…
View article: Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation
Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation Open
Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and …
View article: Federated Causal Inference in Healthcare: Methods, Challenges, and Applications
Federated Causal Inference in Healthcare: Methods, Challenges, and Applications Open
Federated causal inference enables multi-site treatment effect estimation without sharing individual-level data, offering a privacy-preserving solution for real-world evidence generation. However, data heterogeneity across sites, manifeste…
View article: TrialGenie: Empowering Clinical Trial Design with Agentic Intelligence and Real World Data
TrialGenie: Empowering Clinical Trial Design with Agentic Intelligence and Real World Data Open
Clinical trial design (CTD) is a time-consuming process that requires substantial domain expertise. Large-scale real-world data (RWD), such as electronic health records (EHR), encodes practice-based evidence that is of tremendous value to …
View article: Assessment of Nirmatrelvir-Ritonavir Effects on Acute and Post-Acute COVID-19 Illness in US Adolescents: Target Trial Emulation
Assessment of Nirmatrelvir-Ritonavir Effects on Acute and Post-Acute COVID-19 Illness in US Adolescents: Target Trial Emulation Open
IMPORTANCE Nirmatrelvir-ritonavir, an efficacious treatment for acute COVID-19, has yielded conflicting evidence regarding its effectiveness in preventing Long COVID among adults. The effectiveness of nirmatrelvir-ritonavir in adolescents …
View article: Long COVID after SARS-CoV-2 during pregnancy in the United States
Long COVID after SARS-CoV-2 during pregnancy in the United States Open
Pregnancy alters immune responses and clinical manifestations of COVID-19, but its impact on Long COVID remains uncertain. This study investigated Long COVID risk in individuals with SARS-CoV-2 infection during pregnancy compared to reprod…
View article: A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease
A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease Open
View article: Single‐microglia transcriptomic transition network‐based prediction and real‐world patient data validation identifies ketorolac as a repurposable drug for Alzheimer's disease
Single‐microglia transcriptomic transition network‐based prediction and real‐world patient data validation identifies ketorolac as a repurposable drug for Alzheimer's disease Open
INTRODUCTION High microglial heterogeneities hinder the development of microglia‐targeted treatment for Alzheimer's disease (AD). METHODS We integrated 0.7 million single‐nuclei RNA‐sequencing transcriptomes from human brains using a varia…
View article: Post-Acute Sequelae of SARS-CoV-2 Infection in Pregnant Females: An Electronic Health Records Analysis from the RECOVER Initiative (PCORnet and N3C)
Post-Acute Sequelae of SARS-CoV-2 Infection in Pregnant Females: An Electronic Health Records Analysis from the RECOVER Initiative (PCORnet and N3C) Open
While pregnancy has been associated with an altered immune response and distinct clinical manifestations of COVID-19, the influence of pregnancy on the persistence and severity of post-acute sequelae of SARS-CoV-2 infection (PASC), or Long…
View article: Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records
Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records Open
View article: Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts
Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts Open
View article: Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients – A Large-Scale Observational Cohort Study from the RECOVER Initiative
Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients – A Large-Scale Observational Cohort Study from the RECOVER Initiative Open
View article: Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER program
Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER program Open
Importance The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. Objective To characterize PASC-related conditions among individuals likely infected by the ancestral strain …
View article: Association between acquiring SARS-CoV-2 during pregnancy and post-acute sequelae of SARS-CoV-2 infection: RECOVER electronic health record cohort analysis
Association between acquiring SARS-CoV-2 during pregnancy and post-acute sequelae of SARS-CoV-2 infection: RECOVER electronic health record cohort analysis Open
View article: Emerging opportunities of using large language models for translation between drug molecules and indications
Emerging opportunities of using large language models for translation between drug molecules and indications Open
A drug molecule is a substance that changes an organism’s mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Langua…
View article: Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative
Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative Open
View article: Corticosteroids for infectious critical illness: A multicenter target trial emulation stratified by predicted organ dysfunction trajectory
Corticosteroids for infectious critical illness: A multicenter target trial emulation stratified by predicted organ dysfunction trajectory Open
Corticosteroids decrease the duration of organ dysfunction in a range of infectious critical illnesses, but their risk and benefit are not fully defined using this construct. This retrospective multicenter study aimed to evaluate the assoc…
View article: Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications
Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications Open
A drug molecule is a substance that changes the organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Langu…
View article: High-throughput target trial emulation for Alzheimer’s disease drug repurposing with real-world data
High-throughput target trial emulation for Alzheimer’s disease drug repurposing with real-world data Open
Target trial emulation is the process of mimicking target randomized trials using real-world data, where effective confounding control for unbiased treatment effect estimation remains a main challenge. Although various approaches have been…
View article: Accuracy and generalizability of machine learning models for adolescent suicide prediction with longitudinal clinical records
Accuracy and generalizability of machine learning models for adolescent suicide prediction with longitudinal clinical records Open
Machine Learning (ML) models trained from real-world data (RWD) have demonstrated promise in predicting suicide attempts in adolescents. However, their cross-data performance and transportability for suicide prediction are largely unknown,…
View article: Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records
Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records Open
The objective of this study was to investigate the potential association between the use of four frequently prescribed drug classes, namely antihypertensive drugs, statins, selective serotonin reuptake inhibitors, and proton-pump inhibitor…
View article: Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative
Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative Open
Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with s…
View article: Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative
Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative Open
View article: Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER Program
Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER Program Open
Importance The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. Objective To characterize PASC-related conditions among individuals likely infected by the ancestral strain …
View article: Racial/Ethnic Disparities in Post-acute Sequelae of SARS-CoV-2 Infection in New York: an EHR-Based Cohort Study from the RECOVER Program
Racial/Ethnic Disparities in Post-acute Sequelae of SARS-CoV-2 Infection in New York: an EHR-Based Cohort Study from the RECOVER Program Open
Background Compared to white individuals, Black and Hispanic individuals have higher rates of COVID-19 hospitalization and death. Less is known about racial/ethnic differences in post-acute sequelae of SARS-CoV-2 infection (PASC). Objectiv…